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Jim McMahon

JEMcMahon@lbl.gov 

### Ernest Orlando Lawrence Berkeley National Laboratory

USDOE Public Workshop March 11, 1997 

# Manufacturer ImpactAnalysis: II .J 

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Jim McMahon JEMcMahon @Ibl.gov 

### Ernest Orlando Lawrence Berkeley National Laboratory USDOE Public Workshop March 11, 1997Projected shipments of appliances and lighting equipment

are necessary inputs to the manufacturer impact analysis



### • A variety of approaches are possible - Constant shipments at current (or projected) level - Extrapolation of historical trend - More detailed forecasting models ® Forecasting models can account for expectations about - Demographics - Economics and market behavior - Engineering 

### - Other policies and programs

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# ofForecasting Models
• Projected shipments of appliances and lighting equipment are necessary inputs to the manufacturer impact analysis • A variety of approaches are possible

- Constant shipments at current (or projected) level

- Extrapolation ofhistorical trend

- More detailed forecasting models • Forecasting models can accountfor expectations about

- Demographics

- Economics and market behavior Engineering

- Other policies and programs

### • Replacement of existing equipment

• New construction: number of households, or floor area of commercial buildings (by type) 

### • Competition among fuels or technologies
• Other market and regulatory factors information/education (e.g., EPA Green Lights) 

### - incentives (e.g., utility loan or rebate programs) - building codes 

### • Price of appliances or equipment

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# rmlnes**sJJlpm.n1s~" ~**  • Replacement of existing equipment • New construction: number of households, or floor area of commercial buildings (by type) • Competition among fuels ortechnologies • Other market and regulatory factors

- information/education (e.g., EPA Green Lights)

- incentives (e.g., utility loan or rebate programs)

- building codes 

### • Price of appliances or equipment rOfJrarn1, 

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• Stock Turnover- historical shipments and a lifetime (or probability of retirement as a function of age) are used to estimate numbers of appliances retiring each year ® Fuel Choice - future consumer decisions are simulated based upon parameters consistent with past behaviors, and projections of driving factors (equipment and energy prices, income) ® Technology Choice - simulated using explicit lists of discrete technologies, each having a price and energy performance. In standards cases, the lists are truncated. ® Usage Behavior - changes in behavior in response to changes in operating expense are simulated, where appropriate (e.g., space conditioning). 

### N"A 

# What· forecasting modelsdo
• Stock Turnover- historical shipments and a lifetime (or probability of retirement as a function of age) are used to estimate numbers of appliances retiring each year • Fuel Choice - future consumer decisions are simulated based upon parameters consistentwith past behaviors, and projections of driving factors (equipment and energy prices, income) • Technology Choice - simulated using explicit lists of discretetechnologies, each having a price and energy performance. In standards cases, the lists**~re** truncated. • Usage Behavior-**chang~s** in behavior in response to changes in operating expense are simulated, where appropriate (e.g., space conditioning).

### • RESIDENTIAL

- EIA National Energy Modeling System (NEMS) - LBNL Residential Energy Model (REM) - EPRI Residential End-use Energy Planning System (REEPS) - LBNL spreadsheet (under development) 

### • COMMERCIAL - EIA National Energy Modeling System (NEMS) - EPRI commercial sector end-use planning system (COMMEND) 

### - LBNL spreadsheet (under development) 

### • RESIDENTIAL

- EIA National Energy Modeling System (NEMS)

- LBNL Residential Energy Model (REM) -' ,EPRI Residential End-use Energy Planning System (REEPS)

- LBNL spreadsheet (under development) 

### • COMMERCIAL

- EIA National Energy Modeling System (NEMS)

- EPRI commercial sector end-use planning system (COMMEND)

- LBNL spreadsheet (under development) 

### rEtrn

### • REM (18 years) USDOE Codes and Standards

(public domain) • REEPS (15 years) EPRI and member utilities (private) • COMMEND (12 years) EPRI and utilities (private) • NEMS (4 years) EIA Annual Energy Outlook 

### (public) Spreadsheet (under development) (public) • REM (18 years) USDOE Codes and Standards (public domain) • REEPS (15 years) EPRI and member utilities (private) • COMMEND (12 years) EPRI and utilities (private) • NEMS (4 years) EIA Annual Energy Outlook (public) . • Spreadsheet (under development)(public)

!! IS rarn

### • REM -workstation (FORTRAN)

- personal computer version possible 

### BEEPS, COMMEND - personal computer • HEMS - 

### mainframe with specific math package - personal computer version no longer

### ,supported 

### • spreadsheet - personal computer • REM - workstation (FORTRAN)

- personal computerversion possible 

### • REEPS, COMMEND - personal computer 

### • NEMS - mainframe with specific math package

- personal computerversion no longersupported 

### • spreadsheet - personal computer

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## R

• Make models as simple as possible • Make copies of models more accessible on World Wide Web through USDOE or contractor 

### • Develop detailed documentation • conduct training Workshops central location, on-site, or videoconference 

# Id asforeliminating "black. 

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• Make models as simple as possible • Make copies of models more accessible

- on World Wide Web

- through USDOE orcontractor 

### • Develop.detailed documentation • Conducttraining workshops

- central location, on-site, orvideoconference

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## n

• Identify key uncertainties • Estimate ranges rather than point values • Express output as ranges • Conduct scenario ("what-if") analysis • Identify key uncertainties • Estimate ranges rather than pointvalues • Express output as ranges • Conduct scenario ("what-if") .analysis