DOE/EIA-0581(2009)



# The Na tional En ergy Mod el ing

Sys tem: An Over view 2009

October 2009

En ergy In for ma tion Ad min is tra tion Of fice of In te grated Anal y sis and Fore cast ing U.S. De part ment of En ergy Wash ing ton, DC 20585

This re port was pre pared by the En ergy In for ma tion Ad min is tra tion, the in de pend ent sta tis ti cal and an a lyt i cal agency within the U.S. De part ment of En ergy. The in for ma tion con tained herein should be at trib uted to the En ergy In for ma tion Ad min is tra tion and should not be con strued as ad vo cat ing or re flect ing any pol icy po si tion of the De part ment of En ergy or any other or ga ni za tion. 

### This pub li ca tion is on the WEB at: www.eia.doe.gov/oiaf/aeo/over view/The Na tional En ergy Mod el ing Sys tem: An Over view 200 9 pro vides a sum mary de scrip tion of the Na tional En ergy

Mod el ing Sys tem, which was used to gen er ate the pro jec tions of en ergy pro duc tion, de mand, im ports, and prices through the year 20 30 for the An nual En ergy Out look 2009, (DOE/EIA-0383(200 9 )), re leased in March 200 9

. AEO2009

pres ents na tional pro jec tions of en ergy mar kets for five pri mary cases—a ref er ence case and four ad di
- tional cases that as sume higher and lower eco nomic growth and higher and lower world oil prices than in the ref er
- ence case. The Over view pres ents a brief de scrip tion of the meth od ol ogy and scope of each of the com po nent mod ules of NEMS. The model doc u men ta tion re ports listed in the ap pen dix of this doc u ment pro vide fur ther de tails. The Over view was pre pared by the En ergy In for ma tion Ad min is tra tion, Of fice of In te grated Anal y sis and Fore cast ing un der the di rec tion of John J. Conti ( john.conti@ eia.doe.gov, 202/586-2222), Di rec tor , Of fice of In te grated Anal y sis and Fore cast ing; Paul D. Holtberg (paul.holtberg@eia.doe.gov, 202/586-1284), Di rec tor of the De mand and In te gra
- tion Di vi sion; Jo seph A. Beamon ( jbeamon@eia. doe.gov, 202/586- 2025 ), Di rec tor of the Coal and Elec tric Power Di
- vi sion; A. Mi chael Schaal (mi chael,schaal@eia.doe.gov, 202/586-5590), Di rec tor of the Oil and Gas Di vi sion; Glen E. Sweetnam ( glen.sweetnam @eia.doe.gov, 202-586- 2188 ), Di rec tor, In ter na tional, Eco nomic, and Green house Gases Di vi sion; and Andy S. Kydes (akydes@eia.doe.gov, 202/586-2222), Se nior Tech ni cal Ad vi sor. De tailed ques tions con cern ing the Na tional En ergy Mod el ing Sys tem and the An nual En ergy Out look 2009may be ad dressed to the fol low ing an a lysts: AEO2009

................. Paul D. Holtberg (paul.holtberg@eia.doe.gov, 202/586-1284) In te grat ing Mod ule/Car bon Emis sions

... Dan iel H. Skelly (dan iel.skelly@eia.doe.gov, 202-586-1722) Mac ro eco nomic Ac tiv ity Mod ule

...... Kay A. Smith (kay.smith@eia.doe.gov, 202/586-1132) In ter na tional En ergy Mod ule

........ Adrian Geagla (adrian.geagla@eia.doe.gov, 202/586-2873) Res i den tial De mand

............ John H. Cymbalsky (john.cymbalsky@eia.doe.gov, 202/586-4815) Com mer cial De mand

........... Erin E. Boedecker (erin.boedecker@eia.doe.gov, 202/586-4791) In dus trial De mand

............. Amelia L. Elson (amelia.elson@eia.doe.gov, 202/586-1420) Trans por ta tion De mand

.......... John D. Ma ples (john.ma ples@eia.doe.gov, 202/586-1757) Elec tric ity De mand Mod ule

........ Jeffrey S. Jones (jeffrey.jones@eia.doe.gov, 202/586-2038) Re new able Fu els Mod ule

......... Chris R. Namovicz (chris.namovicz@eia.doe.gov, 202/586-7120) Oil and Gas Sup ply Mod ule

........ Eddie L. Thomas, Jr. (eddie.thomas@eia.doe.gov, 202/586-5877) Nat u ral Gas Trans mis sion and Dis tri bu tion Mod ule

................. Jo seph G. Benneche (jo seph.benneche@eia.doe.gov, 202/586-6132) Pe tro leum Mar ket Mod ule

......... Wil liam S. Brown (wil liam.brown@eia.doe.gov, 202/586-8181) Coal Mar ket Mod ule

............ Di ane R. Kear ney (di ane.kear ney@eia.doe.gov, 202/586-2415) AEO2009

is avail able on the EIA Home Page on the Internet (http://www.eia.doe.gov/oiaf/aeo/in dex.html). As sump
- tions un der ly ing the pro jec tions are avail able in As sump tions to the An nual En ergy Out look 200 9 at http://www.eia.doe.gov/oiaf/aeo/as sump tion/in dex.html. Ta bles of re gional pro jec tions and other un der ly ing de tails of the ref er ence case are avail able at http://www.eia.doe.gov/oiaf/aeo/sup ple ment/in dex.html. Model doc u men ta tion re ports and The Na tional En ergy Mod el ing Sys tem: An Over view 200 9 are also avail able on the Home Page at http://tonto.eia.doe.gov/re ports/re ports_kindD.asp?type=model doc u men ta tion. For or der ing in for ma tion and for ques tions on en ergy sta tis tics, please con tact EIA’s Na tional En ergy In for ma tion Cen ter. Na tional En ergy In for ma tion Cen ter, EI-30 En ergy In for ma tion Ad min is tra tion, Forrestal Build ing Wash ing ton, DC 20585, Tele phone: 202/586-8800 FAX: 202/586-0727, TTY: 202/586-1181 9 a.m. to 5 p.m., east ern time, M-F E-mail: infoctr@eia.doe.gov World Wide Web Site: http://www.eia.doe.gov, FTP Site: ftp://ftp.eia.doe.gov

ii Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# PrefaceEnergy Information Administration / The National Energy Modeling System: An Overview 2009 iii 

# Contents

Pref ace

.............................................................................. ii Introduction

........................................................................... 1 Over view of NEMS

...................................................................... 6 Car bon Diox ide and Meth ane Emissions

.................................................... 12 Mac ro eco nomic Activ ity Module

........................................................... 14 Inter na tional Energy Module

.............................................................. 17 Res i den tial Demand Module

.............................................................. 20 Com mer cial Demand Module

............................................................. 25 Indus trial Demand Module

................................................................ 32 Trans por ta tion Demand Module

........................................................... 37 Elec tric ity Mar ket Module

................................................................. 43 Renew able Fuels Module

................................................................ 50 Oil and Gas Sup ply Module

............................................................... 54 Nat u ral Gas Trans mis sion and Dis tri bu tion Module

............................................ 59 Petro leum Mar ket Module

................................................................ 64 Coal Mar ket Module

..................................................................... 71 Appen dix: Bib li og ra phy

.................................................................. 77Figures

iv Energy Information Administration / The National Energy Modeling System : An Overview 2009 

# Contents

1. Census Divisions

.................................................................... 8 2. National Energy Modeling System

...................................................... 9 3. Macroeconomic Activity Module Structure

................................................. 15 4. International Energy Module Structure

.................................................... 18 5. Residential Demand Module Structure

.................................................... 21 6. Commercial Demand Module Structure

................................................... 26 7. Industrial Demand Module Structure

..................................................... 33 8. Transportation Demand Module Structure

................................................. 39 9. Electricity Market Module Structure

...................................................... 44 10. Electricity Market Module Supply Regions

................................................. 45 11. Renewable Fuels Module Structure

...................................................... 51 12. Oil and Gas Supply Module Regions

..................................................... 55 13. Oil and Gas Supply Module Structure

.................................................... 56 14. Natural Gas Transmission and Distribution Module Structure

.................................. 60 15. Natural Gas Transmission and Distribution Module Network

................................... 62 16. Petroleum Market Module Structure

...................................................... 65 17. Petroleum Administration for Defense Districts

............................................. 66 18. Coal Market Module Demand Regions

................................................... 72 19. Coal Market Module Supply Regions

..................................................... 73 20. Coal Market Module Structure

.......................................................... 75Ta bles

v Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Contents

1. Characteristics of Selected Modules

..................................................... 6 2. NEMS Residential Module Equipment Summary

............................................ 22 3. Characteristics of Selected Equipment

................................................... 23 4. Capital Cost and Efficiency Ratings of Selected Commercial Space Heating Equipment

............. 29 5. Commercial End-Use Technology Types

.................................................. 30 6. Economic subsectors Within the IDM

..................................................... 32 7. Fuel-Consuming Activities for the Energy-Intensive Manufacturing Subsectors

.................... 34 8. Selected Technology Characteristics for Automobiles

........................................ 38 9. Examples of Midsize Automobile Attributes

................................................ 38 10. Example of Truck Technology Characteristics (Diesel)

....................................... 41 11. Generating Technologies

.............................................................. 46 12. 2008 Overnight Capital lcosts (including Contingencies), 2008 Heat Rates, and Online Year by Technology for the AEO2009 Reference Case

............................................. 47 13. Coal Export Component

............................................................... 74

# Intro duc tionThe Na tional En ergy Mod el ing Sys tem (NEMS) is a com
-

puter-based, en ergy-econ omy mod el ing sys tem of U.S. through 2030 . NEMS pro jects the pro duc tion, im ports, con ver sion, con sump tion, and prices of en ergy, sub ject to as sump tions on mac ro eco nomic and finan cial fac tors, world en ergy mar kets, re source avail abil ity and costs, be hav ioral and tech no log i cal choice cri te ria, cost and per
- for mance char ac ter is tics of en ergy technologies, and de
- mo graph ics. NEMS was de signed and im ple mented by the En ergy In for ma tion Admin istration (EIA) of the U.S. De part ment of Energy (DOE)

. The Na tional En ergy Mod el ing Sys tem: An Over view 200 9 provides an over view of the struc ture and meth
- od ol ogy of NEMS and each of its com po nents. This chap ter pro vides a de scrip tion of the de sign and ob jec tives of the sys tem, fol lowed by a chap ter on the over all mod el
- ing struc ture and so lu tion al go rithm. The re main der of the re port sum ma rizes the meth o dology and scope of the com po nent mod ules of NEMS. The model de scrip
- tions are in tended for read ers fa mil iar with ter mi nol ogy from eco nomic, op er a tions re search, and en ergy mod el
- ing. More de tailed model doc u men ta tion re ports for all the NEMS mod ules are also avail able from EIA (Appe n dix, “Bibliography”). 

### Purpose of NEMS NEMS is used by EIA to pro ject the en ergy, eco nomic, en vi ron men tal, and se cu rity im pacts on the United States of al ter na tive en ergy pol i cies and dif fer ent as
- sump tions about en ergy mar kets. The pro jec tion ho ri zon is ap prox i mately 25 years into the fu ture. The pro jec tions in An nual En ergy Out look 2009 (AEO2009)are from the pres ent through 2030. This time pe riod is one in which tech nol ogy, de mo graph ics, and eco nomic con di tions are suf fi ciently un der stood in or der to rep re sent en ergy mar
- kets with a rea son able de gree of con fi dence. NEMS pro vides a con sis tent frame work for rep re sent ing the com plex in ter ac tions of the U.S. en ergy sys tem and its re sponse to a wide va ri ety of al ter na tive assumptions and pol i cies or pol icy ini tia tives. As an an nual model, NEMS can also be used to ex am ine the im pact of new en ergy pro grams and pol i cies. En ergy re sources and prices, the de mand for spe cific en - ergy ser vices, and other char ac ter is tics of en ergy mar - kets vary widely across the United States. To ad dress these differences, NEMS is a regional model. The regional disaggregation for each module reflects the availability of data, the regional format typically used to analyze trends in the specific area, geology, and other factors, as well as the regions determined to be the most useful for policy analysis. For exam ple, the demand modules (e.g., residential, commercial, industrial and transportation) use the nine Cen sus divisions, the Electricity Market Module uses 15 supply regions based on the North American Electric Reliability Council (NERC) regions, the Oil and Gas Supply Modules use 12 supply regions, including 3 offshore and 3 Alaskan regions , and the Pe tro leum Market Module uses 5regions based on the Petroleum Administration for Defense Districts. Base line pro jec tions are de vel oped with NEMS and pub lished an nu ally in the An nual En ergy Out look ( AEO ). In ac cor dance with the re quire ment that EIA re
- main pol icy-neu tral, the AEO projec tions are gen er ally based on Fed eral, State, and lo cal laws and reg u la tions in af fect at the time of the pro jec tion

. The po ten tial im pacts of pend ing or pro posed leg is la tion, reg u la tions, and stan
- dards or of sec tions of leg is la tion that have been en
- acted but that re quire im ple ment ing reg u la tions or ap pro pri a tions of funds that have not been pro vided or spec i fied in the leg is la tion it self are not re flected in NEMS. The first ver sion of NEMS, com pleted in De
- cem ber 1993, was used to de velop the pro jec tions pre - sented in the An nual En ergy Out look 1994

. This re port de scribes the ver sion of NEMS used for the AEO 2009

. 1 The pro jec tions p roduced by NEMS are not con sid ered to be state ments of what will hap pen but of what might hap pen, given the as sump tions and methodol ogies used. As sump tions in clude, for ex am ple, the es ti mated size of the eco nom i cally re cov er able re source base of fos sil fu
- els, and changes in world en ergy sup ply and de mand

. The pro jec tions are busi ness-as-usual trend es ti mates, given known tech no log i cal and de mo graphic trends

. 

### Analytical Capability NEMS can be used to an a lyze the ef fects of ex ist ing and pro posed gov ern ment laws and reg u la tions re lated to en ergy pro duc tion and use; the po ten tial im pact of new and ad vanced en ergy pro duc tion, con ver sion, and con
- sump tion tech nol o gies; the im pact and cost of green
- house gas con trol; the im pact of in creased use of re new able en ergy sources; and the po ten tial sav ings

Energy Information Administration / The National Energy Modeling System: An Overview 2009 1 

# Introduction

1 Energy Information Administration, Annual Energy Outlook 2009, DOE/EIA-0383(2009) (Washington, DC, March 2009)from in creased ef fi ciency of en ergy use; and the im pact of

reg u la tions on the use of al ter na tive or re for mu lated fuels

. In ad di tion to pro duc ing the anal y ses in the AEO , NEMS is used for one-time analytical re ports and pa pers, such as An Up dated An nual En ergy Out look 2009 Ref er ence Case Re flect ing Pro vi sions of the Amer i can Re cov ery and Re in vest ment Act and Re cent Changes in the Eco
- nomic Out look, 2 which up dates the AEO2009 ref er ence case to re flect the en act ment of the Amer i can Re cov ery and Re in vest ment Act in Feb ru ary 2009 and to adopt a re vised mac ro eco nomic out look for the U.S. and global econ o mies. The re vised AEO2009 ref er ence case will be used as the start ing point for pend ing and fu ture anal y ses of pro posed en ergy and en vi ron mental leg is la tion. Other an a lyt i cal pa pers, which ei ther de scribe the as sumptions and meth od ol ogy of the NEMS or look at cur
- rent en ergy mar kets is sues, are pre pared us ing the NEMS. Many of these pa pers are pub lished in the Is sues In Fo cus sec tion of the AEO . Past and cur rent anal y ses are avail
- able at http://www.eia.doe.gov/oiaf/aeo/otheranalysis/ aeo_analyes.html

. NEMS has also been used for a num ber of spe cial anal
- y ses at the re quest of the Ad min is tra tion, U.S. Con
- gress, other of fices of DOE and other gov ern ment agen cies, who spec ify the sce nar ios and as sumptions for the anal y sis. Some re cent ex am ples in clude:

• En ergy Mar ket and Eco nomic Im pacts of H.R. 2454, the Amer i can Clean En ergy and Se cu rity Act of 2009 , 3 re quested by Chair man Henry Waxman and Chair man Ed ward Markey to an a lyze the im
- pacts of H.R. 2454, the Amer i can Clean En ergy and Se cu rity Act of 2009 (ACESA), which was passed by the House of Rep re sen ta tives on June 26, 2009. ACESA is a com plex bill that reg u lates emis sions of green house gases through mar ket-based mech a nisms, ef fi ciency pro grams, and eco nomic in cen tives.

• Im pacts of a 25-Per cent Re new able Elec tric ity Stan dard as Pro posed in the Amer i can Clean En
- ergy and Se cu rity Act , 4 re quested by Sen a tor Markey to an a lyze the ef fects of a 25-per cent Fed
- eral re new able elec tric ity stan dard (RES) as in
- cluded in the dis cus sion draft of broader leg is la tion, the Amer i can Clean En ergy and Se cu rity Act

.

• Light-Duty Die sel Ve hi cles: Ef fi ciency and Emis
- sions At trib utes and Mar ket Is sues , 5 re quested by Sen a tor Ses sions toan a lyze the en vi ron men tal and en ergy ef fi ciency at trib utes of die sel-fu eled light-duty ve hi cles (LDV’s), in clud ing com par i son of the char ac ter is tics of the ve hi cles with those of sim i
- lar gas o line-fu eled, E85-fu eled, and hy brid ve hi
- cles, as well as a dis cus sion of any tech ni cal, eco nomic, reg u la tory, or other ob sta cles to in creas
- ing the use of die sel-fu eled ve hi cles in the United States

.

• The Im pact of In creased Use of Hy dro gen on Pe tro
- leum Con sump tion and Car bon Di ox ide Emis
- sions , 6 re quested by Sen a tor Dorgan to an a lyze the im pacts on U.S. en ergy im port de pend ence and emis sions re duc tions re sult ing from the com mer
- cial iza tion of ad vanced hy dro gen and fuel cell tech
- nol o gies in the trans por ta tion and dis trib uted gen er a tion mar kets.

• Anal y sis of Crude Oil Pro duc tion in the Arc tic Na
- tional Wild life Ref uge , 7 re quested by Sen a tor Stevens toac cess the im pact of Fed eral oil and nat u
- ral gas leas ing in the coastal plain of the Arc tic Na
- tional Wild life Ref uge in Alaska

.

• En ergy Mar ket and Eco nomic Im pacts of S.2191, the Lieberman-Warner Cli mate Se cu rity Act of

2 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Introduction

2 Energy Information Administration, An Updated Annual Energy Outlook 2009 Reference Case Reflecting Provisions of the American Recovery and Reinvestment Act and Recent Changes in the Economic Outlook , SR/OIAF/2009-4 (Washington, DC, April 2009). 3 Energy Information Administration, Energy Market and Economic Impacts of H.R. 2454, the American Clean energy and Security Act of 2009, SR/OIAF/2009-05 (Washington, DC, August 2009). 4 Energy Information Administration, Impacts of a 25-Percent Renewable Electricity Standard as proposed in the American Clean Energy and Security Act Discussion , SR/OIAF/2009-03 (Washington, DC, April 2009) 5 Energy Information Administration, Light-Duty Diesel Vehicles: Efficiency and Emissions Attributes and Market Issues , SR/OIAF/2009-02 (Washington, DC, February 2009). 6 Energy Information Administration, The Impact of Increased Use of Hydrogen on Petroleum Consumption and Carbon Light-Duty Diesel Vehicles: Efficiency and Emissions Attributes and Market Issues , SR/OIAF/2008-04 (Washington, DC, September 2008). 7 Energy Information Administration, Analysis of Crude Oil Production in the Arctic National Wildlife Refuge , SR/OIAF/2008-03 (Washington, DC, May 2008).2007 , 8 re quested by Sen a tors Lieberman, Warner,

Inhofe, Voinovich, and Barrasso toan a lyze the im
- pacts of the green house gas cap-and-trade pro gram that would be es tab lished un der Ti tle I of S.2191

.

• En ergy Mar ket and Eco nomic Im pact s of S.1766, the Low Car bon Econ omy Act of 2007 , 9 re quested by Sen a tors Bingaman and Spec ter toan a lyze the im
- pact of the man da tory green house gas al low ance pro gram un der S.1766 de signed to main tain cov ered emis sions at ap prox i mately 2006 lev els in 2020, 1990 lev els in 2030, and at least 60 per cent be low 1990 lev els by 2050. 

### Representations of Energy Market Interactions NEMS is de signed to rep re sent the im por tant interac tions of sup ply and de mand in U.S. en ergy mar kets. In the United States, en ergy mar kets are driven pri mar ily by the fun da men tal eco nomic inter ac tions of sup ply and de
- mand. Gov ern ment regula tions and pol i cies can ex ert con sid er able in flu ence, but the ma jor ity of de ci sions af
- fect ing fuel prices and con sump tion pat terns, re source al lo ca tion, and en ergy tech nol o gies are made by pri
- vate in di vid u als who value at trib utes other than life cy
- cle costs or com pa nies at tempt ing to op ti mize their own eco nomic in ter ests. NEMS rep re sents the mar ket be havior of the pro duc ers and con sum ers of en ergy at a level of de tail that is use ful for an a lyz ing the implica tions of tech no log i cal im prove ments and pol icy ini tiatives. Energy Supply/Conversion/Demand Interactions NEMS is a mod u lar sys tem. Four end-use de mand mod ules rep re sent fuel consump tion in the res i den tial, com mer cial, trans por ta tion, and in dus trial sec tors, sub
- ject to de liv ered fuel prices, mac ro eco nomic in flu
- ences, and tech nol ogy char ac ter is tics. The pri mary fuel sup ply and con ver sion mod ules com pute the lev els of do
- mes tic production, im ports, trans por ta tion costs, and fuel prices that are needed to meet do mes tic and ex port de mands for en ergy, sub ject to re source base char ac
- ter istics, in dus try in fra struc ture and tech nol ogy, and world mar ket con di tions. The mod ules in ter act to solve for the eco nomic sup ply and de mand bal ance for each fuel. Be cause of the mod u lar de sign, each sec tor can be rep re sented with the meth od ol ogy and the level of de tail, in clud ing re gional de tail, ap pro pri ate for that sec
-

tor. The mod u lar ity also fa cilitates the anal y sis, main te nance, and test ing of the NEMS com po nent mod
- ules in the multi-user en vironment.
Domestic Energy System/Economy Interactions The gen eral level of eco nomic ac tiv ity, rep re sented by gross do mes tic prod uct, has tra di tion ally been used as a key ex plan a tory vari able or driver for pro jections of en
- ergy con sump tion at the sec toral and re gional lev els. In turn, en ergy prices and other en ergy sys tem ac tiv i ties in
- flu ence eco nomic growth and ac tiv ity. NEMS cap tures this feed back be tween the do mes tic econ omy and the en ergy sys tem. Thus, changes in en ergy prices af fect the key mac ro eco nomic vari ables—such as gross do
- mes tic prod uct, dis pos able per sonal in come, in dus trial out put, hous ing starts, em ploy ment, and in ter est rates—that drive en ergy con sump tion and ca pac ity ex
- pan sion de ci sions. Domestic/World Energy Market Interactions World oil prices play a key role in do mes tic en ergy sup - ply and de mand de ci sion mak ing and oil price as sump - tions are a typ i cal start ing point for en ergy sys tem pro jec tions. The level of oil pro duc tion and con sump - tion in the U.S. en ergy sys tem also has a sig nif i cant in
- flu ence on world oil mar kets and prices. In NEMS, an in ter na tional mod ule repre sents the re sponse of world oil mar kets (sup ply and de mand) to as sumed world oil prices. The re sults/out puts of the mod ule are in ter na
- tional liq uids con sump tion and pro duc tion by re gion, and a crude oil sup ply curve rep re sent ing in ter na tional crude oil sim i lar in qual ity to West Texas In ter me di ate that is avail able to U.S. mar kets through the Pe tro leum Mar ket Mod ule (PMM) of NEMS. The sup ply-curve cal
- cu la tions are based on his tor i cal mar ket data and a world oil sup ply/de mand bal ance, which is de vel oped from re duced-form mod els of in ter na tional liq uids sup
- ply and de mand, cur rent in vest ment trends in ex plo ra
- tion and de vel op ment, and long-term re source eco nom ics for 221 coun tries/ter ri to ries. The oil pro duc
- tion es ti mates in clude both conventional and unconventional supply recovery technologies. 

# Introduction

Energy Information Administration / The National Energy Modeling System: An Overview 2009 3 8 Energy Information Administration, Energy Market and Economic Impacts of S.2191, the Lieberan-Warner Climate Security Act of 2007 , SR/OIAF/2008-01 (Washington, DC, April 2008). 9 Energy Information Administration, Energy Market and Economic Impacts of S.1766, the Low Carbon Economy Act of 2007 , SR/OIAF/2007-06 (Washington, DC, January 2008).Economic Decision Making Over Time

The pro duc tion and con sump tion of en ergy prod ucts to day are in flu enced by past in vest ment de ci sions to de velop en ergy re sources and ac quire en ergy-us ing cap i tal stock. Sim i larly, the pro duc tion and consumption of en ergy in a fu ture time pe riod will be in fluenced by de ci sions made to day and in the past. Cur rent in vest ment de ci sions de pend on expecta tions about fu ture mar kets. For ex am ple, ex pec ta tions of ris
- ing en ergy prices in the fu ture in crease the like li hood of cur rent de ci sions to in vest in more en ergy-ef fi cient tech
- nol o gies or al ter na tive en ergy sources. A va ri ety of as
- sump tions about plan ning ho rizons, the for ma tion of ex pec ta tions about the fu ture, and the role of those ex
- pec ta tions in eco nomic de ci sion mak ing are ap plied within the in di vid ual NEMS mod ules. 

### Technology Representation A key fea ture of NEMS is the rep re sen ta tion of tech nology and tech nol ogy im prove ment over time. Five of the sec tors—res i den tial, com mer cial, transportation, elec tric ity gen er a tion, and re fin ing—in clude ex ten sive treat ment of indivi dual tech nol o gies and their char ac ter
- is tics, such as the ini tial cap i tal cost, op er at ing cost, date of avail abil ity, ef fi ciency, and other char ac ter is tics spe
- cific to the par tic u lar tech nol ogy. For ex am ple, tech no
- log i cal prog ress in light ing tech nol o gies re sults in a grad ual re duc tion in cost and is mod eled as a func tion of time in these end-use sec tors. In ad di tion, the elec tric ity sec tor ac counts for tech no log i cal op ti mism in the cap i tal costs of first-of-a-kind gen er at ing technologies and for a de cline in cost as ex pe ri ence with the tech nol o gies is gained both do mes ti cally and in ternationally. In each of these sec tors, equip ment choices are made for in di vid
- ual tech nol o gies as new equip ment is needed to meet grow ing de mand for en ergy ser vices or to re place re tired equip ment. In the other sec tors—in dus trial, oil and gas sup ply, and coal sup ply—the treat ment of tech nol o gies is more lim
- ited due to a lack of data on in di vid ual tech nologies. In the in dus trial sec tor, only the com bined heat and power and mo tor tech nol o gies are ex plic itly con sid ered and char ac
- ter ized. Cost re duc tions re sulting from tech no log i cal prog ress in com bined heat and power tech nol o gies are rep re sented as a func tion of time as ex pe ri ence with the tech nol o gies grows. Tech no log i cal prog ress is not ex
- plic itly mod eled for the in dus trial mo tor tech nol o gies. Other technolo gies in the en ergy-in ten sive in dus tries are repre sented by tech nol ogy bun dles, with tech nol ogy possi bility curves rep re sent ing ef fi ciency im prove ment over time. In the oil and gas sup ply sec tor, technolog ical prog ress is rep re sented by econometrically es ti mated im prove ments in find ing rates, suc cess rates, and costs. Pro duc tiv ity im prove ments over time rep re sent tech no log i cal prog ress in coal production. 

### External Availability In ac cor dance with EIA re quire ments, NEMS is fully doc u
- mented and ar chived. EIA has been run ning NEMS on four EIA ter mi nal serv ers and sev eral dual-pro ces sor per sonal com put ers (PCs) us ing the Win dows XP op er
- at ing sys tem. The ar chive file pro vides the source lan
- guage, in put files, and out put files to rep li cate the An nual En ergy Out look re ference case runs on an iden
- ti cally equipped com puter; how ever, it does not in clude the pro pri etary por tions of the model, such as the IHS Global In sight, Inc. (for merly DRI-WEFA) mac ro eco
- nomic model and the op timization mod el ing li brar ies. NEMS can be run on a high-pow ered in di vid ual PC as long as the re quired pro pri etary soft ware re sides on the PC. Be cause of the com plex ity of NEMS, and the rel a
- tively high cost of the pro pri etary soft ware, NEMS is not widely used out side of the De part ment of En ergy. How
- ever, NEMS, or por tions of it, is in stalled at the Law rence Berke ley Na tional Lab o ra tory, Oak Ridge Na tional Lab o
- ra tory, the Elec tric Power Re search In sti tute, the Na
- tional En ergy Tech nol ogy Labora tory, the Na tional Re new able En ergy Lab o ra tory, sev eral pri vate con sult
- ing firms, and a few uni ver si ties.

4 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Introduction

# Over view of NEMSNEMS ex plic itly rep re sents do mes tic en ergy mar kets

by the eco nomic de ci sion mak ing in volved in the pro
- duc tion, con ver sion, and con sumption of en ergy prod
- ucts. Where pos si ble, NEMS in cludes ex plicit rep re sen ta tion of en ergy technolo gies and their char
- ac ter is tics. Since en ergy costs, avail abil ity, and en ergy-con sum ing char ac ter is tics vary widely across re gions, con sid er able re gional de tail is in cluded. Other de tails of pro duc tion and con sump tion are rep re sented to fa cil i tate pol icy anal y sis and en sure the va lid ity of the re sults. A sum mary of the de tail pro vided in NEMS is shown in Ta ble 1.

6 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Overview of NEMS

Energy Activity Categories Regions Res i den tial De mand Twenty four end-use ser vices Three hous ing types Fifty end-use tech nol o gies Nine Cen sus divisions

Com mer cial demand Ten end-use ser vices Eleven build ing types Eleven dis trib uted gen er a tion tech nol o gies Sixty-three end-use technologies Nine Cen sus divisions

In dus trial demand Seven en ergy-in ten sive in dus tries Eight non-en ergy-in ten sive in dus tries Six non-man u fac tur ing in dus tries Cogeneration Four Cen sus re gions, shared to nine Cen sus di vi sions
Trans por ta tion demand Six car sizes Six light truck sizes Sixty-three con ven tional fuel-sav ing tech nol o gies for light-duty ve hi cles Gas o line, die sel, and four teen al ter na tive-fuel ve hi cle tech nol o gies for light-duty ve hi cles Twenty vin tages for light-duty ve hi cles Re gional, nar row, and wide-body air craft Six ad vanced air craft tech nol o gies Light, me dium, and heavy freight trucks Thirty-seven ad vanced freight truck tech nol o gies Nine Cen sus divisions

Elec tric ity Eleven fos sil gen er a tion tech nol o gies Two dis trib uted gen er a tion tech nol o gies Eight re new able gen er a tion tech nol o gies Con ven tional and ad vanced nu clear Stor age tech nol ogy to model load shift ing Mar ginal and av er age cost pric ing Gen er a tion ca pac ity ex pan sion Seven en vi ron men tal con trol tech nol o gies Fif teen elec tric ity sup ply re gions (in clud ing Alaska and Ha waii) based on the North Amer i can Elec tric Re li abil ity Coun cil re gions and sub re gions Nine Cen sus di vi sions for de mand Fif teen elec tric ity sup ply re gions

Renewables Two wind tech nol o gies—on shore and off shore—, geo ther mal, so lar ther mal, so lar pho to vol taic, land fill gas, bio mass, con ven tional hydropower Oil supply Lower-48 on shore Lower-48 deep and shal low off shore Alaska on shore and off shore Six lower 48 on shore re gions Three lower 48 off shore re gions Three Alaska re gions Nat u ral gas sup ply Con ven tional lower-48 on shore Lower-48 deep and shal low off shore Coalbed meth ane Gas shales Tight sands Six lower 48 on shore re gions Three lower 48 off shore re gions Three Alaska regions
Nat u ral gas trans mis sion and distribution Core vs. noncore de liv ered prices Peak vs. off-peak flows and prices Pipe line ca pac ity ex pan sion Pipe line and dis trib u tor tar iffs Can ada, Mex ico, and LNG im ports and ex ports Alaska gas con sump tion and sup ply Twelve lower 48 re gions Ten pipe line bor der points Eight LNG im port re gions

Refining Five crude oil cat e go ries Four teen prod uct cat e go ries More than 40 dis tinct tech nol o gies Re fin ery ca pac ity ex pan sion Five re fin ery re gions based on the Pe tro leum Ad min is tra tion for De fense Dis tricts
Coal supply Three sul fur cat e go ries Four ther mal cat e go ries Un der ground and sur face min ing types Im ports and Ex ports Four teen sup ply re gions Four teen de mand re gions Sev en teen ex port re gions Twenty im port re gions Table 1. Characteristics of Selected ModulesMa jor As sump tions

Each mod ule of NEMS em bod ies many as sump tions and data to char ac ter ize the fu ture pro duc tion, con ver sion, or con sump tion of en ergy in the United States . Two of the more im por tant fac tors in flu enc ing en ergy mar kets are eco nomic growth and oil prices. The AEO2009

in cludes five pri mary fully-in te grated cases: a re ference case, high and low eco nomic growth case s , and high and low oil price case s
. The pri mary de ter mi nant for dif fer ent eco nomic growth rates are as - sump tions about growth in the la bor force and pro duc tiv
- ity, while the long-term oil price paths are based on ac cess to and cost of oil from the non-Or ga ni za tion of Pe tro leum Ex port ing Coun tries (OPEC), OPEC sup ply de ci sions, and the sup ply po ten tial of un con ven tional liq
- uids, as well as the de mand for liq uids

. In ad di tion to the five pri mary fully-in te grated cases, AEO2009

in cludes 34 other cases that ex plore the im pact of vary ing key as sump tions in the indi vidual com po nents of NEMS. Many of these cases in volve changes in the as
- sump tions that im pact the pen e tra tion of new or im
- proved tech nol o gies, which is a ma jor un cer tainty in for mu lat ing pro jec tions of fu ture en ergy mar kets. Some of these cases are run as fully in te grated cases (e.g., in te
- grated 200 9tech nol ogy case, in te grated high tech nol ogy case, low and high renewables tech nol ogy cost cases , slow and rapid oil and gas tech nol ogy cases, and low and high coal cost cases). Oth ers ex ploit the mod u lar struc
- ture of NEMS by run ning only a por tion of the en tire mod
- el ing sys tem in or der to fo cus on the first-or der im pacts of changes in the as sump tions (e.g., 2009, high, and best avail able tech nol ogy cases in the res i den tial and com mer cial sec tors, 2009 and high tech nol ogy cases in the in dus trial sec tor and , low and high tech nol ogy cases in the trans por ta tion sec tor). NEMS Modular Structure Over all, NEMS rep re sents the be hav ior of en ergy mar- kets and their in ter ac tions with the U.S. econ omy. The model achieves a sup ply/de mand bal ance in the end-use de mand re gions, de fined as the nine Cen sus di
- vi sions (Fig ure 1), by solv ing for the prices of each en ergy type that will bal ance the quantities pro duc ers are will ing to sup ply with the quan ti ties con sum ers wish to con sume. The sys tem re flects mar ket eco nom ics, in dus try struc
- ture, and ex ist ing en ergy pol i cies and reg u la tions that in
- flu ence mar ket be hav ior. NEMS con sists of four sup ply mod ules (oil and gas, nat
- u ral gas trans mis sion and dis tri bu tion, coal mar ket, and re new able fu els); two con ver sion mod ules (elec tric ity mar - ket and pe tro leum mar ket ); four end-use de mand mod
- ules (res i den tial de mand, com mer cial de mand , in dus trial de mand, and trans por ta tion de mand ); one mod ule to sim u late en ergy/econ omy in ter ac tions (mac ro
- eco nomic ac tiv ity); one mod ule to sim u late in ter na tional en ergy mar kets (in ter na tional en ergy); and one mod ule that pro vides the mech a nism to achieve a gen eral mar
- ket equi lib rium among all the other mod ules (in te grat ing mod ule). Fig ure 2 depicts the high-level structure of NEMS. Be cause en ergy mar kets are het er o ge neous, a sin gle meth od ol ogy does not ad e quately rep re sent all sup ply, con ver sion, and end-use de mand sec tors. The mod u
- lar ity of the NEMS de sign pro vides the flexi bility for each com po nent of the U.S. en ergy sys tem to use the meth od
- ol ogy and cov er age that is most ap propriate. Fur ther more, mod u lar ity pro vides the ca pability to ex e cute the mod ules in di vid u ally or in col lec tions of mod ules, which fa cil i tates the de velop ment and anal y sis of the sep a rate com po
- nent mod ules. The in ter ac tions among these mod ules are controlled by the in te grat ing mod ule. The NEMS global data struc ture is used to co or di nate and com mu ni cate the flow of in for ma tion among the mod ules. These data are passed through com mon in ter
- faces via the in te grat ing mod ule. The global data struc
- ture in cludes en ergy mar ket prices and con sump tion; mac ro eco nomic vari ables; en ergy pro duc tion, trans por
- ta tion, and con ver sion informa tion; and cen tral ized model con trol vari ables, param eters, and as sump tions. The global data struc ture ex cludes vari ables that are de fined lo cally within the mod ules and are not com mu ni cated to other mod ules. A key sub set of the vari ables in the global data struc ture is the end-use prices and quan ti ties of fu els that are used to equilibrate the NEMS en ergy bal ance in the con ver
- gence al go rithm. These de liv ered prices of en ergy and the quan ti ties de manded are defined by prod uct, re gion, and sec tor. The de liv ered prices of fuel en com pass all the ac tiv i ties nec es sary to pro duce, im port, and trans
- port fu els to the end user. The re gions used for the price and quan tity vari ables in the global data struc ture are the nine Cen sus di vi sions. The four Cen sus re gions (shown in Fig ure 1 by breaks be tween State groups) and nine Cen
- sus di vi sions are a com mon, main stream level of regionality widely used by EIA and other or ga ni za tions for data col lec tion and analysis.
Energy Information Administration / The National Energy Modeling System: An Overview 2009 7 

# Overview of NEMS8 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Overview of NEMS

Fig ure 1. Cen sus DivisionIntegrating Module

The NEMS integrating module controls the entire NEMS solution process as it iterates to determine a general market equilibrium across all the NEMS modules. It has the following functions:

• Man ages the NEMS global data struc ture

• Ex e cutes all or any of the user-se lected mod ules in an it er a tive con ver gence al go rithm

• Checks for con ver gence and re ports vari ables that re main out of con ver gence

• Im ple ments con ver gence re lax ation on se lected vari ables be tween it er a tions to ac cel er ate con ver
- gence

• Up dates ex pected val ues of the key NEMS vari
- ables. The in te grat ing mod ule ex e cutes the de mand, con ver
- sion, and sup ply mod ules iteratively un til it achieves an eco nomic equi lib rium of sup ply and de mand in all the con sum ing and pro duc ing sec tors. Each mod ule is called in se quence and solved, assuming that all other vari ables in the en ergy mar kets are fixed. The mod ules are called iteratively un til the end-use prices and quan ti ties re main constant

within a specified tolerance, a con di tion defined as convergence. Equilibration is achieved annually throughout the projection period, cur rently through 20 30 , for each of the nine Census divisions. In ad di tion, the mac ro eco nomic ac tiv ity and in ter na
- tional en ergy mod ules are ex e cuted iteratively to in cor
- po rate the feed back on the econ omy and in ter na tional en ergy mar kets from changes in the do mes tic en ergy mar kets

. Con ver gence tests check the sta bil ity of a set of key mac ro eco nomic and in ter na tional trade vari ables in re sponse to in ter ac tions with the do mes tic en ergy system. The NEMS al go rithm ex e cutes the sys tem of mod ules un til con ver gence is reached. The so lu tion pro cedure for one it er a tion in volves the ex e cu tion of all the com po nent mod ules, as well as the up dat ing of ex pec ta tion vari
- ables (re lated to fore sight assump tions) for use in the next it er a tion. The sys tem is exe cuted se quen tially for
Energy Information Administration / The National Energy Modeling System: An Overview 2009 9 

# Overview of NEMS

Oil and Gas Supply Module

Natural Gas Transmission and Distribution Module
Coal Market Module

Renewable Fuels Module Supply Residential Demand Module

Commercial Demand Module Transportation Demand Module

Industrial Demand Module Demand Electricity Market Module Petroleum Market Module Conversion Macroeconomic Activity Module International Energy Module



# Integrating Module Fig ure 2. Na tional En ergy Mod el ing Sys temeach year in the pro jec tion pe riod. Dur ing each it er a tion,

th e mod ules are ex e cuted in turn, with in ter ven ing con vergence checks that iso late spe cific mod ules that are not con verg ing. A con ver gence check is made for each price and quan tity vari able to see whether the per- cent age change in the vari able is within the as sumed tol er ance. To avoid un nec es sary it er a tions for changes in in sig nif i cant val ues, the quan tity conver gence check is omit ted for quan ti ties less than a user-spec i fied min i
- mum level. The or der of ex e cu tion of the mod ules may af
- fect the rate of con ver gence but will gen er ally not pre vent con ver gence to an equilib rium so lu tion or sig nif i cantly al ter the re sults. An op tional re lax ation rou tine can be ex e cuted to dampen swings in so lu tion val ues be
- tween itera tions. With this op tion, the cur rent it er a tion val ues are re set part way be tween so lu tion val ues from the cur rent and pre vi ous it er a tions. Because of the modular structure of NEMS and the it er a tive so lu tion al
- go rithm, any sin gle mod ule or sub set of mod ules can be ex e cuted in de pend ently. Mod ules not ex e cuted are by passed in the call ing se quence, and the val ues they would cal cu late and pro vide to the other mod ules are held fixed at the val ues in the global data struc ture, which are the so lu tion val ues from a pre vi ous run of NEMS. This flex i bil ity is an aid to in de pend ent de vel op ment, de bug
- ging, and anal y sis.

10 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Overview of NEMS

# Car bon Diox ide Emis sionsThe emis sions pol icy submodule, part of the in te grat ing

mod ule, es ti mates en ergy-re lated car bon di ox ide emis
- sions and is ca pa ble of rep re sent ing two re lated green
- house gas (GHG) emis sions pol i cies: a cap-and-trade pro gram and a car bon dioxide emission tax. Car bon di ox ide emis sions are cal cu lated from fos
- sil-fuel en ergy con sump tion and fuel-spe cific emis
- sions fac tors. The es ti mates are ad justed for car bon cap ture tech nol o gies where ap pli ca ble. Car bon di ox
- ide emis sions from en ergy use are de pend ent on the car bon con tent of the fos sil fuel, the frac tion of the fuel con sumed in com bus tion, and the con sump tion of that fuel. The prod uct of the car bon con tent at full com bus
- tion and the com bus tion frac tion yields an ad justed car
- bon emis sion fac tor. The ad justed car bon emis sions fac tors, one for each fuel and sec tor, are provided as input to the emissions policy module. Data on past car bon di ox ide emis sions and emis sions fac tors are up dated each year from the EIA’s an nual in
- ven tory, Emis sions of Green house Gases the United States

. 10 To pro vide a more com plete ac count ing of green house gas emis sions con sis tent with that in ven
- tory, a base line emis sions pro jec tion for the non-en ergy car bon di ox ide and other green house gases may be spec i fied as an exogenous input. To rep re sent car bon tax or cap-and-trade pol i cies, an in cre men tal cost of us ing each fos sil fuel, on a dol
- lar-per-Btu ba sis, is cal cu lated based the car bon di ox
- ide emis sions fac tors and the per-ton car bon di ox ide tax or cap-and-trade al low ance cost. This in cre men tal cost, or car bon price ad just ment, is added to the cor re
- spond ing en ergy prices as seen by the en ergy de mand mod ules. These price ad just ments in flu ence en ergy de mand and en ergy-re lated CO 2 emis sions, as well as macroeconomic trends. Un der a cap-and-trade pol icy, the al low ance or per mit price is de ter mined in an it er a tive so lu tion pro cess such that the an nual cov ered emis sions match the cap each year. If al low ance bank ing is per mit ted, a con
- stant-growth al low ance price path is found such that cu mu la tive emis sions over the bank ing in ter val match the cu mu la tive cov ered emis sions. To the ex tent the pol i cies cover green house gases other than CO 2 , the cov er age as sump tions and abate ment po ten tial for the gases must be pro vided as in put. In past stud ies, EIA has drawn on work by the En vi ron men tal Pro tec tion Agency (EPA) to rep re sent ex og e nous es ti mates of emis sions abate ment and the use of off sets as a func
- tion of al low ance prices. Rep re sent ing spe cific cap-and-trade pol i cies in NEMS al most al ways re quires cus tom iz ation of the model. Among the is sues that must be ad dressed are what gases and sec tors are cov ered, what off sets are el i gi
- ble as com pli ance mea sures, how the rev e nues raised by the taxes or al low ance sales are used, how al low
- ances or the value of al low ances are dis trib uted, and how the dis tri bu tion af fects en ergy pric ing or the cost of us ing en ergy.

12 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Carbon Dioxide and Methane Emissions

10 Energy Information Administration, Emissions of Greenhouse Gases in the United States 2007 , DOE/EIA-0573 (2007) (Washington, DC, December 2008), web site www.eia.doe.gov/oiaf/1605/ggrpt/index.html.

# Mac ro eco nomic Activity Mod uleThe Mac ro eco nomic Ac tiv ity Mod ule (MAM) links

NEMS to the rest of the econ omy by pro vid ing projec tions of eco nomic driver vari ables for use by the sup ply, de
- mand, and con ver sion mod ules of NEMS. The der i va tion of the base line mac ro eco nomic pro jec tion lays a foun
- da tion for the de ter mi na tion of the en ergy de mand and sup ply fore cast. MAM is used to pres ent al ter na tive mac ro
- eco nomic growth cases to pro vide a range of un cer tainty about the growth po ten tial for the econ omy and its likely con se quences for the en ergy sys tem. MAM is also able to ad dress the mac ro eco nomic im pacts as so ci ated with chang ing en ergy mar ket con di tions, such as al ter na tive world oil price as sump tions. Out side of the AE O set ting, MAM rep re sents a sys tem of linked mod ules which can as sess the po ten tial im pacts on the econ omy of changes in en ergy events or pol icy pro pos als. These eco nomic im pacts then feed back into NEMS for an in te
- grated so lu tion. MAM con sists of five submodules:

• Global In sight Model of the U.S. Econ omy

• Global In sight In dus try Model

• Global In sight Em ploy ment Model

• EIA Re gional Model

• EIA Com mer cial Floorspace Model The IHS Global In sight Model of the U.S. Econ omy (Mac roeconomic Model) is the same model used by IHS Global In sight, Inc. to gen er ate the eco nomic pro jec
- tions be hind the com pany’s monthly as sess ment of the U.S. econ omy. The In dus try and Em ploy ment submodules, are de riv a tives of IHS Global In sight’s In
- dus try and Em ploy ment Mod els, and have been tai lored to pro vide the in dus try and re gional de tail re quired by NEMS. The Re gional and Com mer cial Floorspace Submodules were de veloped by EIA to com ple ment the set of Global In sight mod els, pro vid ing a fully in te grated ap proach to pro ject ing eco nomic ac tiv ity at the na
- tional, in dus try and re gional lev els. The set of mod els is de signed to run in a re cur sive man ner (see Fig ure 3). Global In sight’s Mac ro eco nomic Model de ter mines the na tional econ omy’s growth path and fi nal de mand mix. The Global In sight Mac ro eco nomic Model pro vides pro
- jec tions of over 1300 con cepts span ning fi nal de mands, ag gre gate sup ply, prices, in comes, in ter na tional trade, in dus trial de tail, in ter est rates and fi nan cial flows. The In dus try Submodule takes the fi nal de mand projec tions from the Mac ro eco nomic Submodule as in
- puts to pro vide pro jec tions of out put and other key in
- dica tors for 61 sec tors, cov er ing the en tire econ omy. This is later ag gre gated to 41 sec tors to pro vide information to NEMS. The In dus try Submodule in sures that sup ply by in dus try is con sis tent with the fi nal de mands (con sump tion, in vest ment, gov ern ment spending, exports and imports) generated in the Macroeconomic Submodule. The Em ploy ment Submodule takes the in dus try out put pro jec tions from the In dus try Submodule and na tional wage rates, pro duc tiv ity trends and av er age work-week trends from the Mac ro eco nomic Submodule to pro ject em ploy ment for the 41 NEMS in dus tries. The sum of non-ag ri cul tural em ploy ment is con strained to sum to the na tional to tal pro jected by the Macroeconomic Submodule. The Re gional Submodule de ter mines the level of in dus try out put and em ploy ment, pop u la tion, in comes, and hous
- ing ac tiv ity in each of nine Cen sus re gions. The Com mer
- cial Floorspace Submodule cal cu lates re gional floorspace for 13 types of build ing use by Cen sus Di vi sion.

14 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Macroeconomic Activity Module

MAM Outputs Inputs from NEMS Exogenous Inputs Gross do mes tic prod uct Other eco nomic ac tiv ity mea sures, in clud ing hous ing starts, com mer cial floorspace growth, ve hi cle sales, pop u la tion Price in di ces and de fla tors Pro duc tion and em ploy ment for man u fac tur ing Pro duc tion and em ploy ment for nonmanufacturing In ter est rates Pe tro leum, nat u ral gas, coal, and elec tric ity prices Oil, nat u ral gas, and coal production Elec tric and gas in dus try out put Re fin ery out put End-use en ergy con sump tion by fuel Mac ro eco nomic vari ables de fin ing al ter na tive eco nomic growth casesIn te grated fore casts of NEMS cen ter around es ti mat ing

the state of the en ergy-econ omy sys tem un der a set of al ter na tive en ergy con di tions. Typ i cally, the pro jec tions fall into the fol low ing four types of in te grated NEMS sim u la tions:

• Base line Pro jec tion

• Al ter na tive World Oil Prices

• Pro posed En ergy Fees or Emis sions Per mits

• Pro posed Changes in Com bined Av er age Fuel Econ omy (CAFE) Stan dards In these in te grated NEMS sim u la tions, pro jec tion pe
- riod base line val ues for over 240 mac ro eco nomic and de mo graphic vari ables from MAM are passed to NEMS which solves for de mand, sup ply and prices of en ergy for the pro jec tion pe riod. These en ergy prices and quan ti ties are passed back to MAM and solved in the Mac ro eco nomic, In dus try, Em ploy ment, Re gional, and Com mer cial Floorspace Submodules in the EViews en
- vi ron ment. 11

Energy Information Administration / The National Energy Modeling System: An Overview 2009 15 

# Macroeconomic Activity Module

National Employment Variables

Regional Macroeconomic Industry Employment and Commercial Floorspace Variables National Interindustry Variables Oil, Natural Gas and Coal Production; Refinery Activity; Electric and Gas Industry Output Energy Prices and End-use

Consumption National Macroeconomic

Variables

National Macroeconomic Variables & Industrial Shipments Macroeconomic Submodule

Industry Submodule

Employment Submodule

Regional Submodule Macroeconomic Growth Cases Exogenous

Commercial Floorspace Submodule 

### Macroeconomic Activity Module



## NEMS Fig ure 3. Mac ro eco nomic Ac tiv ity Mod ule Structure

11 Eviews is a model build ing nad op er at ing soft ware pack age main tained by QMS (Quan ti ta tive Mi cro Soft ware.)

# Inter na tional Energy Mod uleThe In ter na tional En ergy Mod ule (IEM) (Fig ure 4) per
-

forms the fol low ing func tions:

• Cal cu lates the world oil price (WOP) that equilibrates world crude-like liq uids sup ply with de
- mand for each year. The WOP is de fined as the price of light, low sul fur crude oil de liv ered to Cush
- ing , Oklahoma.

• Pro vides the pro jected world crude-like liq uids sup
- ply curve (for each year) used by the Pe tro leum Mar ket Mod ule (PMM). These curves are ad justed to re flect ex pected con di tions in in ter na tional oil mar kets and pro jected changes in U.S. crude-like liq uids pro duc tion and con sump tion

.

• Pro vide an nual re gional (coun try) level pro duc tion de tail for con ven tional and un con ven tional liq uids based on ex og e nous as sump tions about ex pected coun try-level liq uid fu els pro duc tion and pro ducer be hav ior

.

• Pro jects crude oil and light and heavy re fined prod
- uct im port quan ti ties into the U.S. by year and by source based on ex og e nous as sump tions about fu
- ture ex plo ra tion, pro duc tion, re fin ing, and dis tri bu
- tion in vest ments world wide

. Scope of IEM Non-U.S. liq uid fu els mar kets are rep re sented in NEMS bythe in ter ac tion be tween the PMM and the IEM. Us
- ing the spe cific al go rithm de scribed in the doc u men ta
- tion of this mod ule, IEM cal cu lates the WOP that equilibrates world crude-like liq uids sup ply with de
- mand for each year. The IEM then es ti mates new world crude-like liq uids sup ply curves based on ex og e nous, ex pected U.S. and world crude-like liq uids sup ply and de mand curves and that in cor po rate any changes in U.S. crude-like liq uids pro duc tion or con sump tion pro
- jected by other NEMS mod ules. Op er a tion ally, IEM passes to PMM an ar ray of nine points of this sup ply curve, with the equi lib rium point be ing the fifth point of this ar ray. In put data into IEM con tain the his tor i cal per cent ages of im ports of oils, heavy and light prod ucts im ported into U.S. from dif fer ent re gions in the world. Us ing these val ues and to tal im ports into the U.S. of crudes, heavy and light prod ucts pro vided by PMM, IEM gen er ates a re port, with im ports by source for ev ery year in the pro jec tion. While the IEM is in tended to be ex e cuted as a mod ule of the NEMS sys tem, and uti liz ing its com plete ca pa bil i
- ties and fea tures re quires a NEMS in ter face, it is also pos si ble to ex e cute the IEM mod ule on a stand-alone ba sis. In stand-alone mode, the IEM cal cu lates the WOP based on an ex og e nously spec i fied pro jec tion of U.S. crude-like liq uids pro duc tion and con sump tion

. Sen si tiv ity anal y ses can be con ducted to ex am ine the re sponse of the world oil mar ket to changes in oil price, pro duc tion ca pac ity, and de mand. To sum ma rize, the model searches for the WOP that equilibrates crude-like liq uids sup ply and de mand at the world level. Based on the fi nal re sults for U.S. to tal liq uids pro duc
- tion and con sump tion, IEM also pro vides an In ter na
- tional Pe tro leum Sup ply and Dis po si tion Sum mary ta ble for world con ven tional and un con ven tional liq uids pro duc tion as well as for world liq uids de mand by re
- gion. Ex og e nous data used to build this re port is con
- tained in omsinput.wk1 file. Each sce nario has its own ver sion of this file. Be cause U.S. pro duc tion and con sump tion of con ven
- tional liq uids are dy namic val ues (out put from NEMS), all other world re gions have been pro por tion ally up
- dated such that the world liq uids pro duc tion and con
- sump tion re flect the cor re spond ing value as in the In ter na tional En ergy Out look ( IEO ). Relation to Other NEMS Components The IEM both uses in for ma tion from and pro vides in for
- ma tion to other NEMS com po nents. It pri mar ily uses in
- for ma tion about pro jected U.S and world crude-like liq uids pro duc tion and con sump tion and pe tro leum im
- ports and pro vides in for ma tion about the world liq uid fu
- els mar kets, in clud ing global crude-like liq uids sup ply curves and the sources of pe tro leum im ports into the U.S. It should be noted, how ever, that the pres ent fo cus of the IEM is on the in ter na tional oil mar ket where the

Energy Information Administration / The National Energy Modeling System: An Overview 2009 17 

# International Energy Module

IEM Outputs Inputs from NEMS Exogenous Inputs World crude-like liq uids sup ply curves Pro jected world liq uid fu els pro duc tion and con sump tion by re gion Sources of crude oil and pe tro leum prod uct im ports by year Con trol ling in for ma tion: it er a tion count, time ho ri zon, etc GDP de fla tor Pro jected U.S. and world crude-like liq uids pro duc tion and con sump tion U.S. crude oil and pe tro leum prod uct imports Ex pected US and world crude-like liq uids sup ply and de mand curves Ex pected world liq uid fuel pro duc tion and con sump tion by regionWOP is com puted. Any in ter ac tions be tween the U.S.

and for eign re gions in fu els other than oil (for ex am ple, coal trade) are mod eled in the par tic u lar NEMS mod ule that deals with that fuel. For U.S. crude-like liq uids pro duc tion and con sump tion in any year of the pro jec tion pe riod, the IEM uses pro
- jec tions gen er ated by the NEMS PMM (based on sup
- ply curves pro vided by the Oil and Gas Sup ply Mod ule (OGSM) and de mand curves from the end-use de mand mod ules). U.S. and world ex pected crude-like liq uids sup ply and de mand curves, for any year in the pro jec tion pe riod, are ex og e nously pro vided through data in cluded in in
- put file omsecon.txt, as de tailed in the doc u men ta tion of the IEM

. 

# International Energy Module

18 Energy Information Administration / The National Energy Modeling System: An Overview 2009 World Oil Price

Petroleum Market Module Macroeconomic Activity Module

N E M S Projected U. S.

crude-like liquids production and consumption by year

U. S. crude oil and petroleum product imports by year

World crude-like liquids supply curve by year Projected world liquid fuels production and consumption by region by year GDP Deflator

Projected world crude-like liquids production and consumption by year

Sources of crude oil and petroleum product imports by year Expected U. S. crude-like liquids supply and demand curves by year Exogenous

Expected world crude-like liquids supply and demand curves by year

Expected world liquid fuels production and consumption by region by year International Energy Module Fig ure 4. In ter na tional En ergy Mod ule Structure

# Res i den tial Demand ModuleThe res i den tial de mand mod ule (RDM) pro jects energy

con sump tion by Cen sus di vi sion for seven marketed en ergy sources plus so lar, wind, and geo ther mal energy. RDM is a struc tural model and its de mand pro
- jec tions are built up from pro jec tions of the res i den tial hous ing stock and en ergy-con sum ing equip ment. The com po nents of RDM and its interactions with the NEMS sys tem are shown in Figure 5. NEMS pro vides pro jec
- tions of res i den tial en ergy prices, pop u la tion, dis pos
- able in come, and hous ing starts, which are used by RDM to de velop pro jec tions of en ergy con sump tion by end–use ser vice, fuel type, and Census division. RDM in cor po rates the ef fects of four broadly-de fined de ter mi nants of en ergy con sump tion: eco nomic and de mo graphic ef fects, struc tural ef fects, tech nol ogy turn over and ad vance ment ef fects, and en ergy mar ket ef fects. Eco nomic and de mo graphic ef fects in clude the num ber, dwell ing type (sin gle-fam ily, mul ti fam ily or mo
- bile homes), oc cu pants per household, dis pos able in
- come, and lo ca tion of hous ing units.Struc tural ef fects in clude in creas ing av er age dwell ing size and changes in the mix of de sired end-use ser vices pro vided by en
- ergy (new end uses and/or in creas ing pen e tra tion of cur rent end uses, such as the in creas ing pop u lar ity of elec tronic equip ment and com put ers). Tech nol ogy ef
- fects in clude changes in the stock of in stalled equip
- ment caused by nor mal turn over of old, worn out equip ment with newer ver sions that tend to be more en
- ergy ef fi cient, the in te grated ef fects of equip ment and build ing shell (in su la tion level) in new con struc tion, and the pro jected avail abil ity of even more en ergy-ef fi cient equip ment in the fu ture. En ergy mar ket ef fects in clude the short-run ef fects of en ergy prices on en ergy de
- mands, the lon ger-run ef fects of en ergy prices on the ef fi ciency of pur chased equip ment and the ef fi ciency of build ing shells, and lim i ta tions on min i mum lev els of ef
- fi ciency im posed by leg is lated ef fi ciency stan dards. Hous ing Stock Submodule The base hous ing stock by Cen sus di vi sion and dwell
- ing type is de rived from EIA's 2005 Res i den tial En ergy Con sump tion Sur vey (RECS). Each el e ment of the of the base stock is re tired on the ba sis of a con stant rate of de cay for each dwellling type. RDM re ceives as an input from the macroeconomic activity module pro jec
- tions of housing additions by type and Census di vision. RDM supplements the surviving stocks from the previous year with the pro jected ad di tions by dwelling type and Census division. The average square footage of new construction is based on recent upward trends developed from the RECS and the Census Bureau’s Characteristics of New Housing. Appliance Stock Submodule The in stalled stock of ap pli ances is also taken from the 2005 RECS. The ef fi ciency of the ap pli ance stock is derived from his tor i cal ship ments by ef fi ciency level over a multi-year in ter val for the fol low ing equip ment: heat pumps, gas fur naces, cen tral air con di tion ers, room air con di tion ers, wa ter heat ers, re frig er a tors, freez ers, stoves, dish wash ers, clothes wash ers, and clothes dry ers. A lin ear re tire ment func tion with both min i mum and max i mum equip ment lives is used to re
- tire equip ment in sur viv ing hous ing units. For equip ment where ship ment data are avail able, the ef fi ciency of the re tir ing equip ment var ies over the pro jec tion. In early years, the re tir ing ef fi ciency tends to be lower as the older, less ef fi cient equip ment in the stock turns over first. Also, as hous ing units re tire, the as so ci ated appliances are re moved from the base ap pli ance stock as well. Ad di tions to the base stock are tracked sepa rately for housing units existing in 2005 and for cumulative new construction. As ap pli ances are re moved from the stock, they are re - placed by new ap pli ances with gen er ally higher ef ficiencies due to tech nol ogy im prove ments, equip ment stan dards, and mar ket forces. Ap pli ances added due to new con struc tion are ac cu mu lated and re - tired par al lel to ap pli ances in the ex ist ing stock. Ap pli
- ance stocks are main tained by fuel, end use, and tech nol ogy as shown in Ta ble 2. Technology Choice Submodule Fuel-spe cific equip ment choices are made for both new con struc tion and re place ment pur chases. For new con struc tion, ini tial heat ing sys tem shares (taken from the most re cently avail able Cen sus Bureau sur vey data cov er ing new con struc tion, cur rently 2005) are ad justed

20 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Residential Demand Module

RDM Outputs Inputs from NEMS Exogenous Inputs En ergy de mand by ser vice and fuel type Changes in hous ing and ap pli ance stocks Ap pli ance stock efficiency En ergy prod uct prices Hous ing starts Population Cur rent hous ing stocks and re tire ment rates Cur rent ap pli ance stocks and life ex pec tancy New ap pli ance types, efficiences, and costs Hous ing shell ret ro fit in di ces Unit en ergy con sump tion Square footageEnergy Information Administration / The National Energy Modeling System: An Overview 2009 21 

# Residential Demand Module

NEMS Macroeconomic

Activity Module

Petroleum Market Module Electricity Market Module Housing Starts, Population

Technology Choice Submodule

Fuel Consumption Submodule Housing Stock Submodule

Electricity Prices

Natural Gas Transmission and Distribution Module

Coal Market Module Electricity Demand

Natural Gas Prices
Natural Gas Demand

Petroleum Product Prices Petroleum Demand

Coal Prices Coal Demand Shell Integrity Submodule Stock of Structures by Type and Vintage

Appliance Stock Submodule

Building Shell Efficiencies Surviving Stock of Appliances

Average Efficiency of Appliance Stock Exogenous Base Year Housing Stock and Retirement Rates, Appliance Stocks and Life Expectancies, New Appliance Types, Efficiencies, and Costs, Housing Shell Retrofit Indices, Unit Energy Consumption, Square Footage

Distributed Generation Submodule 

### Residential Demand Module Fig ure 5. Res i den tial De mand Mod ule Struc turebased on rel a tive life cy cle costs for all com pet ing tech
-

nol ogy and fuel com bi na tions. Once new home heat ing sys tem shares are es tab lished, the fuel choices for other ser vices, such as wa ter heat ing and cook ing, are de ter mined based on the fuel cho sen for space heat
- ing. For re place ment pur chases, fuel switch ing is al
- lowed for an as sumed per cent age of all re place ments but is de pend ent on the es ti mated costs of fuel-switch
- ing (for ex am ple, switch ing from elec tric to gas heat ing is as sumed to in volve the costs of run ning a new gas line). For both re place ment equip ment and new construc tion, a “sec ond-stage” of the equip ment choice deci sion re
- quires se lect ing from sev eral avail able ef fi ciency lev
- els. The efficiency range of avail able equip ment rep re sents a “menu” of efficiency lev els and in stalled cost com bi na tions pro

jected to be avail able at the time the choice is be ing made. Costs and ef fi cien cies for se
- lected ap pli ances are shown in Table 3, de rived from the re port As sump tions to the An nual En ergy Out look 2009

. 12 At the low end of the ef fi ciency range are the min
- i mum lev els re quired by leg is lated stan dards. In any given year, higher ef fi ciency lev els are as so ci ated with higher in stalled costs. Thus, pur chas ing higher than the min i mum ef fi ciency in volves a trade-off be tween higher in stal la tion costs and future sav ings in en ergy ex pen di tures. In RDM, these trade-offs are cal i brated to re cent ship ment, cost, and ef fi ciency data. Changes in purchases by ef fi ciency level are based on changes in ei ther the in stalled cap i tal costs or changes in the first-year op er at ing costs across the avail able ef fi
- ciency lev els. As en ergy prices in crease, the incen tive of greater en ergy ex pen di tures sav ings will pro mote in
- creased pur chases of higher-ef fi ciency equip ment. In some cases, due to gov ern ment pro grams or gen eral pro
- jec tions of tech nol ogy im prove ment, in creases in ef fi ciency or de creases in the in stalled costs of higher-ef fi ciency equip ment will also pro mote purchases of higher-efficiency equipment. Shell Integrity Submodule Shell in teg rity is also tracked sep a rately for the ex isting hous ing stock and new con struc tion. Shell in tegrity for ex ist ing con struc tion is as sumed to re spond to in
- creases in real en ergy prices by be com ing more ef fi cient. There is no change in ex ist ing shell in teg rity when real en ergy prices de cline. New shell ef fi cien cies are based on the cost and per for mance of the heat ing and cool ing equip ment as well as the shell characteristics. Sev eral ef fi ciency lev els of shell char ac ter is tics are avail able through out the pro jec tion pe riod and can change over time based on changes in build ing codes. All shell ef fi
- cien cies are sub ject to a max i mum shell ef fi ciency based on stud ies of cur rently avail able res i den tial con struc tion methods. Distributed Generation Submodule Dis trib uted gen er a tion equip ment with ex plicit tech nology char ac ter iza tions is also mod eled for residen tial cus tom
- ers. Cur rently, three tech nol o gies are char ac ter ized, photovoltaics, wind, and fuel cells. The submodule in cor po rates his tor i cal es ti mates of photovoltaics (res i den tial-sized fuel cells are not ex pected to be com
- mer cial ized un til af ter 2005, the base year of the model) from its tech nol ogy char ac ter iza tion and ex og e nous pene tration in put file. Pro gram-based pho to vol taic

22 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Residential Demand Module

Space Heating Equipment : electric furnace, electric air-source heat pump, natural gas furnace, natural gas hydronic, kerosene furnace, liquefied petroleum gas, distillate furnace, distillate hydronic, wood stove, ground-source heat pump, natural gas heat pump. Space Cooling Equipment : room air conditioner, central air conditioner, electric air-source heat pump, ground-source heat pump, natural gas heat pump. Water Heaters : solar, natural gas, electric distiallate, liquefied petroleum gas. Refrigerators : 18 cubic foot top-mounted freezer, 25 cubic foot side-by-side with through-the-door features. Freezers : chest - manual defrost, upright - manual defrost. Lighting : incandescent, compact fluorescent, LED, halogen, linear fluoresent. Clothes Dryers : natural gas, electric. Cooking: natural gas, electric, liquefied petroleum gas. Dishwashers Clothes Washers Fuel Cells Solar Photovoltaic Wind Table 2. NEMS Res i den tial Mod ule Equip ment Sum mary

12 Energy Information Administration, Assumptions to the Annual Energy Outlook 2009, http://www.eia.doe.gov/oiaf/aeo/assumption/pdf/0554(2009).pdf (Washington, DC, March 2009).esti mates for the De part ment of En ergy’s Mil lion So lar

Roofs pro gram are also in put to the submodule from the exogenous penetration portion of the input file. Endogenous, economic purchases are based on a pen etration function driven by a cash flow model that simulates the costs and benefits of distributed gener ation purchases. The cash flow calculations are de veloped from NEMS projected energy prices coupled with the technology characterizations provided from the input file. Po ten tial eco nomic pur chases are mod eled by Cen
- sus di vi sion and tech nol ogy for all years subse quent to the base year. The cash flow model de vel ops a 30-year cost-ben e fit ho ri zon for each po ten tial in vest ment. It in
- cludes con sid er ations of an nual costs (down pay ments, loan pay ments, main te nance costs and, for fuel cells, gas costs) and an nual ben e fits (in terest tax de duc tions, any ap pli ca ble tax cred its, elec tric ity cost sav ings, and wa
- ter heat ing sav ings for fuel cells) over the en tire 30-year pe riod. Penetration for a po ten tial in vest ment in ei
- ther photovoltaics, wind, or fuel cells is a func tion of whether it achieves a cu mu la tive pos i tive dis counted cash flow, and if so, how many years it takes to achieve it. Once the cu mu la tive stock of dis trib uted equip ment is pro jected, re duced res i den tial pur chases of elec tricity are pro vided to NEMS. For fuel cells, in creased residential nat u ral gas con sump tion is also pro vided to NEMS based on the cal cu lated en ergy in put re quire ments of the fuel cells, par tially off set by nat u ral gas wa ter heat ing sav
- ings from the use of waste heat from the fuel cell. Energy Consumption Submodule The fuel con sump tion submodule mod i fies base year en - ergy con sump tion in ten si ties in each pro jec tion year. Base year en ergy con sump tion for each end use is de rived from en ergy in ten sity es ti mates from the 2005 RECS. The base year en ergy in ten si ties are mod i fied for the fol low ing ef fects: (1) in creases in ef ficiency, based on a com par i son of the ap pliance stock serv ing this end use rel a tive to the base year stock, (2) changes in shell in teg rity for space heat ing and cool ing end uses, (3) changes in real fuel prices—(short-run price elas tic ity ef fects), (4) changes in square foot age, (5) changes in the num ber of oc cu pants per house hold, (6) changes in dis pos able in come, (7) changes in weather rel a tive to the base year, (8) ad just
- ments in uti li za tion rates caused by ef fi ciency in creases (ef fi ciency “re bound” ef fects), and (9) re duc tions in pur
- chased elec tric ity and in creases in nat u ral gas con sump
- tion from dis trib uted gen er a tion. Once these mod i fi ca tions are made, to tal en ergy use is com puted across end uses and hous ing types and then summed by fuel for each Cen
- sus divi sion.

23 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Residential Demand Module

Equip ment Type Rel a tive Per for mance 1 2007

In stalled Cost ($2007) 2 Ef fi ciency 3 2020 In stalled Cost ($2007) 2 Ef fi ciency 3 Ap prox i mate Hur dle Rate Elec tric Heat Pump
Nat u ral Gas Furnace Min i mum Best Min i mum Best $3,800

$6,700 $1,900 $3,050 13.0

17.0 0.80 0.96 $3,800

$6,700 $1,900 $2,700 13.0

20.0 0.80 0.96 15%

15%
Room Air Con di tioner
Cen tral Air Conditioner Min i mum Best Min i mum Best $310

$925 $3,000 $5,700 9.8

11.7 13.0 21.0 $310

$875 $3,000 $5,750 9.8

12.0 13.0 23.0 140%

15% Re frig er a tor (23.9 cu bic ft in ad justed vol ume) Elec tric Wa ter Heater Min i mum Best Min i mum Best $550

$950 $400 $1,400 510

417 0.90 2.4 $550

$1000 $400 $1,700 510

417 0.90 2.4 19%

30% Table 3. Characteristics of Selected Equipment

1 Min i mum per for mance re fers to the low est ef fi ciency equip ment avail able. Best re fers to the high est ef fi ciency equip ment avail able. 2 In stalled costs are given in 2007 dol lars in the orig i nal source doc u ment. 3 Ef fi ciency mea sure ments vary by equip ment type. Elec tric heat pumps and cen tral air con di tion ers are rated for cool ing per for mance us ing the Sea sonal En ergy Ef fi - ciency Ra tio (SEER); nat u ral gas fur naces are based on An nual Fuel Uti li za tion Ef fi ciency; room air con di tion ers are based on En ergy Ef fi ciency Ra tio (EER); re frig er a - tors are based on ki lo watt-hours per year; and wa ter heat ers are based on En ergy Fac tor (de liv ered Btu di vided by in put Btu). Source: Navigant Con sult ing, EIA Tech nol ogy Fore cast Up dates-Res i den tial and Com mer cial Build ings Tech nol o gies , Sep tem ber 2007.

# Com mer cial Demand ModuleThe com mer cial de mand mod ule (CDM) pro jects

energy consumption by Census division for eight marketed energy sources plus solar, wind, and geothermal energy. For the three major commercial sector fuels, electricity, natural gas and distillate oil, CDM is a structural model and the pro jec tions are built up from the stock of commercial floorspace and energy-consuming equipment. For the remaining five marketed minor fuels, simple econometric projections are made. The com mer cial sec tor en com passes busi ness estab lishments that are not en gaged in in dus trial or trans por ta tion ac tiv i ties. Com mer cial sec tor en ergy is con sumed mainly in build ings, ex cept for a rela tively small amount for ser vices such as street lights and wa ter sup ply. CDM in cor po rates the ef fects of four broadly-de fined de ter mi nants of en ergy con sumption: eco nomic and de mo graph ics, struc tural, tech nol ogy turn over and change, and en ergy mar kets. De mo
- graphic ef fects in clude to tal floorspace, build ing type and lo ca tion. Struc tural ef fects in clude changes in the mix of de sired end-use ser vices pro vided by en ergy (such as the pen e tra tion of telecommunications equip ment, per sonal com put ers and other of fice equip ment). Tech
- nol ogy ef fects in clude changes in the stock of in stalled equip ment caused by the nor mal turn over of old, worn out equip ment to newer ver sions that tend to be more en
- ergy ef fi cient, the in te grated ef fects of equip ment and build ing shell (in su la tion level) in new con struc tion, and the pro jected avail abil ity of equip ment with even greater en ergy-ef fi ciency. En ergy mar ket ef fects in clude the short-run ef fects of en ergy prices on energy de mands, the lon ger-run ef fects of en ergy prices on the ef fi
- ciency of pur chased equip ment, and lim i ta tions on min i
- mum lev els of ef fi ciency im posed by leg is lated ef fi ciency stan dards. The model structure car ries out a se quence of five ba sic steps, as shown in Fig ure 6. The first step is to pro ject com mercial sec tor floorspace. The sec ond step is to pro ject the en ergy ser vices (space heat ing, light ing, etc.) re quired by the pro jected floorspace. The third step is to pro ject the elec tric ity gen er a tion and wa ter and space heat ing sup plied by dis trib uted gen era tion and com bined heat and power (CHP) technolo gies. The fourth step is to se lect spe cific tech nol o gies (nat u ral gas fur naces, flu o res cent lights, etc.) to meet the de mand for en ergy ser vices. The last step is to de ter mine how much en ergy will be con sumed by the equip ment cho sen to meet the de mand for en ergy ser vices. Floorspace Submodule The base stock of com mer cial floorspace by Cen sus di
- vi sion and build ing type is de rived from EIA’s 2003 Com mer cial Build ings En ergy Con sump tion Sur vey (CBECS). CDM re ceives pro jec tions of to tal floorspace by build ing type and Cen sus di vi sion from the macroeconomic ac tiv ity mod ule (MAM) based on IHS Global In sight, Inc. def i ni tions of the com mer cial sec tor. These pro jec tions em body both eco nomic and de mo
- graphic ef fects on com mer cial floorspace. Since the def i ni tion of com mer cial floorspace from IHS Global In
- sight, Inc. is not cal i brated to CBECS, CDM es ti mates the sur viv ing floorspace from the pre vi ous year and then cal i brates its new con struc tion so that growth in to tal floorspace matches that from MAM by build ing type and Cen sus division. CDM mod els com mer cial floorspace for the fol low ing 11 build ing types:

• As sem bly

• Ed u ca tion

• Food sales

• Food ser vice

• Health care

• Lodg ing

• Of fice-large

• Of fice-small

• Mer can tile and ser vice

• Ware house

• Other

Energy Information Administration / The National Energy Modeling System: An Overview 2009 25 

# Commercial Demand Module

CDM Outputs Inputs from NEMS Exogenous Inputs En ergy de mand by ser vice and fuel type Changes in floorspace and ap pli ance stocks En ergy prod uct prices In ter est rates Floorspace growth Ex ist ing com mer cial floorspace Floorspace sur vival rates Ap pli ance stocks and sur vival New ap pli ance types, ef fi cien cies, costs En ergy use intensities26 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Commercial Demand Module

NEMS Macroeconomic

Activity Module

Petroleum Market Module Electricity Market Module Floorspace Additions,

Interest Rates

Equipment Choice Submodule Floorspace Submodule

Electricity Prices

Natural Gas Transmission and Distribution Module

Coal Market Module Electricity Demand

Natural Gas Prices
Natural Gas Demand

Petroleum Product Prices Petroleum Demand

Coal Prices Coal Demand Energy Consumption Submodule Stock of Commercial Floorspace

Energy Service Demand Submodule

End-Use Service Demands

Stocks of Energy-Consuming Equipment Exogenous Existing Commercial Floorspace and Survival Rates, Appliance Stocks and Survival Rates, New Appliance Types, Efficiences, Costs, Energy Use Intensities

Distributed Generation/ Cogeneration Submodule 

### Commercial Demand Module Fig ure 6. Com mer cial De mand Mod ule StructureEnergy Service Demand Submodule

En ergy con sump tion is de rived from the de mand for en - ergy ser vices. So the next step is to pro ject en ergy ser vice de mands for the pro jected floorspace. CDM mod els ser vice de mands for the fol low ing ten end-use services:

• Heat ing

• Cool ing

• Ven ti la tion

• Wa ter heat ing

• Light ing

• Cook ing

• Re frig er a tion

• Of fice equip ment per sonal com puter

• Of fice equip ment other

• Other end uses. Dif fer ent build ing types re quire unique combina tions of en ergy ser vices. A hos pi tal must have more light than a ware house. An of fice build ing in the North east re quires more heat ing than one in the South. To tal ser vice de
- mand for any ser vice de pends on the floorspace, type, and lo ca tion of build ings. Base ser vice de mand by end use by build ing type and Cen sus di vi sion is de rived from es ti mates de vel oped from CBECS en ergy con sump tion data. Pro jected ser vice de mands are ad justed for trends in new con struc tion based on CBECS data con cern ing re
- cent construc tion. Distributed Generation and CHP Submodule Com mer cial con sum ers may de cide to pur chase equip ment to gen er ate elec tric ity (and per haps pro vide heat as well) rather than de pend on pur chased elec tric ity to ful fill all of their elec tric power re quire ments. The third step of the com mer cial mod ule struc ture is to pro ject elec
- tric ity gen er a tion, fuel con sump tion, wa ter heat ing, and space heat ing sup plied by eleven dis trib uted gen er a tion and CHP tech nol o gies. The tech nol o gies char ac ter ized in clude: pho to vol taic so lar sys tems, wind tur bines, nat u
- ral gas fuel cells, re cip ro cat ing en gines, tur bines and microturbines, die sel en gine, coal-fired CHP, and mu nic
- i pal solid waste, wood, and hy dro elec tric gen er a tors. Ex ist ing elec tric ity gen er a tion by CHP tech nol o gies is de
- rived from his tor i cal data con tained in the most re cent year’s ver sion of Form EIA-860, An nual Elec tric Gen
- er a tor Re port. The estimated units form the in stalled base of CHP equipment that is car ried for ward into fu
- ture years and sup ple mented with any ad di tions. Proven in stal la tions of so lar pho to vol taic sys tems , wind tur binesand fuel cells are also in cluded based on infor mation from the De part ments of En ergy and De fense. For years fol low ing the base year, an endoge nous pro jec tion of dis trib uted gen er a tion and CHP is de vel oped based on the eco nomic re turns pro
- jected for dis trib uted gen er a tion tech nol o gies. A de
- tailed dis counted cash-flow ap proach is used to es ti mate the in ter nal rate of re turn for an in vest ment . The cal cu la tions in clude the an nual costs (down pay ments, loan pay ments, main te nance costs, and fuel costs) and re turns (tax de duc tions, tax cred its, and en ergy cost sav
- ings) from the in vest ment cov er ing a 30-year pe riod from the time of the in vest ment de ci sion. Pen e tra tion of these tech nol o gies is a func tion of how quickly an in vest
- ment in a tech nology is es ti mated to re coup its flow of costs. In terms of NEMS pro jec tions, in vest ments in distrib uted gen er a tion re duce pur chases of elec tric ity. Fuel con sum ing tech nol o gies also gen er ate waste heat that is as sumed to be par tially cap tured and used to off
- set com mer cial wa ter heat ing and space heat ing en ergy use. Equip ment Choice Submodule Once ser vice de mands are pro jected, the next step is to de fine the type and ef fi ciency of equip ment that will be used to sat isfy the de mands. The bulk of equip ment re
- quired to meet ser vice de mand will carry over from the equip ment stock of the pre vi ous model year. How ever, equip ment must al ways be pur chased to sat isfy ser vice de mand for new construction. It must also be pur
- chased to re place equip ment that has ei ther worn out (re place ment equip ment) or reached the end of its eco
- nom i cally use ful life (ret rofit equip ment). For re quired equip ment re place ments, CDM uses a con stant de cay rate based on equip ment life. A tech nol ogy will be retro fit
- ted only if the com bined an nual op er at ing and main te
- nance costs plus an nu al ized cap i tal costs of a po ten tial tech nol ogy are lower than the an nual operating and maintenance costs of an existing technology. Equip ment choices are made based on a com par i son of an nu al ized cap i tal and op er at ing and mainte nance costs across all al low able equip ment for a par ticular end-use ser vice. In or der to add in er tia to the equip ment choices, only sub sets of the to tal menu of po ten tially avail able equip ment may be al lowed for de fined mar ket seg ments. For ex am ple, only 7 per cent of floorspace in large of fice build ings may con sider all avail able equip
- ment us ing any fuel or tech nology when mak ing space
Energy Information Administration / The National Energy Modeling System: An Overview 2009 27 

# Commercial Demand Moduleheat ing equip ment replace ment de ci sions. A sec ond

seg ment equal to 3 1 per cent of floorspace, must se lect from tech nol o gies us ing the same fuel as al ready in
- stalled. A third seg ment, the remaining 62 percent of floorspace, is constrained to consider only different efficiency levels of the same fuel and technology already installed. For light ing and refrigeration, all replacement choices are limited to the same tech nol ogy class, where technologies are broadly defined to encompass the prin
- ci pal competing tech nol o gies for a par tic u lar ap pli ca tion. For ex am ple, a com mer cial ice maker may re place an
- other ice maker, but may not re place a re frig er ated vend
- ing ma chine. When com put ing an nu al ized costs to de ter mine equip
- ment choices, com mer cial floorspace is seg mented by what are re ferred to as hur dle rates or im plicit dis count rates (to dis tin guish them from the gen er ally lower and more com mon no tion of fi nan cial dis count rates). Seven seg ments are used to sim u late con sumer be hav ior when pur chas ing com mer cial equip ment. The seg ments range from rates as low as the 10-year Trea sury bond rate to rates high enough to guarantee that only equipment with the lowest capital cost (and least efficiency) is chosen. As real energy prices increase (decrease) there is an in centive for all but the highest implicit discount rate segments to purchase increased (decreased) levels of efficiency. The equip ment choice submodule is de signed to choose among a dis crete set of tech nol o gies that are char ac ter ized by a menu which de fines avail abil ity, cap i
- tal costs, main te nance costs, ef fi cien cies, and equip
- ment life. Tech nol ogy char ac ter is tics for se lected space heat ing equip ment are shown Ta ble 4, de rived from the re port As sump tions to the An nual En ergy Out look 2009

. 13 This menu of equip ment in cludes tech
- no log i cal in no va tion, mar ket de vel op ments, and pol icy inter ventions. For the AEO2009 , the tech nol ogy types that are in cluded for seven of the ten ser vice de mand cat e go ries are listed in Ta ble 5. The re main ing three end-use ser vices (PC-re lated of
- fice equip ment, other of fice equip ment, and other end uses) are con sid ered mi nor ser vices and are pro jected us
- ing ex og e nous equip ment ef fi ciency and market pen e tra
- tion trends. Energy Consumption Submodule Once the re quired equip ment choices have been made, the to tal stock and ef fi ciency of equip ment for a par tic u lar end use are de ter mined. En ergy consumption by fuel can be cal cu lated from the amount of ser vice de mand sat is
- fied by each tech nol ogy and the cor re spond ing ef fi ciency of the tech nol ogy. At this stage, ad just ments to en ergy con sump tion are also made. These in clude ad just ments for changes in real energy prices (short-run price elas
- tic ity ef fects), ad justments in uti li za tion rates caused by ef fi ciency in creases (ef fi ciency re bound ef fects), and changes for weather rel a tive to the CBECS sur vey year. Once these mod i fi ca tions are made, to tal en ergy use is com puted across end uses and build ing types for the three ma jor fu els, for each Cen sus di vi sion. Com bining these pro jec tions with the ec ono met ric/trend pro jec tions for the five mi nor fu els yields to tal pro jected com mer cial en ergy con sump tion.

28 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Commercial Demand Module

13 Energy Information Administration, Assumptions to the Annual Energy Outlook 2009 , http://www.eia.doe.gov/oiaf/aeo/assumption/pdf/0554(2009).pdf (Washington, DC, March 2009)Energy Information Administration / The National Energy Modeling System: An Overview 2009 29 

# Commercial Demand Module

Equip ment Type Vin tage Ef fi ciency 2 Cap i tal Cost ($2007 per Mbtu/hour) 3 Main te nance Cost

($2007 per Mbtu/hour) 3 Ser vice Life (Years) Elec tric Roof top Heat Pump 2007- typ i cal 2007- high efficiency 3.2 3.4 $72.78

$96.67 $1.39

$1.39 15 15 2010 - typ i cal (stan dard) 2010 - high efficiency 3.3 3.4 $76.67

$96.67 $1.39

$1.39 15 15 2020 - typ i cal 2020 - high efficiency 3.3 3.4 $76.67

$96.67 $1.39

$1.39 15 15 Ground-Source Heat Pump 2007 - typ i cal 2007 - high efficiency 3.5 4.9 $140.00

$170.00 $16.80

$16.80 20 20 2010 - typ i cal 2010 - high efficiency 3.5 4.9 $140.00

$170.00 $16.80

$16.80 20 20 2020 - typ i cal 2020 - high efficiency 4.0 4.9 $140.00

$170.00 $16.80

$16.80 20 20 Elec tric Boiler Pack aged Electric Cur rent typ i cal Typical 0.98 0.96 $17.53

$16.87 $0.58

$3.95 21 18 Nat u ral Gas Fur nace Cur rent Stan dard 2007 - high efficiency 0.80 0.82 $9.35

$9.90 $0.97

$0.94 20 20 2020 - typ i cal 2020 - high efficiency 0.81 0.90 $9.23

$11.57 $0.96

$0.86 20 20 2030 - typ i cal 2030 - high efficiency 0.82 0.91 $9.12

$11.44 $0.94

$0.85 20 20 Nat u ral Gas Boiler Cur rent Stan dard 2007 - mid efficiency 0.80 0.85 $22.42

$25.57 $0.50

$0.47 25 25 2007 - high ef fi ciency 2020 - typical 0.96 0.82 $39.96

$21.84 $0.52

$0.49 25 25 Nat u ral Gas Heat Pump 2007 - ab sorp tion 2010 - absorption 1.4 1.4 $158.33

$158.33 $2.50

$2.50 15 15 2020 - ab sorp tion 1.4 $158.33 $2.50 15 Dis til late Oil Fur nace Cur rent Stan dard 0.81 $11.14 $0.96 20 2020 - typ i cal 0.81 $11.14 $0.96 20 Dis til late Oil Boiler Cur rent Stan dard 2007 - high efficiency 0.83 0.89 $17.63

$19.84 $0.15

$0.14 20 20 2020 - typ i cal 0.83 $17.63 $015 20 Table 4. Cap i tal Cost and Ef fi ciency Rat ings of Se lected Com mer cial Space Heat ing Equip ment 1

1 Equip ment listed is for the New Eng land Cen sus di vi sion, but is also rep re sen ta tive of the tech nol ogy data for the rest of the U.S. See the source ref er enced be low for the com plete set of tech nol ogy data.
. 2 Ef fi ciency mea sure ments vary by equip ment type. Elec tric roof top air-source heat pumps, ground source and nat u ral gas heat pumps are rated for heat ing per for mance us ing co ef fi cient of per for mance; nat u ral gas and dis til late fur naces are based on Ther mal Ef fi ciency; and boil ers are based on com bus tion ef fi ciency. 3 Cap i tal and main te nance costs are given in 2007 dol lars. Source: En ergy In for ma tion Ad min is tra tion, “EIA - Tech nol ogy Fore cast Up dates - Res i den tial and Com mer cial Build ing Tech nol o gies - Ref er - ence Case Sec ond Edi tion (Re vised)”, Navigant Con sult ing, Inc., Ref er ence Num ber 20070831.1, Sep tem ber 2007.30 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Commercial Demand Module

End-Use Service by Fuel Technology Types Electric Space Heating air-source heat pump, ground-source heat pump, boiler, packaged space heating Natural Gas Space Heating boiler, furnace, absorption heat pump Fuel Oil Space Heating boiler, furnace Electric Space Cooling air-source heat pump, ground-source heat pump, reciprocating chiller, centrifugal chiller, screw chiller, scroll chiller, rooftop air conditioner, residential style central air conditioner, window unit Natural Gas Space Cooling absorption chiller, engine-driven chiller, rooftop air conditioner, engine-driven heat pump, absorption heat pump Electric Water Heating electric resistance, heat pump water heater, solar water heater with electric back-up Natural Gas Water Heating natural gas water heater Fuel Oil Water Heating fuel oil water heater Ventilation constant air volume (CAV) system, variable air volume (VAV) system Electric Cooking range/oven/griddle, induction range/oven/griddle Natural Gas Cooking range/oven/griddle, power burner range/oven/griddle Incandescent Style Lighting incandescent, compact fluorescent, halogen, halogen-infrared, light emitting diode (LED) Four-foot Fluorescent Lighting magnetic ballast, electronic ballast-T8 electronic w/controls, electronic w/reflectors, electronic ballast-T5, electronic ballast-super T8, LED, Eight-foot Fluorescent Lighting magnetic ballast, electronic ballast, electronic-high output, LED High Intensity-Discharge Lighting metal halide, mercury vapor, high pressure sodium, electronic-T8 high output, electronic-T5 high output, LED Refrigeration supermarket compressor rack, suupermarket condenser, supermarket display case, walk-in cooler, walk-in freezer, reach-in refrigerator, reach-in freezer, ice machine, beverage merchandiser, refrigerated vending machine Table 5. Com mer cial End-Use Tech nol ogy Types

# Indus trial Demand Mod uleThe In dus trial De mand Mod ule (IDM) pro jects energy

con sump tion for fu els and feedstocks for fif teen man u - fac tur ing in dus tries and six nonmanufactur ing in dus
- tries, sub ject to de liv ered prices of en ergy and macroeconomic variables representing the value of shipments for each industry. The module includes electricity generated through Com bined Heat and Power (CHP) systems that is either used in the in dustrial sector or sold to the electricity grid. The IDM structure is shown in Figure 7. In dus trial en ergy de mand is pro jected as a combination of “bot tom up” char ac ter iza tions of the en ergy-us ing technology and “top down” econometric estimates of behavior. The influence of energy prices on industrial energy consumption is modeled in terms of the efficiency of use of existing capital, the efficiency of new capital acquisitions, and the mix of fuels utilized, given existing capital stocks. Energy conservation from technological change is represented over time by trend-based “technology possibility curves.” These curves represent the aggregate efficiency of all new technologies that are likely to penetrate the future markets as well as the aggregate improvement in efficiency of 2002 technology. IDM in cor po rates three ma jor in dus try cat e go ries: en
- ergy-in ten sive man u fac tur ing in dus tries, non- en - ergy-in ten sive man u fac tur ing in dus tries, and nonmanufacturing in dus tries (see Ta ble 6). The level and type of mod el ing and de tail is dif fer ent for each. Man u fac tur ing disaggregation is at the 3-digit North Amer i can In dus trial Clas si fi ca tion Sys tem (NAICS) level, with some fur ther disaggregation of large and en - ergy-in ten sive in dus tries. D etail ed in dus tries in clude food, pa per, chem i cals, glass, ce ment, steel, and alu minum. En ergy prod uct de mands are cal cu lated in
- de pend ently for each industry. Each in dus try is mod eled (where ap pro pri ate) as three in ter re lated com po nents: build ings (BLD), boil
- ers/steam/ cogeneration (BSC), and pro cess/as sem
- bly (PA) ac tiv i ties. Build ings are es ti mated to ac count for 4 per cent of en ergy con sump tion in manufactur ing in dus tries (in nonmanufacturing in dus tries, build ing en ergy con sump tion is not cur rently cal cu lated ). Con se quently, IDM uses a sim ple mod el ing ap proach for the BLD com po nent. En ergy con sump tion in in dus trial build ings is as sumed to grow at the same rate as the av er age growth rate of em ploy ment and out
- put in that in dus try. The BSC com po nent con sumes en ergy to meet the steam de mands from and pro vide in ter nally gen er ated elec tric ity to the other two com po
- nents. The boiler com po nent con sumes by-prod uct fu
- els and fos sil fu els to pro duce steam, which is passed to the PA and BLD com po nents.

32 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Industrial Demand Module

IDM Outputs Inputs from NEMS Exogenous Inputs En ergy de mand by ser vice and fuel type Elec tric ity sales to grid Cogeneration out put and fuel consumption En ergy prod uct prices Eco nomic out put by in dus try Re fin ery fuel con sump tion Lease and plant fuel con sump tion Cogeneration from re fin er ies and oil and gas pro duc tion Pro duc tion stages in en ergy-in ten sive in dus tries Tech nol ogy pos si bil ity curves Unit en ergy con sump tion of out puts Cap i tal stock re tire ment rates Energy-Intensive Manufacturing Nonmanufacturing Industries
Food and Kindred Products (NAICS 311) Agricultural Production - Crops (NAICS 111) Paper and Allied Products (NAICS 322) Other Agriculture including Livestock (NAICS 112-115) Bulk Chemicals (NAICS 325) Coal Mining (NAICS 2121) Glass and Glass Products (NAICS 3272) Oil and Gas Extraction (NAICS 211) Hydraulic Cement (NAICS 32731) Metal and Other Nonmetallic Mining (NAICS 2122-2123) Blast Furnaces and Basic Steel (NAICS 331111) Construction (NAICS 233-235)
Aluminum (NAICS 3313) Nonenergy-Intensive Manufacturing
Metals-Based Durables (NAICS 332-336) Other Manufacturing (all remaining manufacturing NAICS) NAICS = North American Industry Classification System Table 6. Eco nomic Subsectors Within the IDMIDM mod els “tra di tional” CHP based on steam de mand

from the BLD and the PA com po nents. The “non
- tra di
- tional” CHP units are rep re sented in the elec tric ity mar
- ket mod ule since these units are mainly grid-serv ing, elec tric ity-price-driven entities. CHP ca pac ity, gen er a tion, and fuel use are cal cu lated from ex og e nous data on ex ist ing and planned ca pac ity ad di tions and new ad di tions de ter mined from an en gi
- neer ing and eco nomic eval u a tion. Ex isting CHP ca pac
- ity and planned ad di tions are derived from Form EIA-860, “An nual Elec tric Generator Re port,” for merly Form EIA-867, “An nual Nonutility Power Pro ducer Re
- port.” Ex isting CHP ca pac ity is as sumed to re main in ser vice through out the pro jec tion or, equiv a lently, to be re fur bished or re placed with sim i lar units of equal capac ity. Cal cu la tion of un planned CHP ca pac ity ad di tions be
- gins in 200 9 . Mod el ing of un planned ca pac ity ad di tions is done in two parts: bio mass-fu eled and fos sil-fu eled. Bio mass CHP ca pac ity is as sumed to be added to the ex tent pos si ble as ad di tional bio mass waste prod ucts are pro duced, pri mar ily in the pulp and pa per in dus try. The amount of bio mass CHP ca pac ity added is equal to the quan tity of new bio mass avail able (in Btu), divided by the to tal heat rate from bio mass steam tur bine CHP.

Energy Information Administration / The National Energy Modeling System: An Overview 2009 33 

# Industrial Demand Module

Industrial Demand Module Unit Energy Consumption by Industry, Production Stage Information for Energy-Intensive Industries, Technology Possibility Curves, Stock Retirement Rates

Exogenous

Boilers/Steam/Cogeneration Component

Buildings Component

Process/Assembly Component Steam and Cogenerated Electricity


## N E M S Macroeconomic

Activity Module Electricity Market Module

Coal Market Module
Oil and Gas Supply Module Natural Gas Transmission and Distribution Module

Petroleum Market Module Economic Activity by Sector Electricity Prices Electricity Demand Electricity Sales to Grid Cogeneration Output and Fuel Consumption Coal Prices Coal Demand Cogeneration
Natural Gas Prices Natural Gas Demand Lease and Plant Fuel Consumption Petroleum Product Prices Refinery Fuel Consumption

Cogeneration Petroleum Demand Energy Byproducts Industrial Demand Module

Boilers/Steam/Cogeneration

Component

Buildings Component

Process/Assembly Component Steam and Cogenerated Electricity


## N E M S Macroeconomic

Activity Module Electricity Market Module

Coal Market Module
Oil and Gas Supply Module Natural Gas Transmission and Distribution Module

Petroleum Market Module Economic Activity by Sector Electricity Prices Electricity Demand Electricity Sales to Grid

CHP Output and Fuel Consumption Coal Prices Coal Demand

Natural Gas Prices Natural Gas Demand Lease and Plant Fuel Consumption Petroleum Product Prices Refinery Fuel Consumption

CHP Petroleum Demand Energy Byproducts

CHP Fig ure 7. In dus trial De mand Mod ule StructureIt is as sumed that the tech ni cal po ten tial for fos sil-fuel

source CHP is based pri mar ily on sup ply ing ther mal re
- quire ments. First, the model as sesses the amount of ca
- pac ity that could be added to gen er ate the in dus trial steam re quire ments not met by ex isting CHP . The sec
- ond step is an eco nomic eval u a tion of gas tur bine pro to
- types for each steam load seg ment. Fi nally, CHP ad di tions are pro jected based on a range of acceptable payback periods. The PA com po nent ac counts for the larg est share of di
- rect en ergy con sump tion for heat and power, 55 per- cent. For the seven most en ergy-in ten sive indus tries, pro cess steps or end uses are mod eled us ing en gineering con cepts. The pro duc tion pro cess is decom posed into the ma jor steps, and the en ergy re la tion ships among the steps are spec i fied. The en ergy in ten si ties of the pro cess steps or end uses vary over time, both for ex ist ing tech nol ogy and for tech nol
- o gies ex pected to be adopted in the fu ture. In IDM, this vari a tion is based on en gi neer ing judge ment and is re
- flected in the pa ram e ters of tech nol ogy pos si bil ity curves, which show the de clin ing en ergy in ten sity of ex ist ing and new cap i tal rel a tive to the 2002 stock. IDM uses “tech nol ogy bun dles” to char ac ter ize tech nological change in the en ergy-in ten sive in dus tries. These bun dles are de fined for each pro duc tion pro cess step for five of the in dus tries and for end use sin the re maining two en ergy-in ten sive in dus tries. The pro cess step in dus tries are pulp and pa per, glass, ce ment, steel, and alu mi num. The end-use in dus tries are food and bulk chem i cals (see Ta ble 7). Ma chine drive elec tric ity con sump tion in the food, bulk chem i cals, metal-based durables, and bal ance of man u
- fac tur ing sec tors is cal cu lated by a mo tor stock model. The be gin ning stock of mo tors is modified over the pro jec
- tion ho ri zon as mo tors are added to ac com mo date growth in ship ments for each sec tor, as mo tors are re
- tired and re placed, and as failed motors are re wound. When a new mo tor is added, ei ther to ac com mo date growth or as a re place ment, an eco nomic choice is made be tween pur chas ing a mo tor that meets the EPACT min i
- mum for ef fi ciency or a pre mium ef fi ciency mo tor. There are seven mo tor size groups in each of the four in dus
- tries. The EPACT ef fi ciency stan dards only ap ply to the five small est groups (up to 200 horse power). As the mo tor stock changes over the pro jec tion ho ri zon, the overall ef fi ciency of the mo tor pop u la tion changes as well. The Unit En ergy Con sump tion (UEC) is de fined as the en ergy use per ton of through put at a pro cess step or as en ergy use per dol lar of ship ments for the end
- use in dustries. The “Ex ist ing UEC” is the cur rent av er age in
- stalled in ten sity as of 2002 . The “New 2002 UEC” is the in ten sity as sumed to pre vail for a new installa tion in 2002

. Sim i larly, the “New 20 30 UEC” is the in ten sity ex pected to pre vail for a new in stal la tion in 20 30 . For in ter ven ing years, the in ten sity is interpo lated. The rate at which the av er age in ten sity de clines is de
- ter mined by the rate and tim ing of new ad di tions to ca pac
- ity. In IDM, the rate and tim ing of new addi tions are func tions of re tire ment rates and in dus try growth rates. IDM uses a vintaged cap i tal stock ac count ing frame work that mod els en ergy use in new ad di tions to the stock and in the ex ist ing stock. This cap i tal stock is rep re sented as the ag gre gate vin tage of all plants built within an in dus try and does not im ply the in clusion of spe cific tech nol o gies or cap i tal equip ment. The cap i tal stock is grouped into three vin tages: old, mid
- dle, and new. The old vin tage con sists of cap i tal in pro
- duc tion prior to 2002 , which is as sumed to retire at a fixed rate each year. Mid dle-vin tage cap i tal is that added af ter 2002 . New pro duc tion ca pac ity is built in the pro jec tion years when the capacity of the existing stock of capital in

34 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Industrial Demand Module

End Use Characterization Food : direct fuel, hot water/steam, refrigeration, and other energy uses. Bulk Chemicals : direct fuel, hot water/steam, electrotytic, and other energy uses. Process Step characterization Pulp and Paper : wood preparation, waste pulping, mechanical pulping, semi-chemical pulping, kraft pulping, bleaching, and paper making. Glass : batch preparation, melting/refining, and forming. Cement : dry process clinker, wet process clinker, and finish grinding. Steel : coke oven, open hearth steel making, basic oxygen furnace steel making, electric arc furnace steel making, ingot casting, continuous casting, hot rolling, and cold rolling. Aluminum : primary and secondary (scrap) aluminum smelting, semi-fabrication (e.g. sheet, wire, etc.). Table 7. Fuel-Con sum ing Ac tiv i ties for the En ergy-In ten sive Man u fac tur ing SubsectorsIDM cannot produce the output pro jected by the NEMS

regional submodule of the macroeco nomic activity module. Capital additions during the pro jec tion ho ri zon are retired in subsequent years at the same rate as the pre- 2002 capital stock. The en ergy-in ten sive and/or large en ergy-consum ing in dus tries are mod eled with a struc ture that ex plicitly de
- scribes the ma jor pro cess flows or “stages of pro duc tion” in the in dus try (some in dus tries have ma jor con sum ing uses). Tech nol ogy pen e tra tion at the level of ma jor pro ces ses in each in dus try is based on a tech nol ogy pen etration curve re la tion ship. A sec ond re la tion ship can pro vide ad di tional en ergy con ser va tion re sult ing from in creases in rel a tive en ergy prices. Ma jor pro cess choices (where ap pli ca ble) are de ter mined by in dustry pro duc tion, spe cific pro cess flows, and ex og e nous as sump tions. Re cy cling, waste prod ucts, and by prod uct con sump tion are mod eled us ing pa ram e ters based on off-line anal y sis and as sump tions about the man u fac tur ing pro cesses or tech nol o gies ap plied within in dus try. These anal y ses and as sump tions are mainly based upon en vi ron men
- tal reg u la tions such as gov ern ment re quire ments about the share of re cy cled pa per used in of fices. IDM also ac
- counts for trends within industry to ward the pro duc tion of more spe cial ized prod ucts such as spe cial ized steel which can be pro duced us ing scrap ma te rial ver sus raw iron ore

.

Energy Information Administration / The National Energy Modeling System: An Overview 2009 35 

# Industrial Demand Module

# Transportation Demand Mod uleThe trans por ta tion de mand mod ule (TRAN) pro jects

the consumption of transportation sector fuels by transportation mode, including the use of renewables and alternative fuels, subject to deliv ered prices of en
- ergy and macroeconomic vari ables, in clud ing dis pos
- able personal income, gross domestic product, level of imports and exports, industrial output, new car and light truck sales, and population. The structure of the module is shown in Figure 8. Pro jec tions of fu ture fuel prices in flu ence fuel ef fi ciency, ve hi cle-miles trav eled, and alterna tive-fuel ve hi cle (AFV) mar ket pen e tra tion for the cur rent fleet of ve hi
- cles. Al ter na tive-fuel ve hi cle shares are pro jected on the ba sis of a multinomial logit model, sub ject to State and Fed eral gov ern ment man dates for minimum AFV sales volumes. Fuel Economy Submodule This submodule pro jects new light-duty ve hi cle fuel econ - omy by 12 U.S. En vi ron men tal Pro tec tion Agency (EPA) ve hi cle size classes and 16 pro pul sion tech nol o
- gies (gas o line, die sel, and 14 AFV technolo gies) as a func tion of en ergy prices and in come-re lated vari
- ables. There are 61 fuel-sav ing tech nol o gies which vary in cost and mar ginal fuel sav ings by size class. Char ac ter is tics of a sam ple of these tech nol o gies are shown in Ta ble 8, a com plete list is pub lished in As
- sump tions to the An nual En ergy Out look 2009. 14 Tech
- nol o gies pen e trate the mar ket based on a costef fec tive ness al go rithm that com pares the tech nol ogy cost to the dis counted stream of fuel sav ings and the value of per

formance to the con sumer. In gen eral, higher fuel prices lead to higher fuel ef fi ciency es ti mates within each size class, a shift to a more fuel-ef fi cient size class mix, and an in crease in the rate at which al terna - tive-fuel ve hi cles en ter the mar ket place. Regional Sales Submodule Ve hi cle sales from the MAM are di vided into car and light truck sales. The re main der of the submodule is a sim ple ac count ing mech a nism that uses en dog e nous es ti mates of new car and light truck sales and the his
- tor i cal re gional ve hi cle sales ad justed for re gional pop u
- la tion trends to pro duce es ti mates of re gional sales, which are subsequently passed to the al ter na tive-fuel ve hi cle and the light-duty vehicle stock submodules. Alternative-Fuel Vehicle Submodule This submodule pro jects the sales shares of al ter na
- tive-fuel tech nol o gies as a func tion of technol ogy at trib
- utes, costs, and fuel prices. The alterna tive-fuel ve hi cles at trib utes are shown in Ta ble 9, de rived from As sump tions to the An nual En ergy Out look 2009

. Both con ven tional and new tech nol ogy ve hi cles are con sid ered. The al ter
- na tive-fuel ve hi cle submodule re ceives re gional new car and light truck sales by size class from the re gional sales submodule. The pro jec tion of ve hi cle sales by tech nol ogy uti lizes a nested multinomial logit (NMNL) model that pre dicts sales shares based on rel e vant ve hi cle and fuel at trib
- utes. The nest ing struc ture first pre dicts the prob a bil ity of fuel choice for multi-fuel vechicles within a tech nol
- ogy set. The sec ond level nest ing pre dicts pen e tra tion among sim i lar tech nol o gies within a tech nol ogy set (i.e. gas o line ver sus die sel hy brids). The third level choice de ter mines mar ket share among the the dif fer
- ent tech nol ogy sets. 15

Energy Information Administration / The National Energy Modeling System: An Overview 2009 37 

# Transportation Demand Module

TRAN Outputs Inputs from NEMS Exogenous Inputs Fuel de mand by mode Sales, stocks, and char ac ter is tics of ve hi cle types by size class Ve hi cle-miles trav eled Fuel econ omy by tech nol ogy type Al ter na tive-fuel ve hi cle sales by tech nol ogy type Light-duty com mer cial fleet ve hi cle char ac ter is tics En ergy prod uct prices Gross do mes tic prod uct Dis pos able per sonal in come In dus trial out put Ve hi cle sales In ter na tional trade Nat u ral gas pipe line Pop u la tion Ex ist ing ve hi cle stocks by vin tage and fuel econ omy Ve hi cle sur vival rates New ve hi cle technology char ac ter is tics Fuel avail abil ity Com mer cial avail abil ity Ve hi cle safety and emis sions reglations Ve hi cle miles-per-gal lon deg ra da tion rates

14 Energy Information Administration, Assumptions to the Annual Energy Outlook 2009 http://www.eia.doe.gov/oiaf/aeo/assumption/pdf/0554(2009) (Washington, DC, January 2009). 15 Greene, David L. and S.M. Chin, "Alternative Fuels and Vehicles (AFV) Model Changes," Center for Transportation Analysis, Oak Ridge National Laboratory, page 1, (Oak Ridge, TN, November 14, 2000).Energy Information Administration / The National Energy Modeling System: An Overview 2009 38 

# Transportation Demand Module

Fractional Fuel Efficiency Change First Year Introduced Fractional Horsepower Change Ma te rial Sub sti tu tion IV 0.099 2006 0 Drag Re duc tion IV 0.042 2000 0 5-Speed Au to matic 0.025 1995 0 CVT 0.052 1998 0 Au to mated Man ual Trans 0.073 2004 0 VVL-6 Clinder 0.033 2000 0.10 Camless Valve Ac tu a tion 6 Cylinder 0.058 2020 0.13 Elec tric Power Steering 0.015 2004 0 42V-Launch As sist and Regen 0.075 2005 -0.05 Table 8. Selected Technology Characteristics for Automobiles

Year Gasoline TDI Diesel Ethanol Flex LPG Bi-Fuel Electric Gasoline Hybrid Fuel Cell

Hydrogen Ve hi cle Price (thousand 2007 dol lars) 2006 28.0 29.8 28.7 33.3 31.1 78.6* 2030 29.8 30.7 30.2 35.0 31.0 54.2 Ve hi cle Miles per Gal lon 2006 29.5 39.8 29.9 29.6 42.7 53.3* 2030 37.8 48.2 38.1 37.7 51.0 54.9 Ve hi cle Range (miles) 2006 521 704 381 417 652 594* 2030 674 910 492 539 843 674 *First year of avail abil ity Ta ble 9. Ex am ples of Midsize Au to mo bile At trib utesThe technology sets include:

• Con ven tional fuel ca pa ble (gas o line, die sel, bi-fuel and flex-fuel),

• Hy brid (gas o line and die sel) and plug-in hy brid

• Ded i cated al ter na tive fuel (com pressed nat u ral gas (CNG), liquified pe tro leum gas (LPG), and ethanol),

• Fuel cell (gas o line, meth a nol, and hy dro gen),

• Elec tric bat tery pow ered (nickel-metal hy dride, lith ium) The ve hi cles at trib utes con sid ered in the choice algo rithm in clude: price, main te nance cost, bat tery re place ment cost, range, multi-fuel ca pa bil ity, home re fu el ing ca pa
- bil ity, fuel econ omy, ac cel er a tion and lug gage space. 

# Transportation Demand Module

39 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

### Transportation Demand Module

Freight Transport Submodule Miscellaneous Energy Use Submodule Aircraft Fleet Efficiency Submodule Commercial Light Truck Submodule Vehicle Miles Traveled Submodule

Fuel Demand Submodule Light-Duty Vehicle Commercial Fleet SubmoduleAlternativeFuel Vehicle Submodule Regional Sales Submodule Fuel Economy Submodule

Air Travel Demand Submodule 

### N E M S Gross Domestic Product Disposable Personal Income Industrial Output International Trade New Car and Light Truck Sales

Petroleum Demand
Natural Gas Prices Pipeline Fuel Consumption Natural Gas Demand Electricity Prices Electricity Demand Electricity Market Module Natural Gas Transportation and Distribution Module Petroleum Market Module Macroeconomic Activity Module

Exogenous Current and Projected Demographics, Existing Vehicle Stocks by Vintage and Fuel Efficiency, Vehicle Survival Rates, New Vehicle Technology Characteristics, Fuel Availability, Commercial Availability, Vehicle Safety and Emissions Regulations, Vehicle Miles-per-Gallon Degradation Rates

Petroleum Product Prices Population Fig ure 8. Trans por ta tion De mand Mod ule Structure

Alternative Fuel Vehicles
Ethanol flex-fueled Ethanol neat (85 percent ethanol) Compressed natural gas (CNG) CNG bi-fuel Liquefied petroleum gas (LPG) LPG bi-fuel Battery electric vehicle Plug-in hybrid with 10 mile all electric range Plug-in hybrid with 40 mile all electric range Gasoline hybrid Diesel Hybrid Fuel cell gasoline Fuel cell hydrogen Fuel cell methanolWith the ex cep tion of main te nance cost, bat tery re
-

place ment cost, and lug gage space, ve hi cle at trib utes are de ter mined en dog e nously. 16 The fuel at trib utes used in mar ket share es ti ma tion in clude avail abil ity and price. Ve hi cle at trib utes vary by six EPA size classes for cars and light trucks and fuel avail abil ity var ies by Cen sus di vi sion. The NMNL model co ef fi cients were de vel oped to re flect pur chase pref er ences for cars and light trucks sepa rately. Light-Duty Ve hi cle (LDV) Stock Submodule This submodule spec i fies the in ven tory of LDVs from year to year. Sur vival rates are ap plied to each vin tage, and new ve hi cle sales are in tro duced into the ve hi cle stock through an ac count ing framework. The fleet of ve hi cles and their fuel ef fi ciency char ac ter is tics are im por tant to the trans la tion of trans por ta tion ser vices de mand into fuel de mand. TRAN main tains a level of de tail that in cludes twenty vin tage clas si fi ca tions and six pas sen ger car and six light truck size classes cor re spond ing to EPA in te rior vol ume clas si fi ca tions for all ve hi cles less than 8,500 pounds,

as follows: Vehicle-Miles Traveled (VMT) Submodule This submodule pro jects travel de mand for automo biles and light trucks. VMT per ca pita es ti mates are based on the fuel cost of driv ing per mile and per ca pita dis pos able per sonal in come. To tal VMT is calcu lated by mul ti ply ing VMT by the number of li censed drivers. LDV Commercial Fleet Submodule This submodule gen er ates es ti mates of the stock of cars and trucks used in busi ness, gov ern ment, and util ity fleets. It also es ti mates travel de mand, fuel ef ficiency, and en ergy con sump tion for the fleet vehicles prior to their tran si tion to the pri vate sec tor at pre de ter mined vin tages. Commercial Light Truck Submodule The com mer cial light truck submodule es ti mates sales, stocks, fuel ef fi cien cies, travel, and fuel demand for all trucks greater than 8,500 pounds and less than 10,000 pounds gross ve hi cle weight rat ing. Air Travel Demand Submodule This submodule es ti mates the de mand for both pas senger and freight air travel. Pas sen ger travel is pro jected by do mes tic travel (within the U.S.), in ter na
- tional travel (be tween U.S. and Non U.S.), and Non U.S. travel. Ded i cated air freight travel is es ti mated for U.S. and Non U.S. de mand. In each of the mar ket seg ments, the de mand for air travel is es ti mated as a func tion of the cost of air travel (in clud ing fuel costs) and eco nomic growth (GDP, dis pos able in come, and merchandise exports). Air craft Fleet Ef fi ciency Submodule This submodule pro jects the to tal world-wide stock and the average fleet ef fi ciency of nar row body, wide body, and re gional jets re quired to meet the pro jected travel demand. The stock es ti ma tion is based on the growth of travel de mand and the flow of air craft into and out of the United States The over all fleet efficiency is de ter
- mined by the weighted av er age of the sur viv ing air craft ef fi ciency (in clud ing retro fits) and the ef fi cien cies of the newly ac quired air craft. Efficiency im prove ments of new air craft are determined by pro ject ing the mar ket pen e tra tion of ad vanced air craft tech nol o gies. 

# Transportation Demand Module

40 Energy Information Administration / The National Energy Modeling System: An Overview 2009 Light Duty Vehicle Size Classes
Cars: Mini-compact - less than 85 cubic feet Subcompact - between 85 and 99 cubic feet Compact - between 100 and 109 cubic feet Mid-size - between 110 and 119 cubic feet Large - 120 or more cubic feet Two-seater - designed to seat two adults Trucks: Small vans - gross vehicle weight rating (GVWR) less than 4,750 pounds Large vans - GVWR 4,750 to 8,500 pounds Small pickups - GVWR less than 4,750 pounds Large pickups - GVWR 4,750 to 8,500 pounds Small utility - GVWR less than 4,750 pounds Large utility

- GVWR 4,750 to 8,500 pounds

16 Energy and Environmental Analysis, Inc., Updates to the Fuel Economy Model (FEM) and Advanced Technology Vehicle (ATV:) Module of the National Energy Modeling System (NEMS) Transportation Model, prepared for the Energy Information Administration (EIA),Freight Trans port Submodule

This submodule trans lates NEMS es ti mates of in dustrial pro duc tion into ton-miles trav eled for rail and ships and into vehicle ve hi cle-miles trav eled for trucks, then into fuel de mand by mode of freight travel. The freight truck stock is sub di vided into me dium and heavy-duty trucks. VMT freight es timates by truck size class and tech nol ogy are based on match ing freight needs, as mea sured by the growth in in dus trial out put by NAICS code, to VMT lev els as so ci ated with truck stocks and new ve hi cles. Rail and shipping ton-miles trav eled are also es ti mated as a function of growth in in
- dus trial out put. Freight truck fuel ef fi ciency growth rates are tied to his tor i
- cal growth rates by size class and are also de pen dent on the max i mum pen e tra tion, in tro duc tion year, fuel trig ger price (based on cost-ef fec tive ness), and fuel econ omy im prove ment of ad vanced technol ogies, which in clude al ter na tive-fuel tech nol o gies. A sub set of the tech nol ogy char ac ter is tics are shown in Ta ble 10 . In the rail and ship
- ping modes, en ergy effi ciency es ti mates are struc tured to eval u ate the potential of both tech nol ogy trends and ef fi ciency im provements re lated to en ergy prices. Miscellaneous Energy Use Submodule This submodule pro jects the use of en ergy in mil i tary op er - a tions, mass tran sit ve hi cles, rec re ational boats, and lu bri
- cants, based on en dog e nous vari ables within NEMS (e.g., ve hi cle fuel ef fi cien cies) and exogenous vari ables (e.g., the mil i tary bud get). 

# Transportation Demand Module

Energy Information Administration / The National Energy Modeling System: An Overview 2009 41 Fuel Economy Improvement (percent) Maximum Penetration (percent) Introduction Year Capital Cost (2001 dollars) Medium Heavy Medium Heavy Medium Heavy Medium Heavy Aero Dy nam ics: bumper, un der side air bat tles, wheel well covers 3.6 2.3 50 40 2002 N/A N/A $1,500 Low roll ing resistence tires 2.3 2.7 50 66 2004 2005 $180 $550 Trans mis sion: lock-up, elec tronic con trols, re duced friction 1.8 1.8 100 100 2005 2005 $750 $1,000 Die sel En gine: hy brid elec tric powertrain 36.0 N/A 15 N/A 2010 N/A $6,000 N/A Re duce waste heat, ther mal mgmt N/A 9.0 N/A 35 N/A 2010 N/A $2,000 Weight re duc tion 4.5 9.0 20 30 2010 2005 $1,300 $2,000 Die sel Emis sion No xnon-ther mal plasma cat a lyst -1.5 -1.5 25 25 2007 2007 $1,000 $1,250 PM cat a lytic filter -2.5 -1.5 95 95 2008 2006 $1,000 $1,500 HC/CO: ox i da tion cat a lyst -0.5 -0.5 95 95 2002 2002 $150 $250 NO xadsorbers -3.0 -3.0 90 90 2007 2007 $1,500 $2,500 Table 10. Ex am ple of Truck Tech nol ogy Char ac ter is tics (Die sel)

# Elec tric ity Mar ket Mod uleThe elec tric ity mar ket mod ule (EMM) rep re sents the

generation, transmission, and pricing of electricity, subject to: delivered prices for coal, petroleum prod ucts, and natural gas; the cost of centralized gen
- eration from renewable fuels; macroeconomic variables for costs of capital and domestic investment; and electricity load shapes and demand. The submodules consist of capacity planning, fuel dispatching, finance and pricing, and load and de mand (Figure 9). In addition, nonutility supply and electricity trade are represented in the fuel dispatching and ca
- pac ity planning submodules. Nonutility generation from CHP and other facilities whose primary business is not electricity generation is represented in the demand and fuel supply modules. All other nonutility generation is represented in the EMM. The generation of electricity is accounted for in 15 supply regions (Figure 10), and fuel consumption is allocated to the 9 Census divisions. The EMM de ter mines air borne emis sions pro duced by the gen er a tion of elec tric ity. It rep re sents lim its for sul
- fur di ox ide and ni tro gen ox ides spec i fied in the Clean Air Act Amend ments of 1990 (CAAA90) and the Clean Air In ter state Rule. The AEO2009 also mod els State-level reg u la tions im ple ment ing mer cury stan
- dards. The EMM also has the abil ity to track and limit emis sions of car bon di ox ide, and the AEO2009 in - cludes the re gional car bon re stric tions of the Re gional Green house Gas Ini tia tive (RGGI). Op er at ing (dis patch) de ci sions are pro vided by the cost-min i miz ing mix of fuel and vari able op er at ing and main te nance (O&M) costs, sub ject to en vi ron men tal costs. Ca pac ity ex pan sion is de ter mined by the least-cost mix of all costs, in clud ing cap i tal, O&M, and fuel. Elec tric ity de mand is rep re sented by load curves, which vary by re gion and sea son. The so lu tion to the submodules of EMM is simultaneous in that, di rectly or in di rectly, the so lu tion for each submodule de pends on the so lu tion to ev ery other submodule. A so lu tion se
- quence through the submodules can be viewed as fol lows: • The elec tric ity load and de mand submodule pro
- cesses elec tric ity de mand to con struct load curves

• The elec tric ity ca pac ity plan ning submodule pro
- jects the con struc tion of new util ity and nonutility plants, the level of firm power trades, and the ad di tion of equip ment for en vi ron men tal com pli
- ance

• The elec tric ity fuel dis patch submodule dis
- patches the avail able gen er at ing units, both util ity and nonutility, al low ing sur plus ca pac ity in se lect re
- gions to be dis patched to meet an other re gions needs (econ omy trade)

• The elec tric ity fi nance and pric ing submodule cal cu
- lates to tal rev e nue re quire ments for each op er a tion and com putes av er age and mar ginal-cost based elec tric ity prices. Electricity Capacity Planning Submodule The elec tric ity ca pac ity plan ning (ECP) submodule de
- ter mines how best to meet ex pected growth in elec tric
- ity de mand, given avail able re sources, expected load shapes, ex pected de mands and fuel prices, en vi ron
- men tal con straints, and costs for util ity and nonutility tech nol o gies. When new ca pac ity is re quired to meet growth in elec tric ity de mand, the tech nol ogy cho sen is de ter mined by the tim ing of the de mand in crease, the ex pected uti li za tion of the new ca pac ity, the op er at ing ef fi
- cien cies, and the con struction and op er at ing costs of avail able technolo gies. The ex pected uti li za tion of the ca pac ity is im por tant in the de ci sion-mak ing pro cess. A tech nol ogy with rel a tively high cap i tal costs but com par a tively low op er at ing costs (pri mar ily fuel costs) may be the ap pro pri ate choice if the ca pac ity is ex pected to op er ate con tin u
- ously (base load). How ever, a plant type with high op er
- at ing costs but low cap i tal costs may be the most eco nom i cal se lec tion to serve the peak load (i.e., the high est de mands on the sys tem), which oc curs in fre
- quently. In ter me di ate or cy cling load oc cu pies a mid dle ground be tween base and peak load and is best served

Energy Information Administration / The National Energy Modeling System: An Overview 2009 43 

# Electricity Market Module

EMM Outputs Inputs from NEMS Exogenous Inputs Elec tric ity prices and price com po nents Fuel de mands Ca pac ity ad di tions Cap i tal re quire ments Emis sions Re new able ca pac ity Avoided costs Elec tric ity sales Fuel prices Cogeneration sup ply and fuel con sump tion Elec tric ity sales to the grid Re new able tech nol ogy char ac ter is tics, al low able ca pac ity, and costs Re new able ca pac ity fac tors Gross do mes tic prod uct In ter est rates Fi nan cial data Tax assumptions Cap i tal costs Op er a tion and main te nance costs Op er at ing pa ram e ters Emmissions rates New tech nol o gies Ex ist ing fa cil i ties Trans mis sion constraintsby plants that are cheaper to build than baseload plants

and cheaper to op er ate than peak load plants. Tech nol o gies are com pared on the ba sis of to tal capi tal and op er at ing costs in curred over a 20-year pe riod. As new tech nol o gies be come avail able, they are com peted against con ven tional plant types. Fos sil-fuel, nu clear, and re new able cen tral-sta tion gen erating tech nol o gies are rep re sented, as listed in Ta ble 11. The EMM also con sid ers two dis trib uted gen er a tion tech nol o gies -baseload and peak. The EMM also has the abil ity to model a de mand stor age tech nol ogy to rep re sent load shift ing. Un cer tainty about in vest ment costs for new technol ogies is cap tured in ECP us ing tech no log i cal opti mism and learn ing fac tors. The tech no log i cal opti mism fac tor re
- flects the in her ent ten dency to un deres ti mate costs for new tech nol o gies. The de gree of tech no log i cal op ti mism de pends on the com plex ity of the en gi neer ing de sign and the stage of de velop ment. As de vel op ment pro
- ceeds and more data be come avail able, cost es ti mates be come more ac cu rate and the tech no log i cal op ti mism fac tor de clines. Learn ing fac tors rep re sent re duc tions in cap i tal costs due to learn ing-by-do ing. For new technolo gies, cost re
- duc tions due to learn ing also ac count for in ter na tional ex
- pe ri ence in build ing gen er at ing ca pacity. These fac tors

44 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Electricity Market Module

Electricity Market Module

Electricity Capacity Planning Submodule

Electricity Fuel Dispatch Submodule

Electricity Finance and Pricing Submodule

Load and Demand-Side Management Submodule Available Capacity

Fuel Demands

Average Electricity Prices

Load Curves Capacity Additions Electricity Sales Cogeneration Supply and Fuel Consumption Sales to Grid Electricity Prices

Natural Gas Peak and Offpeak, Core and Noncore

Demand Petroleum Product Prices Petroleum Demand Electricity Price Electricity Price Coal Prices Coal Demand

Renewable Capacity, Avoided Costs, Discount Rate, Biomass

Consumption
Electricity Prices Electric Industry Output Macroeconomic Activity Module Renewable Fuels Module Coal Market Module Oil and Gas Supply Module Petroleum Market Module Natural Gas Transmission and Distribution Module Demand Modules Exogenous Financial Data, Tax Assumptions, Capital Costs, Operating and Maintenance Costs, Operating Parameters, Emission Rates, Existing Facilities, New Technologies, Transmission Constraints, Hydropower Capacity and Capacity Factors

Renewable Technology Characteristics, Allowable Capacity, Capacity Factors, Costs Expectations

Interest Rates, Gross Domestic Product Natural Gas Prices Fig ure 9. Elec tric ity Mar ket Mod ule Strucutureare cal cu lated for each of the ma jor de sign com po nents

of a plant type de sign. For mod el ing pur poses, com po
- nents are iden ti fied only if the com po nent is shared be
- tween mul ti ple plant types, so that the ECP can re flect the learn ing that oc curs across tech nol o gies. The cost ad just ment fac tors are based on the cu mu la tive ca pac
- ity of a given com po nent. A 3-step learn ing curve is uti
- lized for all de sign com po nents. Typ i cally, the great est amount of learn ing oc curs dur ing the ini tial stages of de vel op ment and the rate of cost re
- duc tions de clines as com mer cial iza tion pro gresses. Each step of the curve is char ac ter ized by the learn ing rate and the num ber of doublings of ca pac ity in which this rate is ap plied. De pend ing on the stage of de vel op
- ment for a par tic u lar com po nent, some of the learn ing may al ready be in cor po rated in the ini tial cost es ti mate. Cap i tal costs for all new elec tric ity gen er at ing tech nol o
- gies (fos sil, nu clear, and re new able) de crease in re - sponse to for eign and do mes tic ex pe ri ence. Foreign units of new tech nol o gies are as sumed to con trib ute to re duc tions in cap i tal costs for units that are in stalled in the United States to the ex tent that (1) the tech nol ogy char ac ter is tics are sim i lar to those used in U.S. mar kets, (2) the de sign and con struc tion firms and key per son nel com pete in the U.S. mar ket, (3) the own ing and op er at ing firm com petes ac tively in the United States, and (4) there ex ists rel a tively com plete in for ma tion about the sta tus of the associ ated fa cil ity. If the new for eign units do not sat isfy one or more of these re quire ments, they are given a re duced weight or not in cluded in the learn ing ef fects cal cu la tion. Cap i tal costs, heat rates, and first year of availablilty from the AEO2009 ref er ence case are shown in Ta ble 12; cap i tal costs rep re sent the costs of building

Energy Information Administration / The National Energy Modeling System: An Overview 2009 45 

# Electricity Market Module

13 11

12 5

2 10

8 9 4 1 3 6 7
11

1 4



### 1 

### 5 1 ECAR 2 ERCOT 3 MAAC 4MAIN 5 MAPP 6 NY 7 NE 8 FL 9 STV

12 RA 10 SPP 11 NWP
13 CNV 14 15 AK HI Electricity Supply Regions Fig ure 10. Elec tric ity Mar ket Mod ule Sup ply Regionsnew plants or dered in 2008. Ad di tional in for ma tion

about costs and per for mance char ac ter is tics can be found on page 89 of the "As sump tions to the An nual En
- ergy Out look 2009." 17 Ini tially, in vest ment de ci sions are de ter mined in ECP us ing cost and per for mance char ac ter is tics that are rep re sented as sin gle point es ti mates corre sponding to the av er age (ex pected) cost. How ever, these pa ram e
- ters are also sub ject to un cer tainty and are better rep re
- sented by dis tri bu tions. If the distributions of two or more op tions over lap, the op tion with the low est av er
- age cost is not likely to cap ture the en tire mar ket. There fore, ECP uses a mar ket-shar ing al go rithm to ad just the ini tial solu tion and re al lo cate some of the ca
- pac ity ex pan sion decisions to technologies that are competitive but do not have the lowest average cost. Fos sil-fired steam and nu clear plant re tire ments are cal cu lated en dog e nously within the model. Plants are re tired if the mar ket price of elec tric ity is not suf fi cient to sup port con tin ued op er a tion. The ex pected rev e nues from these plants are com pared to the an nual go
- ing-for ward costs, which are mainly fuel and O&M costs. A plant is re tired if these costs ex ceed the rev e nues and the over all cost of elec tric ity can be re duced by building replacement capacity. The ECP submodule also de ter mines whether to con
- tract for un planned firm power im ports from Can ada and from neigh bor ing elec tric ity sup ply re gions. Im ports from Can ada are com peted us ing sup ply curves de vel
- oped from cost es ti mates for po tential hy dro elec tric pro
- jects in Can ada . Im ports from neigh bor ing elec tric ity sup ply re gions are competed in the ECP based on the cost of the unit in the ex port ing re gion plus the ad di tional cost of trans mit ting the power. Trans mis sion costs are com puted as a fraction of revenue. Af ter build ing new ca pac ity, the submodule passes to tal avail able ca pac ity to the elec tric ity fuel dis patch submodule and new ca pac ity ex penses to the elec tric ity fi nance and pric ing submodule. Elec tric ity Fuel Dis patch Submodule Given avail able ca pac ity, firm pur chased-power agree ments, fuel prices, and load curves, the elec tric ity fuel dis patch (EFD) submodule min i mizes vari able costs as it solves for gen er a tion fa cil ity utiliza tion and econ omy power ex changes to sat isfy de mand in each time pe riod and re gion. Lim its on emis sions of sul fur di
- ox ide from gen er at ing units and the en gi neer ing char ac
- ter is tics of units serve as con straints. Coal-fired ca pac ity can co-fire with biomass in or der to lower op er at ing costs and/or emissions. The EFD uses a lin ear pro gram ming (LP) ap proach to pro vide a min i mum cost so lu tion to al lo cat ing (dis patch
- ing) ca pac ity to meet de mand. It sim u lates the elec tric trans mis sion net work on the NERC re gion level and si
- mul ta neously dis patches ca pac ity re gion ally by time slice un til de mand for the year is met. Tra di tional cogeneration and firm trade ca pac ity is re moved from the load du ra tion curve prior to the dis patch de ci sion. Ca pac ity costs for each time slice are based on fuel and vari able O&M costs, mak ing ad just ments for RPS

46 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Electricity Market Module

Fossil Existing coal steam plants (with or without environmental controls) New pulverized coal with environmental controls Advanced clean coal technology Advanced clean coal technology with sequestration Oil/Gas steam Conventional combined cycle Advanced combined cycle Advanced combined cycle with sequestration Conventional combusion turbine Fuel cells Nuclear
Conventional nuclear Advanced nuclear Renewables Conventional hydropower Pumped storage Geothermal Solar-thermal Solar-photovoltaic Wind - onshore and offshore Wood Municipal solid waste En vi ron men tal con trols in clude flue gas desulfurization (FGD), se lec tive cat - a lytic re duc tion (SCR), se lec tive non-cat a lytic re duc tion (SNCR), fab ric fil - ters, spray cool ing, activated car bon in jec tion (ACI), and par tic u late re moval equipiment. Ta ble 11. Gen er at ing Technologies

17 Energy Information Administration, Assumptions to the Annual Energy Outlook 2009 , http://www.eia.doe.gov/oiaf/aeo/assumption/pdf/0554(2009).pdf (March 2009)cred its, if ap pli ca ble, and pro duc tion tax cred its. Gen er
-

a tors are re quired to meet planned main te nance re
- quire ments, as defined by plant type. In ter re gional econ omy trade is also rep re sented in the EFD submodule by al low ing sur plus gen er a tion in one re
- gion to sat isfy elec tric ity de mand in an import ing re gion, re sult ing in a cost sav ings. Econ omy trade with Can ada is de ter mined in a sim i lar man ner as in ter re gional econ
- omy trade. Sur plus Canadian en ergy is al lowed to dis
- place en ergy in an im port ing re gion if it re sults in a cost sav ings. Af ter dis patch ing, fuel use is re ported back to the fuel sup ply mod ules and op er at ing ex penses and rev e
- nues from trade are re ported to the elec tric ity fi nance and pric ing submodule. Electricity Finance and Pricing Submodule The costs of build ing ca pac ity, buy ing power, and gen - er at ing elec tric ity are tal lied in the elec tric ity fi nance and pric ing (EFP) submodule, which simulates both com
- pet i tive elec tric ity pric ing and the cost-of-ser vice method of ten used by State regula tors to de ter mine the price of elec tric ity. The AEO2009 ref er ence case as
- sumes a tran si tion to full com pet i tive pric ing in New York, Mid-At lan tic Area Coun cil, and Texas, and a 95 per cent tran si tion to com pet i tive pric ing in New Eng
- land (Ver mont be ing the only fully-reg u lated State in that re gion). Cal i for nia re turned to al most fully reg u
- lated pric ing in 2002, af ter be gin ning a tran si tion to com pe ti tion in 1998. In ad di tion elec tric ity prices in the

Energy Information Administration / The National Energy Modeling System: An Overview 2009 47 

# Electricity Market Module

Technology Capital Costs 1 (2007$/KW) Heatrate in 2008 (Btu/kWhr) Online Year 2 Scrubbed Coal New 2058 9200 2012 Integrated Coal-gasification Comb Cycle (IGCC) 2378 8765 2012 IGCC with carbon sequestration 3496 10781 2016 Coventional Gas/Oil Comb Cycle 962 7196 2011 Advanced Gas/Oil Comb Cycle (CC) 948 6752 2011 Advanced CC with carbon sequestration 1890 8613 2016 Conventional Combusion Turbine 670 10810 2010 Advanced Combusition Turbine 634 9289 2010 Fuel Cells 5360 7930 2011 Adv nuclear 3318 10434 2016 Distributed Generation - Base 1370 9050 2011 Distributed Generation - Peak 1645 10069 2010 Biomass 3766 9646 2012 MSW - Landfill Gas 2543 13648 2010 Geothermal 3 1711 34633 2010 Conventional Hydropower 3,4 2242 9919 2012 Wind 4 1923 9919 2009 Wind Offshore 4 3851 9919 2012 Solar Thermal 5021 9919 2012 Photovoltaic 6038 9919 2011 Table 12. 2008 Over night Cap i tal Costs (in clud ing Con tin gen cies), 2008 Heat Rates, and On line Year by Tech nol ogy for the AEO2009 Ref er ence Case

1 Over night cap i tal cost in clud ing con tin gency fac tors, ex clud ing reigonal mul ti pli ers and learn ing ef fects. In ter est charges are also ex cluded. These rep re sent costs of new pro jects ini ti ated in 2008. Cap i tal costs are shown be fore in vest ment tax cred its are ap plied, where ap pli ca ble. 2 On line year rep re sents the first year that a new unit could be com pleted, given an or der date of 2008. For wind, geo ther mal and land fill gas, the on line year was moved ear lier to ac knowl edge the sig nif i cant mar ket ac tiv ity al ready occuring in anticipation of the ex pi ra tion of the Pro duc tion Tax Credit in 2009 for wind and 2010 for the oth ers. 3 Be cause geo ther mal and hy dro cost and per for mance char ac ter is tics are spe cific for each site, the ta ble en tries rep re sent the cost of the least ex pen sive plant that could be built in the North west Power Pool re gion, where most of the pro posed sites are lo cated. 4 For hy dro, wind, and so lar tech nol o gies, the heatrate shown rep re sents the av er age heatrate for con ven tional ther mal gen er a tion as of 2007. This isused for pur - poses of cal cu lat ing pri mary en ergy con sump tion dis placed for these re sources, and does not im ply an es ti mate of their ac tual en ergy con ver sion ef fi ciency.East Cen tral Area Re li abil ity Coun cil, the Mid-Amer i can

In ter con nected Net work, the South east ern Elec tric Re
- li abil ity Coun cil, the South west Power Pool, the North
- west Power Pool, and the Rocky Moun tain Power Area/Ar i zona are a mix of both com pet i tive and reg u
- lated prices. Since some States in each of these re
- gions have not taken ac tion to de reg u late their pric ing of elec tric ity, prices in those States are as sumed to con tinue to be based on tra di tional cost-of-ser vice pric
- ing. The price for mixed re gions is a load-weighted av
- er age of the com pet i tive price and the reg u lated price, with the weight based on the per cent of elec tric ity load in the re gion that has taken ac tion to de reg u late. In re
- gions where none of the states in the re gion have in tro
- duced com pe ti tion—Florida Re li abil ity Co or di nat ing Coun cil and Mid-Con ti nent Area Power Pool—elec tric
- ity prices are as sumed to re main reg u lated and the cost-of-ser vice calculation is used to determine electricity prices. Us ing his tor i cal costs for ex ist ing plants (de rived from var i ous sources such as Fed eral En ergy Regula tory Com
- mis sion Form 1, An nual Re port of Ma jor Elec tric Util i - ties, Li cens ees and Oth ers, and Form EIA-412, An nual Re port of Pub lic Elec tric Util i ties), cost es ti mates for new plants, fuel prices from the NEMS fuel sup ply mod
- ules, unit op er at ing lev els, plant de com mis sion ing costs, plant phase-in costs, and pur chased power costs, the EFP submodule cal cu lates to tal rev e nue re quire ments for each area of op er a tion—gen er a tion, trans mis sion, and dis tri bu tion—for pric ing of elec tric ity in the fully reg u
- lated States. Rev e nue re quire ments shared over sales by cus tomer class yield the price of elec tric ity for each class. Elec tric ity prices are re turned to the de mand mod ules. In ad di tion, the submodule gen er ates de tailed fi nan cial state ments. For those States for which it is ap pli ca ble, the EFP also de ter mines com pet i tive prices for elec tric ity gen era tion. Un like cost-of-ser vice prices, which are based on av er
- age costs, com pet i tive prices are based on mar ginal costs. Mar ginal costs are pri mar ily the operating costs of the most ex pen sive plant re quired to meet de mand. The com pet i tive price also in cludes a re li abil ity price ad just
- ment, which rep re sents the value con sum ers place on re li abil ity of ser vice when de mands are high and avail able ca pac ity is lim ited. Prices for trans mis sion and dis tri bu
- tion are as sumed to re main reg u lated, so the de liv ered elec tric ity price un der com pe ti tion is the sum of the marginal price of gen er a tion and the av er age price of transmission and distribution. Electricity Load and Demand Submodule The elec tric ity load and de mand (ELD) submodule gen
- er ates load curves rep re sent ing the de mand for elec
- tric ity. The de mand for elec tric ity var ies over the course of a day. Many dif fer ent tech nol o gies and end uses, each re quir ing a dif fer ent level of ca pac ity for dif fer ent lengths of time, are pow ered by elec tric ity. For op er a tional and plan ning anal y sis, an an nual load du ra tion curve, which rep re sents the ag gre gated hourly de mands, is con structed. Be cause de mand var ies by geo graphic area and time of year, the ELD submodule gen er ates load curves for each re gion and sea son. Emissions EMM tracks emis sion lev els for sul fur di ox ide (SO 2 ) and ni tro gen ox ides (NO x ). Fa cil ity development, retro
- fit ting, and dis patch are con strained to com ply with the pol lu tion con straints of the CAAA90 and other pol lu tion con straints in clud ing the Clean Air In ter state Rule. An in no va tive fea ture of this leg is la tion is a sys tem of trad
- ing emis sions al low ances. The trad ing sys tem al lows a util ity with a rel a tively low cost of com pli ance to sell its ex cess com pli ance (i.e., the de gree to which its emis
- sions per unit of power gen er ated are be low max i mum al low able lev els) to util i ties with a rel a tively high cost of com pli ance. The trad ing of emis sions al low ances does not change the na tional ag gre gate emis sions level set by CAAA90, but it does tend to min i mize the over all cost of com pli ance. In ad di tion to SO 2 , and NO x , the EMM also de ter mines mer cury and car bon di ox ide emis sions. It rep re sents con trol op tions to re duce emis sions of these four gases, ei ther in di vid u ally or in any com bi na tion. Fuel switch ing from coal to nat u ral gas, renewables, or nu
- clear can re duce all of these emis sions. Flue gas desulfurization equip ment can de crease SO 2 and mer
- cury emis sions. Se lec tive cat a lytic re duc tion can re
- duce NO xand mer cury emis sions. Se lec tive non-cat a lytic re duc tion and low-NO xburn ers can lower NO xemis sions. Fab ric fil ters and ac ti vated car bon in
- jec tion can re duce mer cury emis sions. Lower emis
- sions re sult ing from de mand re duc tions are de ter mined in the end-use de mand mod ules. The AEO2009

in cludes a gen er al ized struc ture to model cur rent state-level reg u la tions call ing for the best avail able con trol tech nol ogy to con trol mer cury. The AEO2009

also in cludes the car bon caps for States that are part of the RGGI.

48 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Electricity Market Module

# Renew able Fuels Mod uleThe re new able fu els mod ule (RFM) rep re sents re new
-

able en ergy resoures and large–scale tech nol o gies used for grid-con nected U.S. elec tric ity sup ply (Fig ure 11). Since most renewables (bio mass, con ven tional hy dro elec tric ity, geo ther mal, land fill gas, so lar photovoltaics, so lar ther mal, and wind) are used to gen
- er ate elec tric ity, the RFM pri mar ily in ter acts with the electricity market module (EMM). New re new able en ergy gen er at ing ca pac ity is ei ther model–de ter mined or based on sur veys or other pub
- lished in for ma tion. A new unit is only in cluded in sur
- veys or acccepted from pub lished in for ma tion if it is re ported to or iden ti fied by the EIA and the unit meets EIA cri te ria for in clu sion (the unit ex ists, is un der con
- struc tion, un der con tract, is pub licly de clared by the ven dor, or is man dated by state law, such as un der a state re new able port fo lio stan dard). EIA may also as
- sume min i mal builds for rea sons based on his tor i cal ex
- pe ri ence (floors). The pen e tra tion of grid-con nected re new able en ergy gen er at ing tech nol o gies, with the exception of landfill gas, is determined by the EMM. Each re new able en ergy submodule of the RFM is treated in de pend ently of the oth ers, ex cept for their least-cost com pe ti tion in the EMM. Be cause vari able op er a tion and main te nance costs for re new able tech
- nol o gies are lower than for any other ma jor gen er at ing tech nol ogy, and be cause they gen er ally pro duce lit tle or no air pol lu tion, all avail able re new able ca pac ity, ex
- cept bio mass, is as sumed to be dis patched first by the EMM. Be cause of its po ten tially sig nif i cant fuel cost, bio mass is dis patched according to its variable cost by the EMM. With sig nif i cant growth over time, in stal la tion costs are as sumed to be higher be cause of grow ing con straints on the avail abil ity of sites, nat u ral re source deg ra da
- tion, the need to up grade ex ist ing trans mis sion or dis tri
- bu tion net works, and other re source-spe cific fac tors. Geothermal-Electric Submodule The geo ther mal-elec tric submodule pro vides the EMM the amounts of new geo ther mal ca pac ity that can be built at known and well char ac ter ized geo ther mal re
- source sites, along with re lated cost and per for mance data. The in for ma tion is ex pressed in the form of a three–step sup ply func tion that rep re sents the ag gre
- gate amount of new ca pac ity and as so ci ated costs that can be of fered in each year in each region. Only hy dro ther mal (hot wa ter and steam) re sources are con sid ered. Hot dry rock re sources are not in
- cluded, be cause they are not ex pected to be eco nom i
- cally ac ces si ble dur ing the NEMS pro jec tion horizon. Cap i tal and op er at ing costs are es ti mated sep a rately, and life-cy cle costs are cal cu lated by the RFM. The cost ing meth od ol ogy in cor po rates any ap pli ca ble ef
- fects of Fed eral and State en ergy tax con struc tion and pro duc tion in cen tives Wind-Electric Submodule The wind-elec tric submodule pro jects the avail abil ity of wind re sources as well as the cost and per for mance of wind tur bine gen er a tors. This in for ma tion is passed to EMM so that wind tur bines can be built and dis patched in com pe ti tion with other elec tric ity gen er at ing tech nol
- o gies. The wind tur bine data are ex pressed in the form of en ergy sup ply curves that pro vide the max i mum amount, cap i tal cost, and ca pac ity fac tor of tur bine gen
- er at ing ca pac ity that could be in stalled in a re gion in a year, given the avail able land area and wind speed. The model also eval u ates the con tri bu tion of the wind ca pac ity to meet ing sys tem re li abil ity re quire ments so that the EMM can ap pro pri ately in cor po rate wind ca
- pac ity into cal cu la tions for re gional reliability reserve margins. So lar-Elec tric Submodule The so lar-elec tric submodule rep re sents both pho to
-vol taic and high-tem per a ture ther mal elec tric (concen50 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Renewable Fuels Module

RFM Outputs Inputs from NEMS Exogenous Inputs En ergy pro duc tion ca pac i ties Cap i tal costs Op er at ing costs (in clud ing wood sup ply prices for the wood submodule) Ca pac ity factors Avail able ca pac ity Bio mass fuel costs Bio mass sup ply curves In stalled en ergy pro duc tion capacity Gross do mes tic prod uct Pop u la tion In ter est Rates Avoided cost of elec tric ity Dis count rate Ca pac ity additions Bio mass con sump tion Site-spe cific geo ther mal re source quan tity data Site-spe cific and re source qual ity data Plant uti li za tion (capacity fac tor)Trans mis sion and dis tri bu tion costs Tech nol ogy cost and per for mance pa ram e ters Land fill gas ca pac ityEnergy Information Administration / The National Energy Modeling System: An Overview 2009 51 

# Renewable Fuels Module

Cost Characteristics, Capacity Factor, Available Capacity Avoided Cost, Installed Capacity, Discount Rate Cost Characteristics, Time Segment Capacity Factors, Available Capacity by Wind Class Capacity Additions

Cost Characteristics, Capacity Factor, Installed Capacity Cost Characteristics, Capacity Factor, Fuel Cost, Available Capacity Biomass Consumption Macroeconomic Activity Module

Demand Modules Biomass Consumption Gross Domestic Product, Population, Interest Rates 

### Electricity Market Module Geothermal Electric Submodule

Wind-Electric Submodule

Solar-Electric Submodule Cost Characteristics, Time Segment Capacity Factors, Available Capacity 

### Renewable Fuels Module Exogenous Technological Characteristics, Capital Costs, Operating Costs, Resource Data, Landfill Gas Capacity, Municipal Solid Waste Trends

Municipal Solid Waste Submodule

Biomass Fuels Submodule Petroleum Market Module Biomass Supply Curves -

Biomass

Consumption Hydroelectricity Submodule Cost Characteristics Capacity Factor Available Capacity Avoided Cost Installed Capacity Discount Rate Fig ure 11. Re new able Fu els Mod ule Structuretrating so lar power) in stal la tions. Only cen tral-sta tion,

grid-con nected ap pli ca tions con structed by a util ity or in de pend ent power pro ducer are con sid ered in this por tion of the model. The so lar-elec tric submodule pro vides the EMM with time-of-day and sea sonal so lar avail abil ity data for each re gion, as well as cur rent costs. The EMM uses this data to eval u ate the cost and per for mance of so
- lar-elec tric tech nol o gies in re gional grid ap pli ca tions. The com mer cial and res i den tial de mand mod ules of NEMS also model pho to vol taic sys tems in stalled by con sum ers, as dis cussed in the de mand mod ule de
- scrip tions un der “Dis trib uted Gen er a tion.” Land fill Gas Submodule The land fill gas submodule pro vides an nual pro jec tions of elec tric ity gen er a tion from meth ane from land fills (land fill gas). The submodule uses the quan tity of mu
- nic i pal solid waste (MSW) that is pro duced, the pro por
- tion of MSW that will be re cy cled, and the meth ane emis sion char ac ter is tics of three types of land fills to pro duce pro jec tions of the fu ture elec tric power gen er- at ing ca pac ity from land fill gas. The amount of meth
- ane avail able is cal cu lated by first de ter min ing the amount of to tal waste gen er ated in the United States

. The amount of to tal waste gen er ated is de rived from an ec ono met ric equa tion that uses gross do mes tic prod
- uct and pop u la tion as the pro jec tion driv ers. It is as
- sumed that no new mass burn waste–to–en ergy (MSW) fa cil i ties will be built and op er ated dur ing the pro jec tion pe riod in the United States . It is also as
- sumed that op er a tional mass-burn fa cil i ties will con
- tinue to op er ate and re tire as planned through out the pro jec tion pe riod. The land fill gas submodule passes cost and per for mance char ac ter is tics of the land fill gas–to–elec tric ity tech nol ogy to the EMM for ca pac ityplan ning de ci sions. The amount of new land-fill-gas-toelec tric ity ca pac ity com petes with other tech nol o gies us ing sup ply curves that are based on the amount of high, me dium, and low meth ane pro duc ing land fills lo
- cated in each EMM re gion. Bio mass Fu els Submodule The bio mass fu els submodule pro vides bio mass-fired plant tech nol ogy char ac ter iza tions (cap i tal costs, op er
- at ing costs, ca pac ity fac tors, etc.) and fuel in for ma tion for EMM, thereby al low ing bio mass-fu eled power plants to com pete with other elec tric ity gen er at ing tech nol o gies. Bio mass fuel prices are rep re sented by a sup ply curve con structed ac cord ing to the ac ces si bil ity of re sources to the elec tric ity gen er a tion sec tor. The sup ply curve em ploys re source in ven tory and cost data for four cat e
- go ries of bio mass fuel - ur ban wood waste and mill res i
- dues, for est res i dues, en ergy crops, and ag ri cul tural res i dues. Fuel dis tri bu tion and prep a ra tion cost data are built into these curves. The sup ply sched ule of bio
- mass fuel prices is com bined with other vari able op er
- at ing costs as so ci ated with burn ing bio mass. The ag gre gate vari able cost is then passed to EMM. Hydroelectricity Submodule The hy dro elec tric ity submodule pro vides the EMM the amounts of new hy dro elec tric ca pac ity that can be built at known and well char ac ter ized sites, along with re
- lated cost and per for mance data. The in for ma tion is ex
- pressed in the form of a three–step sup ply func tion that rep re sents the ag gre gate amount of new ca pac ity and as so ci ated costs that can be of fered in each year in each re gion. Sites in clude un de vel oped stretches of rivers, ex ist ing dams or di ver sions that do not cur rently pro duce power, and ex ist ing hy dro elec tric plants that have known ca pa bil ity to ex pand op er a tions through the ad di tion of new gen er at ing units. Ca pac ity or ef fi
- ciency im prove ments through the re place ment of ex ist
- ing equip ment or changes to op er at ing pro ce dures at a fa cil ity are not in cluded in the hy dro elec tric ity sup ply.

52 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Renewable Fuels Module

# Oil And Gas Supply Mod uleThe OGSM con sists of a se ries of pro cess submodules

that pro ject the avail abil ity of do mes tic crude oil production and dry natural gas production from onshore, offshore, and Alaskan res er voirs, as well as con ven tional gas pro duc tion from Can ada. The OGSM re gions are shown in Fig ure 12. The driv ing as sump tion of OGSM is that do mes tic oil and gas ex plo ra tion and de vel op ment are un der taken if the dis counted pres ent value of the re cov ered re
- sources at least cov ers the pres ent value of taxes and the cost of cap i tal, ex plo ra tion, de vel op ment, and pro
- duc tion. Crude oil is trans ported to re fin er ies, which are sim u lated in the PMM, for con ver sion and blend ing into re fined pe tro leum prod ucts. The in di vid ual submodules of the OGSM are solved in de pend ently, with feed backs achieved through NEMS solu tion iterations (Figure 13). Tech no log i cal prog ress is rep re sented in OGSM through an nual in creases in the find ing rates and suc
- cess rates, as well as an nual de creases in costs. For con ven tional on shore, a time trend was used in econometrically es ti mated equa tions as a proxy for tech nol ogy. Re serve ad di tions per well (or find ing rates) are pro jected through a set of equa tions that distinquish be tween new field dis cov er ies and dis cov
- er ies (ex ten sions) and re vi sions in known fields. The find ing rate equa tions cap ture the im pacts of tech nol
- ogy, prices, and de clin ing re sources. An other rep re
- sen ta tion of tech nol ogy is in the suc cess rate equa tions. Suc cess rates cap ture the im pact of tech
- nol ogy and sat u ra tion of the area through cu mu la tive drill ing. Tech nol ogy is fur ther rep re sented in the de ter
- mi na tion of drill ing, lease equip ment, and op er at ing costs. Tech no log i cal prog ress puts down ward pres
- sure on the drill ing, lease equip ment, and op er at ing cost pro jec tions. For un con ven tional gas, a se ries of eleven dif fer ent tech nol ogy groups are rep re sented by time–de pend ent ad just ments to fac tors which in flu ence find ing rates, success rates, and costs. Con ven tional nat u ral gas pro duc tion in West ern Can
- ada is mod eled in OGSM with three econometrically es ti mated equa tions: to tal wells drilled, re serves added per well, and ex pected pro duc tion-to-re serves ra tio. The model per forms a sim ple re serves ac count ing and ap plies the ex pected pro duc tion-to-re serve ra tio to es ti
- mate an ex pected pro duc tion level, which in turn is used to es tab lish a sup ply curve for con ven tional West
- ern Can ada nat u ral gas. The rest of the gas pro duc tion sources in Can ada are rep re sented in the Nat u ral Gas Trans mis sion and Dis tri bu tion Mod ule (NGTDM). Lower 48 Onshore and Shallow Offshore Supply Submodule The lower 48 on shore sup ply submodule pro jects crude oil and nat u ral gas pro duc tion from con ven tional re cov ery tech niques. This submodule ac counts for drill
- ing, re serve ad di tions, to tal re serves, and pro duc tion -to-re serves ra tios for each lower 48 on shore sup ply region. The ba sic pro ce dure is as fol lows:

• First, the pro spec tive costs of a rep re sen ta tive drill
- ing pro ject for a given fuel cat e gory and well class within a given re gion are com puted. Costs are a func tion of the level of drill ing ac tiv ity, av er age well depth, rig avail abil ity, and the ef fects of tech no log i
- cal progress.

• Sec ond, the pres ent value of the dis counted cash flows (DCF) as so ci ated with the rep re sen ta tive pro
- ject is com puted. These cash flows in clude both the cap i tal and op er at ing costs of the pro ject, in clud ing roy al ties and taxes, and the rev e nues de rived from a de clin ing well pro duc tion pro file, com puted af ter tak ing into ac count the pro gres sive ef fects of re
- source de ple tion and val ued at con stant real prices as of the year of initial valuation.

• Third, drill ing lev els are cal cu lated as a func tion of pro jected prof it abil ity as mea sured by the pro jected DCF lev els for each pro ject and na tional level cash
- flow.

54 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Oil and Gas Supply Module

OGSM Outputs Inputs from NEMS Exogenous Inputs Crude oil pro duc tion Do mes tic nonassociated and Ca na dian con ven tional nat u ral gas suply curves Cogeneration from oil and gas producton Re serves and re serve ad di tions Drill ing lev els Do mes tic as so ci ated-dis solved gas pro duc tion Do mes tic and Ca na dian nat u ral gas pro duc tion and well head prices Crude oil de mand World oil price Elec tric ity price Gross do mes tic prod uct In fla tion rate Re source lev els Ini tial find ing rate parameters and costs Pro duc tion pro files Tax parameters• Fourth, re gional find ing rate equa tions are used to

pro ject new field dis cov er ies from new field wild
- cats, new pools, and ex ten sions from other ex plor
- atory drill ing, and re serve re vi sions from de vel op ment drill ing.

• Fifth, pro duc tion is de ter mined on the ba sis of re
- serves, in clud ing new re serve ad di tions, pre vi ous pro duc tive ca pac ity, flow from new wells, and, in the case of nat u ral gas, fuel de mands. This oc curs within the mar ket equil i bra tion of the NGTDM for nat u ral gas and within OGSM for oil. Un con ven tional Gas Re cov ery Sup ply Submodule Un con ven tional gas is de fined as gas pro duced from nonconventional geo logic for ma tions, as op posed to con ven tional (sand stones) and car bon ate rock for ma
- tions. The three un con ven tional geo logic for ma tions con sid ered are low–per me abil ity or tight sand stones, gas shales and coalbed methane. For un con ven tional gas, a play–level model cal cu lates the eco nomic fea si bil ity of in di vid ual plays based on lo
- cally spe cific well head prices and costs, re source quan tity and qual ity, and the var i ous ef fects of tech nol
- ogy on both re sources and costs. In each year, an ini tial re source char ac ter iza tion de ter mines the ex pected ul ti
- mate re cov ery (EUR) for the wells drilled in a par tic u lar play. Re source pro files are ad justed to re flect as sumed tech no log i cal im pacts on the size, avail abil ity, and in
- dus try knowl edge of the re sources in the play.

Energy Information Administration / The National Energy Modeling System: An Overview 2009 55 

# Oil and Gas Supply Module

Rocky Mountain West Coast

Pacific Midcontinent

South West Northwest

Gulf Coast

Gulf of Mexico Offshore North Slope

Other Alaska North Slope Onshore Ocean Atlantic Ocean Fig ure 12. Oil and Gas Supply Module RegionsSub se quently, prices re ceived from NGTDM and en
-

dog e nously de ter mined costs ad justed to re flect tech
- no log i cal prog ress are uti lized to cal cu late the eco nomic prof it abil ity (or lack thereof) for the play. If the play is prof it able, drill ing oc curs ac cord ing to an as
- sumed sched ule, which is ad justed an nu ally to ac count for tech no log i cal im prove ments, as well as vary ing eco
- nomic con di tions. This drill ing re sults in re serve ad di
- tions, the quan ti ties of which are di rectly re lated to the EURs for the wells in that play. Given these re serve ad
- di tions, re serve lev els and ex pected pro duc tion–to–re
- serves (P/R) ra tios are cal cu lated at both the OGSM and the NGTDM re gion level. The re sul tant val ues are ag gre gated with sim i lar val ues from the con ven tional on shore and off shore submodules. The ag gre gate P/R ra tios and re serve lev els are then passed to NGTDM, which de ter mines the prices and pro duc tion for the fol
- low ing year through mar ket equil i bra tion. Off shore Sup ply Submodule This submodule uses a field-based en gi neer ing ap
- proach to rep re sent the ex plo ra tion and de vel op ment of U.S. off shore oil and nat u ral gas re sources. The submodule sim u lates the eco nomic de ci sion-mak ing at each stage of de vel op ment from fron tier ar eas to post-ma ture ar eas. Off shore re sources are di vided into 3 cat e go ries:

• Un dis cov ered Fields. The num ber, lo ca tion, and size of the un dis cov ered fields are based on the MMS's 2006 hy dro car bon re source as sess ment.

• Dis cov ered, Un de vel oped Fields. Any dis cov ery that has been an nounced but is not cur rently pro
- duc ing is eval u ated in this com po nent of the model. The first pro duc tion year is an in put and is based on an nounced plans and ex pec ta tions.

56 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Oil and Gas Supply Module

NEMS Oil and Gas Supply Module

Resource Levels, Finding Rates, Costs, Production Profiles, Taxes Exogenous Natural Gas Transmission and Distribution Module

Industrial Demand Module Electricity Market Module Electricity Price

Oil and Gas Supply Submodules Petroleum Market Module

Associated-Dissolved Gas Production Supply Curves for Domestic and Canadian Natural Gas

Crude Oil Production Crude Oil Demand

Combined Heat and Power Natural Gas Production and Expectations International Energy Module World Oil Price

Wellhead Prices Domestic and Canadian Fig ure 13. Oil and Gas Sup ply Mod ule Structure• Pro duc ing Fields. The fields in this cat e gory have

wells that have pro duced oil and/or gas through the year prior to the AEO pro jec tion. The pro duc tion vol umes are from the Min er als Man age ment Ser
- vice (MMS) da ta base. Re source and eco nomic cal cu la tions are per formed at an eval u a tion unit ba sis. An eval u a tion unit is de fined as the area within a plan ning area that falls into a spe
- cific wa ter depth cat e gory. Plan ning ar eas are the West ern Gulf of Mex ico (GOM), Cen tral GOM, East ern GOM, Pa cific, and At lan tic. There are six wa ter depth cat e go ries: 0-200 me ters, 200-400 me ters, 400-800 me ters, 800-1600 me ters, 1600-2400 me ters, and greater than 2400 me ters. Sup ply curves for crude oil and nat u ral gas are gen er
- ated for three off shore re gions: Pa cific, At lan tic, and GOM . Crude oil pro duc tion in cludes lease con den sate. Nat u ral gas pro duc tion ac counts for both nonassociated gas and as so ci ated-dis solved gas. The model is re spon sive to changes in oil and nat u ral gas prices, roy alty re lief as sump tions, oil and nat u ral gas re source base, and tech no log i cal im prove ments af fect
- ing ex plo ra tion and de vel op ment. Alaska Oil and Gas Submodule This submodule pro jects the crude oil and nat u ral gas pro duced in Alaska. The Alas kan oil submodule is di
- vided into three sec tions: new field dis cov er ies, de vel
- op ment pro jects, and pro duc ing fields. Oil trans por ta tion costs to lower 48 fa cil i ties are used in con junc tion with the rel e vant mar ket price of oil to cal
- cu late the es ti mated net price re ceived at the well head, some times called the netback price. A dis counted cash flow method is used to de ter mine the eco nomic vi a bil ity of each pro ject at the netback price. Alas kan oil sup plies are mod eled on the ba sis of dis
- crete pro jects, in con trast to the on shore lower 48 con
- ven tional oil and gas sup plies, which are mod eled on an ag gre gate level. The con tin u a tion of the ex plo ra tion and de vel op ment of multiyear pro jects, as well as the dis cov ery of new fields, is de pend ent on prof it abil ity. Pro duc tion is de ter mined on the ba sis of as sumed drill
- ing sched ules and pro duc tion pro files for new fields and de vel op men tal pro jects, his tor i cal pro duc tion pat terns, and an nounced plans for cur rently pro duc ing fields.

• Alas kan gas pro duc tion is set sep a rately for any gas tar geted to flow through a pipe line to the lower 48 States and gas pro duced for con sump tion in the State and for ex port to Ja pan . The lat ter is set based on a pro jec tion of Alas kan con sump tion in the NGTDM and an ex og e nous spec i fi ca tion of ex
- ports. North Slope pro duc tion for the pipe line is de
- pend ent on con struc tion of the pipe line, set to com mence if the lower 48 av er age well head price is main tained at a level ex ceed ing the es tab lished com pa ra ble cost of de liv ery to the lower 48 States.

Energy Information Administration / The National Energy Modeling System: An Overview 2009 57 

# Oil and Gas Supply Module

# Nat u ral Gas Trans mis sion

and Dis tri bu tion Mod uleThe NGTDM of NEMS rep re sents the nat u ral gas mar
-

ket and de ter mines re gional mar ket–clear ing prices for nat u ral gas sup plies and for end–use con sump tion, given the in for ma tion passed from other NEMS mod
- ules (Fig ure 14). A trans mis sion and dis tri bu tion net
- work (Fig ure 15), com posed of nodes and arcs, is used to sim u late the in ter re gional flow and pric ing of gas in the con tig u ous United States and Can ada in both the peak (De cem ber through March) and offpeak (April through No vem ber) pe riod. This net work is a sim pli fied rep re sen ta tion of the phys i cal nat u ral gas pipe line sys
- tem and es tab lishes the pos si ble in ter re gional flows and as so ci ated prices as gas moves from supply sources to end users. Flows are fur ther rep re sented by es tab lish ing arcs from trans ship ment nodes to each de mand sec tor rep re
- sented in an NGTDM re gion (res i den tial, com mer cial, in dus trial, elec tric gen er a tors, and trans por ta tion). Mex i can ex ports and net stor age in jec tions in the offpeak pe riod are also rep re sented as flow ex it ing a trans ship ment node. Sim i larly, arcs are also es tab
- lished from sup ply points into a trans ship ment node. Each trans ship ment node can have one or more en ter
- ing arcs from each sup ply source rep re sented: U.S. or Ca na dian on shore or U.S. off shore pro duc tion, liq ue
- fied nat u ral gas im ports, sup ple men tal gas pro duc tion, gas pro duced in Alaska and trans ported via pipe line, Mex i can im ports, or net stor age with draw als in the re
- gion in the peak pe riod. Most of the types of sup ply listed above are set in de pend ently of cur rent year prices and be fore NGTDM de ter mines a mar ket equi
- lib rium so lu tion. Only the on shore and off shore lower 48 U.S. and West
- ern Ca na dian Sed i men tary Ba sin pro duc tion, along with net stor age with draw als, are rep re sented by short–term sup ply curves and set dy nam i cally dur ing the NGTDM so lu tion pro cess. The con struc tion of nat u
- ral gas pipe lines from Alaska and Can ada’s Mac Ken zie Delta are trig gered when mar ket prices ex ceed es ti
- mated pro ject costs. The flow of gas dur ing the peak pe riod is used to es tab lish in ter re gional pipe line and stor age ca pac ity re quire ments and the as so ci ated ex
- pan sion. These ca pac ity lev els pro vide an upper limit for the flow during the offpeak period. Arcs be tween trans ship ment nodes, from the trans
- ship ment nodes to end–use sec tors, and from sup ply sources to trans ship ment nodes are as signed tar iffs. The tar iffs along in ter re gional arcs re flect res er va tion (rep re sented with vol ume de pend ent curves) and us
- age fees and are es tab lished in the pipe line tar iff submodule. The tar iffs on arcs to end–use sec tors rep
- re sent the in ter state pipe line tar iffs in the re gion, in tra
- state pipe line tar iffs, and dis trib u tor mark ups set in the dis trib u tor tar iff submodule. Tar iffs on arcs from sup ply sources rep re sent gath er ing charges or other dif fer en
- tials be tween the price at the sup ply source and the re
- gional mar ket hub. The tar iff as so ci ated with in ject ing, stor ing, and with draw ing from stor age is as signed to the arc rep re sent ing net stor age with draw als in the peak pe riod. Dur ing the pri mary so lu tion pro cess in the in ter state trans mis sion submodule, the tar iffs along an in ter re gional arc are added to the price at the source node to ar rive at a price for the gas along the arc right be fore it reaches its des ti na tion node. 

### Interstate Transmission Submodule The in ter state trans mis sion submodule (ITS) is the main in te grat ing mod ule of NGTDM. One of its ma jor func tions is to sim u late the nat u ral gas price de ter mi na
- tion pro cess. ITS brings to gether the ma jor eco nomic fac tors that in flu ence re gional nat u ral gas trade on a sea sonal ba sis in the United States, the bal anc ing of the de mand for and the do mes tic sup ply of nat u ral gas, in clud ing com pe ti tion from im ported nat u ral gas. These are ex am ined in com bi na tion with the rel a tive prices as
- so ci ated with mov ing the gas from the pro ducer to the end user where and when (peak ver sus offpeak) it is

Energy Information Administration / The National Energy Modeling System: An Overview 2009 59 

# Natural Gas Transmission And Distribution Module

NGTDM Outputs Inputs from NEMS Exogenous Inputs Nat u ral gas de liv ered prices Do mes tic and Ca na dian nat u ral gas wellhead prices Do mes tic nat u ral gas pro duc tion Mex i can and liq ue fied nat u ral gas im ports and ex ports Ca na dian nat u ral gas im ports and pro duc tion Lease and plant fuel con sump tion Pipe line and dis tri bu tion tar iffs In ter re gional nat u ral gas flows Stor age and pipe line ca pac ity ex pan sion Sup ple men tal gas production Nat u ral gas de mands Do mes tic and ca na dian nat u ral gas sup ply curves Mac ro eco nomic vari ables As so ci ated-dis solved nat u ral gas production His tor i cal con sump tion and flow pat terns His tor i cal sup plies Pipe line com pany-level fi nan cial data Pipe line and stor age ca pac ity and uti li za tion data His tor i cal end-use citgate, and well head prices State and Fed eral tax pa ram e ters Pipe line and stor age ex pan sion cost data Liq ue fied nat u ral gas sup ply curves Can ada and Mex ico con sump tion projections60 Energy Information Administration / The National Energy Modeling System 2009 

# Natural Gas Transmission And Distribution Module

NEMS Macroeconomic Activity Module

Oil and Gas Supply Module

Petroleum Market Module

Demand Modules

Electricity Market Module Exogenous Historical values Company-Level Financial Data, Pipeline and Storage Capacity, Utilization and Cost Data, State and Federal Tax Parameters, Liquefied Natural Gas Supply Curves Canada and Mexico Consumption Projections

Interstate Transmission Submodule

Distributor Tariff Submodule 

### Natural Gas Transmission and Distribution Module
Expansion Cost Curves (Exogenous)

Pipeline Tariff Submodule

Distributor Markups

Lease and Plant Fuel Consumption, Pipeline Fuel Consumption Macroeconomic Variables Natural Gas Prices, Production, and Industry Activity Domestic and Canadian Natural Gas Supply Curves Associated-Dissolved Gas Production

Domestic and Canadian Natural Gas Wellhead Prices Domestic and Canadian Natural Gas Production Natural Gas Prices and Production Natural Gas Core and Noncore ConsumptionNatural Gas EndUse Prices

Peak and Offpeak, Core and Noncore Consumption
Natural Gas Prices Interstate Tariffs Curves Interstate Flows

and Capacity Expansion

Natural Gas Imports and Exports Fig ure 14. Nat u ral Gas Trans mis sion and Dis tri bu tion Mod ule Structureneeded. In the pro cess, ITS sim u lates the de ci
-

sion–mak ing pro cess for ex pand ing pipe line and/or sea sonal stor age ca pac ity in the U.S. gas mar ket, de
- ter min ing the amount of pipe line and stor age ca pac ity to be added be tween or within re gions in NGTDM. Stor
- age serves as the pri mary link be tween the two sea
- sonal pe ri ods rep re sented. ITS em ploys an it er a tive heu ris tic al go rithm, along with an acy clic hi er ar chi cal rep re sen ta tion of the pri mary arcs in the net work, to es tab lish a mar ket equi lib rium so lu tion. Given the con sump tion lev els from other NEMS mod ules, the ba sic pro cess fol lowed by ITS in
- volves first es tab lish ing the back ward flow of nat u ral gas in each pe riod from the con sum ers, through the net work, to the pro duc ers, based pri mar ily on the rel a
- tive prices of fered for the gas from the pre vi ous ITS it er
- a tion. This pro cess is per formed for the peak pe riod first since the net with draw als from stor age dur ing the peak pe riod will es tab lish the net in jec tions dur ing the offpeak pe riod. Sec ond, us ing the model’s sup ply curves, well head and im port prices are set cor re spond
- ing to the de sired pro duc tion vol umes. Also, us ing the pipe line and stor age tar iffs from the pipe line tar iff submodule, pipe line and stor age tar iffs are set cor re
- spond ing to the as so ci ated flow of gas, as de ter mined in the first step. These prices are then trans lated from the pro duc ers, back through the net work, to the city gate and the end us ers, by add ing the ap pro pri ate tar
- iffs along the way. A re gional stor age tar iff is added to the price of gas in jected into stor age in the offpeak to ar rive at the price of the gas when with drawn in the peak pe riod. This pro cess is then re peated un til the so
- lu tion has con verged. Fi nally, de liv ered prices are de
- rived for res i den tial, com mer cial, and trans por ta tion cus tom ers, as well as for both core and noncore in dus
- trial and elec tric gen er a tion sec tors us ing the dis trib u tor tar iffs pro vided by the dis trib u tor tar iff submodule. Pipeline Tariff Submodule The pipe line tar iff submodule (PTS) pro vides us age fees and vol ume de pend ent curves for com put ing unit
- ized res er va tion fees (or tar iffs) for in ter state trans por
- ta tion and stor age ser vices within the ITS. These curves ex tend be yond cur rent ca pac ity lev els and re
- late in cre men tal pipe line or stor age ca pac ity ex pan sion to cor re spond ing es ti mated rates. The un der ly ing ba sis for each tar iff curve in the model is a pro jec tion of theas so ci ated reg u lated rev e nue re quire ment. Economet ri cally es ti mated equa tions within a gen eral ac
- count ing frame work are used to track costs and com
- pute rev e nue re quire ments as so ci ated with both res er va tion and us age fees un der cur rent rate de sign and reg u la tory sce nar ios. Other than an as sort ment of mac ro eco nomic in di ca tors, the pri mary in put to PTS from other mod ules in NEMS is pipe line and stor age ca pac ity uti li za tion and ex pan sion in the pre vi ous pro
- jec tion year. Once an ex pan sion is pro jected to oc cur, PTS cal cu
- lates the re sult ing im pact on the rev e nue re quire ment. PTS as sumes rolled–in (or av er age), not in cre men tal, rates for new ca pac ity. The pipe line tar iff curves gen er
- ated by PTS are used within the ITS when de ter min ing the rel a tive cost of pur chas ing and mov ing gas from one source ver sus an other in the peak and offpeak sea sons. Distributor Tariff Submodule The dis trib u tor tar iff submodule (DTS) sets dis trib u tor mark ups charged by lo cal dis tri bu tion com pa nies for the dis tri bu tion of nat u ral gas from the city gate to the end user. For those that do not typ i cally pur chase gas through a lo cal dis tri bu tion com pany, this markup rep
- re sents the dif fer en tial be tween the citygate and de liv
- ered price. End–use dis tri bu tion ser vice is dis tin guished within the DTS by sec tor (res i den tial, com mer cial, in dus trial, elec tric gen er a tors, and trans
- por ta tion), sea son (peak and offpeak), and ser vice type (core and noncore). Dis trib u tor tar iffs for all but the trans por ta tion sec tor are set us ing econometrically es ti mated equa tions. The nat u ral gas ve hi cle sec tor mark ups are cal cu lated sep
- a rately for fleet and per sonal ve hi cles and ac count for dis tri bu tion to de liv ery sta tions, re tail mark ups, and fed
- eral and state mo tor fu els taxes. Natural Gas Imports and Exports Liq ue fied nat u ral gas im ports for the U.S., Can ada, and Baja, Mex ico are set at the be gin ning of each NEMS it
- er a tion within the NGTDM by eval u at ing sea sonal east and west sup ply curves, based on out puts from EIA’s In ter na tional Nat u ral Gas Model, at as so ci ated regasification tail gate prices set in the pre vi ous NEMS it er a tion. A shar ing al go rithm is used to al lo cate the re
- sult ing im port vol umes to par tic u lar re gions. LNG ex
- ports to Ja pan from Alaska are set ex og e nously by the OGSM. The Mex ico model is largely based on ex og e nously spec i fied as sump tions about con sump tion and pro duc
- tion growth rates and LNG im port lev els. For the most part, nat u ral gas im ports from Mex ico are set ex og e
- nously for each of the three bor der cross ing points with 

# Natural Gas Transmission And Distribution Module

Energy Information Administration / The National Energy Modeling System 2009 61the United States, with the ex cep tion of any gas that is

im ported into Baja , Mex ico in liq uid form only to be ex
- ported to the United States . Ex ports to Mex ico from the United States are es tab lished be fore the NGTDM equilibrates and rep re sent the re quired level to bal ance the as sumed con sump tion in (and ex ports from) Mex
- ico against do mes tic pro duc tion and LNG im ports. The pro duc tion lev els are also largely as sump tion based, but are set to vary with changes in the ex pected well
- head price in the United States

. A node for east and west Can ada is in cluded in the NGTDM equil i bra tion net work, as well as seven bor der cross ings into the United States. The model in cludes a rep re sen ta tion/ac count ing of the U.S. bor der cross ing pipe line ca pac ity, east and west sea sonal stor age trans fers, east and west con sump tion, east and west LNG im ports, east ern pro duc tion, con ven tional/tight sands pro duc tion in the west, and coalbed/shale pro
- duc tion. Im ports from the United States , con ven tional pro duc tion in east ern Can ada , and base level nat u ral gas con sump tion (which var ies with the world oil price) are set ex og e nously. Con ven tional/tight sands pro duc
- tion in the west is set us ing a sup ply curve from the OGSM. Coalbed and shale gas pro duc tion are ef fec
- tively based on an as sumed pro duc tion growth rate which is ad justed with re al ized prices. 

# Natural Gas Transmission And Distribution Module

62 Energy Information Administration / The National Energy Modeling System: An Overview 2009 Fig ure 15. Natural Gas Transmission and Distribution Module Network

# Petro leum Market Mod uleThe PMM rep re sents do mestic refinery operations and

the marketing of liq uid fu els to consumption regions. PMM solves for liq uid fuel prices, crude oil and product import activity (in conjunction with the IEM and the OGSM), and domestic refinery capacity expansion and fuel consumption. The so lu tion sat is fies the demand for liq uid fu els, incorporating the prices for raw material in
- puts, im ported liq uid fu els, cap i tal invest ment, as well as the domestic production of crude oil, natural gas liq
- uids, and other un con ven tional re fin ery inputs. The relationship of PMM to other NEMS modules is illustrated in Figure 16. The PMM is a re gional, lin ear pro gram ming for mu la tion of the five Pe tro leum Administration for De fense Dis tricts (PADDs) (Fig ure 17). For each re gion two dis tinct re
- finery are mod eled. One is highly com plex us ing over 40 dif fer ent refinrry pro cesses, while the sec ond is de
- fined as a sim ple re fin ery that pro vides mar ginal cost eco nom ics. Re fin ing ca pac ity is al lowed to ex pand in each re gion, but the model does not dis tin guish be tween ad di tions to ex ist ing re fin er ies or the build ing of new fa cil i
- ties. In vest ment cri te ria are de vel oped ex og e nously, al
- though the de ci sion to in vest is endogenous. PMM as sumes that the pe tro leum re fin ing and mar keting in dus try is com pet i tive. The mar ket will move to ward lower-cost re fin ers who have ac cess to crude oil and mar
- kets. The se lec tion of crude oils, re fin ery pro cess uti li za
- tion, and lo gis tics (trans por ta tion) will ad just to min i mize the over all cost of sup ply ing the mar ket with liq uid fu els. PMM's model for mu la tion re flects the op er a tion of do
- mes tic liquuid fu els. If de mand is un usu ally high in one re gion, the price will in crease, driv ing down de mand and pro vid ing eco nomic in cen tives for bring ing sup plies in from other re gions, thus re stor ing the sup ply and de mand bal ance. Ex ist ing reg u la tions con cern ing prod uct types and spec i fi ca tions, the cost of en vi ron men tal com pli ance, and Fed eral and State taxes are also mod eled. PMM in cor po rates pro vi sions from the En ergy In de pend ence and Se cu rity Act of 2007 (EISA2007) and the En ergy Pol icy Act of 2005 (EPACT05). The costs of pro duc ing new for mu la tions of gas o line and die sel fuel as a re sult of the CAAA90 are de ter mined within the lin ear-pro
- gram ming rep re sen ta tion by in cor po rat ing spec i fi ca
- tions and de mands for these fuels. PMM also in cludes the in ter ac tion be tween the do mes
- tic and in ter na tional mar kets. Prior to AEO2009, PMM pos tu lated en tirely ex og e nous prices for oil on the in ter
- na tional mar ket (the world oil price). Sub se quent AEOs in clude an In ter na tional En ergy Mod ule (IEM) that es ti
- mates sup ply curves for im ported crude oils and prod
- ucts based on, among other fac tors, U.S. par tic i pa tion in global trade of crude oil and liq uid fu els. Re gions PMM mod els U.S. crude oil re fin ing ca pa bil i ties based on the five PADDs which were es tab lished dur ing World War II and are still used by EIA for data col lec tion and anal y sis. The use of PADD data per mits PMM to take full ad van tage of EIA’s histori cal da ta base and al lows anal y sis within the same frame work used by the pe tro
- leum in dus try.

64 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Petroleum Market Module

PMM Outputs Inputs from NEMS Exogenous Inputs Pe tro leum prod uct prices Crude oil im ports and ex ports Crude oil de mand Pe tro leum prod uct im ports and ex ports Re fin ery ac tiv ity and fuel use Eth a nol de mand and price Com bined heat and power (CHP) Nat u ral gas plant liq uids pro duc tion Pro cess ing gain Ca pac ity ad di tions Cap i tal ex pen di tures Revenues Pe tro leum prod uct de mand by sec tor Do mes tic crude oil pro duc tion World oil price In ter na tional crude oil sup ply curves In ter na tional prod uct sup ply curves In ter na tional ox y gen ates sup ply curves Nat u ral gas prices Elec tric ity prices Nat u ral glas pro duc tion Mac ro eco nomic vari ables Bio mass sup ply curves Coal prices Pro cess ing unit op er at ing pa ram e ters Pro cess ing unit ca pac i ties Prod uct spec i fi ca tions Op er at ing costs Cap i tal costs Trans mis sion and dis tri bu tion costs Fed eral and State taxes Ag ri cul tural feedstock quan ti ties and costs CHP unit op er at ing pa ram e ters CHP unit capacitiesEnergy Information Administration / The National Energy Modeling System: An Overview 2009 65 

# Petroleum Market Module

N E M S Petroleum Market Module Oil and Gas Supply Module

Natural Gas Transmission and Distribution Module 

# N E M S Exogenous

Expectations

Crude Oil Production

Crude Oil Demand

Natural Gas Prices and Production Demand Modules

Electricity Market Module

International Energy Module

Macroeconomic Activity Module Liquid Fuels Demand

Liquid Fuel Prices Electricity Prices Liquid Fuel Demands
World Oil Price Domestic Oil Production and Demand Product Imports, Exports Crude Oil and Product Supply Curves Oxygenate Supply Curves and Prices

Refinery Activity
Interest Rates, Gross Domestic Product, Deflators Refinery Fuel Use, Cogeneration Liquid Fuels Prices Processing Unit Parameters and Capacities, Product Specifications, Operating and Capital Costs, Transmission and Distribution Costs, Federal and State Taxes, Agricultural Feedstock Quantities and Parameters and Capacities

Oil Production Liquid Fuel Prices Coal Market Module Diesel Fuel Prices Renewable Fuels Module Biomass Supply Curves Costs, Cogeneration Unit Fig ure 16. Pe tro leum Mar ket Mod ule Structure66 Energy Information Administration / The National Energy Modeling System: An Overview 2009 

# Petroleum Market Module

Fig ure 17. Pe tro leum Ad min is tra tion for De fense DistrictsProd uct Cat e go ries

Prod uct cat e go ries, spec i fi ca tions and rec ipe blends mod eled in PMM in clude the fol low ing: Liquid Fuels Mod eled in PMM

Fuel Use PMM de ter mines re fin ery fuel use by re fin ing re gion for pur chased elec tric ity, nat u ral gas, dis til late fuel, re sid
- ual fuel, liq ue fied pe tro leum gas, and other pe tro leum. The fu els (nat u ral gas, pe tro leum, other gas eous fu els, and other) con sumed within the re fin ery to gen er ate elec tric ity from CHP fa cil i ties are also de ter mined. Crude Oil Cat e go ries Both do mes tic and im ported crude oils are ag gre gated into five cat e go ries as de fined by API grav ity and sul fur con tent ranges. This ag gre ga tion of crude oil types al
- lows PMM to ac count for changes in crude oil com po si
- tion over time. A com pos ite crude oil with the ap pro pri ate yields and qual i ties is de vel oped for each cat e gory by av er ag ing char ac ter is tics of for eign and do mes tic crude oil streams. Re fin ery Pro cesses The fol low ing dis tinct pro cesses are rep re sented in the PMM:

Natural Gas Plants Nat u ral gas plant liq uids (eth ane, pro pane, nor mal bu
- tane, iso bu tane, and nat u ral gas o line) pro duced from nat u ral gas pro cess ing plants are mod eled in PMM. Their pro duc tion lev els are based on the pro jected nat
- u ral gas sup ply and his tor i cal liq uids yields from var i ous nat u ral gas sources. These prod ucts move di rectly into the mar ket to meet de mand (e.g., for fuel or pet ro chem
- i cal feedstocks) or are in puts to the re fin ery. 

# Petroleum Market Module

Energy Information Administration / The National Energy Modeling System: An Overview 2009 67 Mo tor gas o line : conventional (oxygenated and non-oxygentated), reformulated, and California reformulated Jet fu els : ker o sene-based Dis til lates : kerosene, heating oil, low sulfur (LSD) and ultra-low-sulfur (ULSD) highway diesel, distillate fuel oil, and distillate fuel from various non-crude feedstocks (coal, biomass, natural gas) via the Fischer-Tropsch process (BTL, CTL, GTL) Alternative Fuel : Biofuels [including ethanol, biodiesel (methyl-ester), renewable diesel, biomass-to-liquids (BTL)], coal-to-liquids (CTL), gas-to-liquids (GTL)

. Re sid ual fu els : low sulfur and high sulfur residual fuel oil Liq ue fied pe tro leum gas (LPG) : a light-end mixture used for fuel in a wide range of sectors comprised primarily of propane Natural gas plant :ethane, propane, iso and normal butane, and pentanes plus (natural gasoline) Pet ro chem i cal feedstocks Other : as phalt and road oil, still gas, (refinery fuel) pe tro leum coke, lu bes and waxes, special naphthas 1) Crude Oil Dis til la tion a. At mo spheric Crude Unit b. Vac uum Crude Unit 2) Re sid ual Oil Up grad ing a. Coker - De layed, fluid b. Ther mal Cracker/Visbreaker c. Re sid uum Hydrocradker d. Sol vent Deasphalting 3) Crack ing a. Fluidized Cat a lytic Cracker b. Hydrocracker 4) Fi nal Prod uct Treat ing/Up grad ing a. Tra di tional Hydrotreating b. Mod ern Hydrotreating c. Alkylation d. Jet Fuel Pro duc tion e. Ben zene Sat u ra tion f. Cat a lytic Re form ing 5) Light End Treat ing a. Sat u rated Gas Plant b. Isomerization c. Dimerization/Poly mer iza tion d. C2-C5 Dehydrogenation 6) Non-Fuel Pro duc tion a. Sul fur Plant b. Meth a nol Pro duc tion c. Oxgenate Pro duc tion d. Lube and Wax Pro duc tion e. Steam/Power Gen er a tion f. Hy dro gen Pro duc tion g. Aromatics Pro duc tion 7) Spe cialty Unit Op er a tions a. Olefins to Gas o line/Die sel b. Meth a nol to Olefins 8) Mer chant Fa cil i ties a. Coal/Gas/Bio mass to Liq uids b. Nat u ral Gas Plant c. Eth a nol Pro duc tion d. Biodiesel PlantBiofuels

PMM con tains submodules which pro vide re gional sup
- plies and prices for biofuels: eth a nol (con ven
- tional/corn, ad vanced, cel lu losic) and var i ous forms of bio mass-based die sel: FAME (methyl es ter), bio
- mass-to-liq uid (Fisher-Tropsch), and re new able (“green”) die sel (hy dro ge na tion of veg e ta ble oils or fats). Eth a nol is as sumed to be blended ei ther at 10 per cent into gas o line (con ven tional or re for mu lated) or as E85. Food feedstock sup ply curves (corn, soy bean oil, etc.) are up dated to USDA base line pro jec tions; bio
- mass feedstocks are drawn from the same sup ply curves that also sup ply bio mass fuel to re new able power gen er a tion within the Re new able Fu els Mod ule of NEMS. The mer chant pro cess ing units which gen er
- ate the biofuels sup plies sum these feedstock costs with other cost in puts (e.g., cap i tal, op er at ing). A ma jor driv ing force be hind the pro duc tion of these biofuels is the Re new able Fu els Stan dard un der EISA2007. De
- tails on the mar ket pen e tra tion of the ad vanced biofuels pro duc tion ca pac ity (such as cel lu losic eth a nol and BTL) which are not yet com mer cial ized can be found in the PMM doc u men ta tion. End-Use Mark ups The lin ear pro gram ming por tion of the model pro vides unit prices of prod ucts sold in the re fin ery re gions (re fin ery gate) and in the de mand re gions (whole sale). End use mark ups are added to pro duce a re tail price for each of the Cen sus Di vi sions. The mark ups are based on an av
- er age of his tor i cal mark ups, de fined as the dif fer ence be
- tween the end-use prices by sec tor and the cor re spond ing whole sale price for that prod uct. The av er
- age is cal cu lated us ing data from 2000 to the pres ent. Be
- cause of the lack of any con sis tent trend in the his tor i cal end-use mark ups, the mark ups re main at the his tor i cal av
- er age level over the projection period. State and Fed eral taxes are also added to transporta tion fuel prices to de ter mine fi nal end-use prices. Pre vi ous tax trend anal y sis in di cates that state taxes in crease at the rate of in fla tion, while Fed eral taxes do not. In PMM, there fore state taxes are held con stant in real terms through out the pro jec tion while Fed eral taxes are felated at the rate of in fla tion. 18 Gas o line Types Mo tor ve hi cle fuel in PMM is cat e go rized into four gas o
- line blends (con ven tional, ox y gen ated con ven tional, re
- for mu lated, and Cal i for nia re for mu lated) and also E85. While fed eral law does not man date gas o line to be ox y
- gen ated, all gas o line com ply ing with the Fed eral re for
- mu lated gas o line pro gram is as sumed to con tain 10 per cent eth a nol, while con ven tional gas o line may be “clear” (no eth a nol) or used as E10. As the man date for biofuels grows un der the Re new able Fu els Stan dard, the pro por tion of con ven tional gas o line that is E10 also gen er ally grows. Cal i for nia re for mu lated mo tor gas o
- line is as sumed to con tain 5.7% eth a nol in 2009 and 10 per cent there af ter in line with its ap proval of the use of California’s Phase 3 reformulated gasoline. EIA de fines E85 as a gas o line type but is treated as a sep a rate fuel in PMM. The trans por ta tion mod ule in NEMS pro vides PMM with a flex fuel ve hi cle (FFV) de
- mand, and PMM com putes a sup ply curve for E85. This curve in cor po rates E85 in fra struc ture and sta tion costs, as well as a logit re la tion ship be tween the E85 sta tion avail abil ity and de mand of E85. In fra struc ture costs dic
- tate that the E85 sup plies emerge in the Mid west first, fol lowed by an ex pan sion to the coasts. Ul tra–Low–Sul fur Die sel By def i ni tion, Ul tra Low Sul fur Die sel (ULSD) is high
- way die sel fuel that con tains no more than 15 ppm sul
- fur at the pump. As of June 2006, 80 per cent of all high way die sel pro duced or im ported into the United States was re quired to be ULSD, while the re main ing 20 per cent con tained a max i mum of 500 parts per mil
- lion. By De cem ber 1, 2010 all high way fuel sold at the pump will be re quired to be ULSD. Ma jor as sump tions re lated to the ULSD rule are as fol lows:

• High way die sel at the re fin ery gate will con tain a max i
- mum of 7-ppm sul fur. Al though sul fur con tent is lim ited to 15 ppm at the pump, there is a gen eral consensus that re fin er ies will need to pro duce die sel be low 10 ppm sul
- fur in or der to al low for c ontamination dur ing the dis tri
- bu tion pro cess.

• De mand for high way grade die sel, both 500 and 15 p pm com bined, is as sumed to be equiv a lent to the total trans por ta tion dis til late de mand. His tor i cally, h ighway grade die sel sup plied has nearly matched to tal trans por
- ta tion dis til late sales, al though some high way grade 

# Petroleum Market Module

68 Energy Information Administration / The National Energy Modeling System: An Overview 2009 18 http://www.eia.doe.gov/oiaf/archive/aeo07/leg_reg.html.die sel has gone to non-trans portation uses such as

con struc tion and ag ri cul ture. Gas, Coal and Bio mass to Liq uids Nat u ral gas, coal, and bio mass con ver sion to liq uid fu
- els is mod eled in the PMM based on a three step pro
- cess known as in di rect liq ue fac tion. This pro cess is some times called Fischer-Tropsch (FT) liq ue fac tion af
- ter the in ven tors of the sec ond step. The liq uid fu els pro duced in clude four sep a rate prod
- ucts: FT light naph tha, FT heavy naph tha, FT ker o
- sene, and FT die sel. The FT des ig na tion is used to dis tin guish these liq uid fu els from their pe tro leum coun
- ter parts. This is nec es sary due to the dif fer ent phys i cal and chem i cal prop er ties of the FT fu els. For ex am ple, FT die sel has a typ i cal cetane rat ing of ap prox i mately 70-75 while that of pe tro leum die sel is typ i cally much lower (about 40). In ad di tion, the above pro duc tion meth ods have dif fer ing im pacts with re gard to cur rent and po ten tial leg is la tion, par tic u larly RFS and CO2.

Energy Information Administration / The National Energy Modeling System: An Overview 2009 69 

# Petroleum Market Module

# Coal Mar ket ModuleThe coal mar ket mod ule (CMM) rep re sents the min ing,

transportation, and pricing of coal, subject to end-use demand. Coal supplies are differentiated by ther mal grade, sul fur con tent, and min ing method (un der ground and sur face). CMM also determines the minimum cost pattern of coal supply to meet exogenously defined U.S. coal export demands as a part of the world coal market. Coal dis tri bu tion, from sup ply re gion to de mand re gion, is projected on a cost-minimizing ba sis. The domestic pro duction and distribution of coal is pro jected for 14 de mand regions and 14 supply regions (Figures 18 and 19). The CMM com po nents are solved si mul ta neously. The se quence of so lu tion among com po nents can be sum
- ma rized as fol lows. Coal sup ply curves are pro duced by the coal pro duc tion submodule and in put to the coal dis tri
- bu tion submodule. Given the coal supply curves, dis tri bu
- tion costs, and coal de mands, the coal dis tri bu tion submodule pro jects de liv ered coal prices. The mod ule is it er ated to con ver gence with re spect to equi lib rium prices to all de mand sec tors. The struc ture of the CMM is shown in Figure 20. Coal Production Submodule This submodule pro duces an nual coal sup ply curves, re - lat ing an nual pro duc tion to minemouth prices. The sup
- ply curves are con structed from an econo met ric anal y sis of prices as a func tion of pro duc tive ca pac ity, ca pac ity uti li za tion, pro duc tiv ity, and var i ous fac tor in put costs. A sep a rate sup ply curve is pro vided for sur face and un derground min ing for all sig nif i cant pro duc tion by coal ther mal grade (met al lur gi cal, bi tu mi nous, subbituminous and lig nite), and sul fur level in each sup
- ply re gion. Each supply curve is as signed a unique heat, sul fur, and mer cury con tent, and car bon di ox ide emis
- sions fac tor. Con struct ing curves for the coal types avail
- able in each re gion yields a to tal of 40 curves that are used as inputs to the coal distribu tion submodule. Supply curves are updated for each year in the pro jec tion pe riod. Coal sup ply curves are shared with both the EMM and the PMM. For de tailed as sump tions, please see the As sump tions to the An nual En ergy Out look up dated each year with the re lease of the AEO. Coal Distribution Submodule: Domestic Component The coal dis tri bu tion submodule is a lin ear pro gram that de ter mines the least-cost sup plies of coal for a given set of coal de mands by de mand re gion and sector, ac count
- ing for trans por ta tion costs from the different sup ply curves, heat and sul fur con tent, and ex ist ing coal sup ply con tracts. Ex ist ing sup ply con tracts be tween coal pro
- duc ers and elec tric ity gen er a tors are in cor po rated in the model as min i mum flows for sup ply curves to coal de mand re gions. De pend ing on the spe cific sce nario, coal dis tri bu tion may also be af fected by any re stric
- tions on sul fur di ox ide, mer cury, or car bon di ox ide emis sions. Coal trans por ta tion costs are sim u lated us ing inter re - gional coal trans por ta tion costs de rived by sub tracting re ported minemouth costs for each sup ply curve from re ported de liv ered costs for each de mand type in each de mand re gion. For the elec tric ity sec tor, higher trans
- por ta tion costs are as sumed for mar ket ex pan sion in cer tain sup ply and de mand re gion com bi na tions. Trans por ta tion rates are modified over time us ing econometrically based mul ti pli ers which con sid ers the im pact of chang ing pro duc tiv ity and equip ment costs. When die sel fuel prices are suf fi ciently high, a fuel sur
- charge is also added to the trans por ta tion costs. Coal Distribution Submodule: International Component The in ter na tional com po nent of the coal dis tri bu tion submodule pro jects quan ti ties of coal im ported and ex- ported from the United States. The quan ti ties are de ter
- mined within a world trade con text, based on as sumed char ac ter is tics of for eign coal sup ply and de mand. The com po nent disaggregates coal into 17 ex port re gions and 20 im port re gions, as shown inTable 13. The sup
- ply and de mand com po nents of world coal trade are

Energy Information Administration / The National Energy Modeling System: An Overview 2009 71 

# Coal Market Module

CMM Outputs Inputs from NEMS Exogenous Inputs Coal pro duc tion and dis tri bu tion Minemouth coal prices End-use coal prices U.S. coal ex ports and im ports Trans por ta tion rates Coal qual ity by source, des ti na tion, and end-use sec tor World coal flows Coal de mand In ter est rates Price in di ces and de fla tors Die sel fuel prices Elec tric ity prices Base year pro duc tion, pro duc tive ca pac ity, ca pac ity uti li za tion, prices, and coal qual ity pa ram e ters Con tract quan ti ties La bor pro duc tiv ity La bor costs Do mes tic trans por ta tion costs In ter na tional trans por ta tion costs In ter na tional sup ply curves In ter na tional coal im port demandsseg mented into two sep a rate mar kets: 1) cok ing coal,

which is used for the pro duc tion of coke for the steelmaking pro cess; and 2) steam coal, which is pri
- mar ily con sumed in the elec tric ity and in dus trial sec tors. The in ter na tional com po nent is solved as part of the lin ear pro gram that optimizes U.S. coal sup ply. It de ter mines world coal trade dis tri bu tion by min i miz ing over all costs for coal, sub ject to coal sup ply prices in the United States and other coal ex port ing re gions plus trans por
- ta tion costs. The com po nent also in cor po rates sup ply di ver sity con straints that re flect the ob served ten dency of coal-im port ing coun tries to avoid ex ces sive de pend
- ence upon one source of sup ply, even at a some what higher cost

.

72 Energy Information Administration / The National Energy Modeling System: An Overview 20099 

# Coal Market Module
Fig ure 18. Coal Mar ket Mod ule De mand Regions

# Coal Market Module

Energy Information Administration / The National Energy Modeling System: An Overview 2009 73 Fig ure 19. Coal Mar ket Mod ule Sup ply Regions74 Energy Information Administration / The National Energy Modeling System: An Overview 20099 

# Coal Market Module

Coal Export Regions Coal Import Regions U.S. East Coast U.S. East Coast U.S. Gulf Coast U.S. Gulf Coast U.S. Southwest and West U.S. Northern Interior U.S. Northern Interior U.S. Noncontiguous U.S. Noncontiguous Eastern Canada Australia Interior Canada Western Canada Scandinavia Interior Canada United Kingdom and Ireland Southern Africa Germany and Austria Poland Other Northwestern Europe Eurasia-exports to Europe Iberia Eurasia-exports to Asia Italy China Mediterranean and Eastern Europe Colombia Mexico Indonesia South America Venezuela Japan Vietnam East Asia China and Hong Kong ASEAN (Association of Southeast Asian Nations) India and South Asia Ta ble 13. Coal Ex port Component

# Coal Market Module

Energy Information Administration / The National Energy Modeling System: An Overview 2009 75 Petroleum Market Module

Macroeconomic Activity Module Demand Modules

Electricity Market Module Coal Distribution Submodule

Coal Production Submodule 

### Coal Market Module

International Component

Coal Supply Curves Coal

Production and Distribution Coal Prices Coal Demand Coal Prices Coal Demand

Diesel Fuel Prices Export

Demand Minemouth

Coal Prices

N E M S Exogenous Coal Export Demands International Transportation Costs International Supply Curves

Exogenous Domestic Transportation Costs Contract Quantities Emissions Limits

Exogenous Base Year Production Capacity Base Year Capacity Utilization Labor Productivity Labor Costs Labor Cost Escalators Electricity Prices

Coal Prices Coal for Liquids Derived

Interest Rates, Price Indices, and Deflators Coal Production and Prices Fig ure 20. Coal Mar ket Mod ule Structure

# Appen dixThe Na tional En ergy Mod el ing Sys tem is docu mented

in a series of model documentation reports, available on the EIA Web site at http://tonto.eia.doe.gov/re ports/ reports_kindD.asp?type=model doc u men ta tion or by contacting the National Energy Information Center (202/586-8800). En ergy In for ma tion Ad min is tra tion, In te grat ing Mod
- ule of the Na tional En ergy Mod el ing Sys tem: Model Doc u men ta tionDOE/EIA-M057(2009) (Washington, DC, May 2009). En ergy In for ma tion Ad min is tra tion, Model Documentation Re port: Mac ro eco nomic Ac tiv ity Mod ule (MAM) of the Na tional En ergy Mod el ing Sys tem, DOE/EIA-M065(2009) (Wash ing ton, DC, Jan u ary 2009). En ergy In for ma tion Ad min is tra tion, NEMS In ter na tional En ergy Mod ule: Model Doc u men ta tion Re port, DOE/EIA-M071(2007) (Wash ing ton, DC, May 2007). En ergy In for ma tion Ad min is tra tion, Model Documentation Re port: Res i den tial Sec tor De mand Mod ule of the Na tional En ergy Mod el ing Sys tem , DOE/EIA-M067 (2009) (Wash ing ton, DC, May 2009). En ergy In for ma tion Ad min is tra tion, Model Documentation Re port: Com mer cial Sec tor De mand Module of the Na tional En ergy Mod el ing Sys tem , DOE/EIA-M066(2009) (Wash ing ton, DC, May 2009). En ergy In for ma tion Ad min is tra tion, Model Documentation Re port: In dus trial Sec tor De mand Mod ule of the Na tional En ergy Mod el ing Sys tem , DOE/EIA-M064(2009) (Wash ing ton, DC, May 2009). En ergy In for ma tion Ad min is tra tion, Trans por ta tion Sec tor Mod ule of the Na tional En ergy Mod el ing Sys tem: Model Doc u men ta tion Re port , DOE/EIA- M070(2009) (Wash
- ing ton, DC, June 2009). En ergy In for ma tion Ad min is tra tion, The Elec tric ity Mar ket Mod ule of the Na tional En ergy Mod el ing System: Model Doc u men ta tion Re port , DOE/EIA- M068(2009) (Wash
- ing ton, DC, May 2009). En ergy In for ma tion Ad min is tra tion, Doc u men ta tion of the Oil and Gas Sup ply Mod ule (OGSM) , DOE/ EIA-M063(2009) (Wash ing ton, DC, July 2009). En ergy In for ma tion Ad min is tra tion, Model Documentation: Nat u ral Gas Trans mis sion and Distribution Model of the Na tional En ergy Mod el ing Sys tem , DOE/EIA-M062(2009) (Wash ing ton, DC, June 2009). En ergy In for ma tion Ad min is tra tion, Model Documentation: Coal Mar ket Mod ule of the Na tional Energy Mod el ing Sys tem , DOE/EIA-M060(2009) (Wash ing ton, DC, June 2009). En ergy In for ma tion Ad min is tra tion, Model Documentation: Re new able Fu els Mod ule of the Na tional En ergy Mod el ing Sys tem , DOE/EIA-M069(2009) (Wash ing ton, DC, July 2009). En ergy In for ma tion Ad min is tra tion, An nual En ergy Re
- view 2008 , DOE/EIA-0384(2008) (Wash ing ton, DC, June 2009). En ergy In for ma tion Ad min is tra tion, Model Doc u men ta
- tion: Pe tro leum Mar ket Model of the Na tional En ergy Mod el ing Sys tem , DOE/EIA-M059(20009) (Wash ing
- ton, DC, Au gust 2009).

Energy Information Administration / The National Energiy Modeling System: An Overview 2009 77 

## Appendix Bibliography