### From: Higgins, Cortney [mailto:Cortney_Higgins@omb.eop.gov] Sent: Friday, April 04, 2014 7:59 PM To: Wayland, Robertj Subject: Re: Chapters 1, 2 and 6 from GHG Abatement Measures TSD

Thanks!
Have a good weekend.
Cortney

From: Wayland, Robertj [mailto:Wayland.Robertj@epa.gov] Sent: Friday, April 04, 2014 07:30 PM Eastern Standard Time To: Higgins, Cortney Cc: Culligan, Kevin <Culligan.Kevin@epa.gov>; Tsirigotis, Peter <Tsirigotis.Peter@epa.gov>; Srivastava , Ravi <Srivastava.Ravi@epa.gov> Subject: Chapters 1, 2 and 6 from GHG Abatement Measures TSD

Cortney -
Attached please fine Chapters 1, 2 and 6 from the GHG Abatement Measures TSD. Chapter 7 needs a bit more editing which we'll take care of over the weekend. Please confirm receipt of these 3 chapters given the email issues we discussed earlier! :-)

thanx!

bob
Robert J. Wayland, Ph.D. Leader, Energy Strategies Group U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Sector Policies and Programs Division Mail Code D243-01 Research Triangle Park, North Carolina 27709
Office: (919) 541-1045 Cell: (919) 306-2290 Fax: (919) 541-5450 Email: wayland.robertj@epa.gov

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## Chapter 1: Introduction

CAA section 111(d) requires that state plans must establish st andards of performance that reflect the degree of emission limitation achievable through the application of the best system of
emission reduction (BSER) that, taking into account the cost of achie ving such reductions and any non-air quality health and environmental imp act and energy requirements, the Administrator determines has been adequately demonstrated. Under CAA section 111(a)(1) and (d), the EPA is
authorized to determine the BSER and to calcula te the amount of emissi on reduction achievable through applying the BSER.

As a first step towards determination of BSER, the EPA recognized that, in general, reductions in carbon dioxide (CO 2 

### ) emissions from individual exis ting electric generating units (EGUs) can be achieved by implementing either of two basic approaches: (1) making emission rate improvements at affected EGUs (e.g., by im proving heat rates or switching to lower carbon fuels), and/or (2) reducing u tilization of greenhouse gas (GHG )-emitting EGUs (e.g., by reducing the overall demand for electricity or by shif ting dispatch from higher-GHG-emitting EGUs to lower-GHG-emitting and non-emitting units). Accord ingly, to determine BSER for reducing GHG emissions at affected units, the EPA eval uated numerous GHG abatement measures that utilize the above approaches. In its evaluation, th e EPA considered only those measures that have been adequately demonstrated to reduce CO 2 

### emissions from fossil fuel-fired EGUs. These measures included: heat rate improvements at individual EGUs, switching to lower carbon fuels at individual EGUs, carbon capture and sequestrati on at individual EGUs, shifting dispatch from higher-GHG-emitting EGUs to lower-GHG-emitti ng and non-emitting units , and reducing the overall demand for electricity via improve ments in demand-side energy efficiency.

Based on its evaluation of the above GHG abat ement measures, the EPA identified four categories of demonstrated measures, or “build ing blocks,” that are technically viable and broadly applicable, and can provide cost-effective reductions in CO 2 

### emissions from individual existing EGUs. These building blocks include:

1. Lowering the carbon intensity of generation at individual affect ed EGUs (e.g., through heat rate improvements);

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2 2. Reducing emissions of the most carbon-intensiv e affected EGUs to the extent that this can be accomplished cost-effectively by shif ting generation to less carbon-intensive existing fossil fuel-fired EGUs, including NGCC units that are under construction;

3. Reducing emissions of carbon-emitting EGUs to the extent that this can beaccomplished cost-effectively by expanding the amount of new, lower (or no) carbonintensity generation; and,

4. Reducing emissions of carbon-emitting EGUs to the extent that this can be accomplished cost-effectively by increas ing demand-side energy efficiency.

The EPA believes that for purposes of CAA section 111(d), as applied to the power sector, the BSER encompasses a ll four building blocks. The app lication of all four building
blocks as BSER is consistent with current trends in the electric power sect or and with strategies that companies and states are already taking to reduce GHG emissions. Also, the application of all four building blocks as BS ER supports achieving cost-effectiv e, and technically feasible
reductions of CO 2 

### . The subsequent chapters in this technical support document describe EPA’s evaluation of all adequately demonstrated GHG abatement meas ures. While evaluating each measure, the EPA considered its technical feasibility, applicability and use, application leve l appropriate for BSER,
and cost effectiveness associated with reducing GHG emissions at EGUs.

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## Chapter 2: Heat Rate Improveme nt at Existing Coal-fired EGUs

Introduction Based on the range of operating efficiencies for existing coal-fir ed electric generating units (EGUs), it can be presumed that EGUs are ge nerally less efficient at converting fuel into electricity than is technically and economically possible. For example, the difference in operating efficiency of EGUs with similar design characte ristics and the year to year variability in individual EGU efficiency indicates that there is potential for broadly applicable efficiency improvements through cost-effective operational and maintenance practices. These improved efficiencies would result in corresponding reductions in greenhouse gas emissions. This chapter presents an overview of exis ting coal-fired EGUs, design factors that influence efficiency, technologies to improve efficiency, previ ous studies estimating potential efficiency improvements, the proposed EPA appro ach to calculate efficiency improvements, and the estimated capital costs of those improvements. Overview of U.S. Existing Coal-F ired Electric Generating Units Coal in the United States and is predominat ely used for electric power generation. Most
coal-fired EGUs in the United States burn either bituminous or subbituminous coals. The largest
sources of bituminous coals burned in coal-f ired EGUs are mines in regions along the Appalachian Mountains and in southern Illinois, western Ke ntucky and Indiana. Additional bituminous coals are supplied from mines in Utah and Colorado. The vast majority of subbituminous coals are supplied from mines in Wyoming and Montana, with many coal-fired EGUs burning subbituminous coals from the Powder River Basin (PRB) region in Wyoming. In general, the burning of lignite by U. S. electric utilities is limited to coal-fired EGUs that are located near the mines that supply the lignite in Texas, Louisiana, Mississippi, Montana, and North Dakota. At a few power plant locations in the Eastern U.S., recovered anthracite coal or coal refuse is burned in limited quantities. Existing coal-fired EGUs in the U.S. electric utility fleet use one of five basic coal combustion configurations: (1) pu lverized coal (PC) combusti on, (2) fluidized-bed combustion (FBC), (3) gasified coal combustion, (4) cyclone furnace combustion, or (5) stoker-fired coal combustion. Table 2-1 presents a summary of the operating characteristics of each of these coal combustion configurations.

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2 Table 2-1. Characteristics of coal-firin g configurations used for U.S. EGUs Coal-firing Configuration Coal Combustion Process Description Distinctive Design/Operating Characteristics

Pulverized Coal Combustion Coal is ground to a fine powder that is pneumatically fed to a burner where it is mixed with combustion air and then blown into the furnace. The pulverized-coal particles burn in suspension in the furnace. Unburned and partially burned coal particles are carried off with the flue gas. Wall-fired An array of burners fire into the furnace horizontally, and can be positioned on one wall or opposing walls depending on furnace design.

Tangential-fired

(Corner-fired) Multiple burners are positioned in opposite corners of the furnace producing a fireball that moves in a cyclonic motion and expands to fill the furnace.

Fluidized-bed Combustion (FBC) Coal is crushed into fine particles. The coal particles are suspended in a fluidized bed by upward-blowing jets of air creating a turbulent mixing of combustion air with the coal particles. Typically, the coal is mixed with a sorbent such as limestone (for SO 2 emission control). FBC can be designed for combustion within the bed to occur at atmospheric or elevated pressures. FBC operating temperatures are in the range of 1,500 to 1,650  F (800 to 900 o C). Bubbling fluidized bed (BFB) Operates at relatively low gas stream velocities and with coarse-bed size particles. Air in excess of that required to fluidize the bed passes through the bed in form of bubbles.

Circulating fluidized bed (CFB) Operates at higher gas stream velocities and with finer-bed size particles. No defined bed surface. Must use high-volume, hot cyclone separators to recirculate entrained solid particles in flue gas to maintain the bed and achieve high combustion efficiency.

Integrated Coal

Gasification Combined Cycle (IGCC) Synthetic combustible gas (“syngas”) derived from an on-site coal gasification process is burned in a combustion turbine. The hot exhaust gases from the combustion turbine pass through a heat recovery steam generator to produce steam for driving a steam turbine/generator unit. Coal gasification units are unique among coal-firing configurations because a gase ous fuel (synfuel or syngas) is burned instead of solid coal because the combustion and power generation process and combines the Rankine and Brayton thermodynamic cycles as is the case for a combined cycle power plant.

Cyclone Furnace Combustion Coal is crushed into small pieces and fed through a burner into the cyclone furnace. A portion of the combustion air enters the burner tangentially creating a whirling motion to the incoming coal. Designed to burn coals with low-ash fusion temperatures that are difficult to burn in PC boilers. The majority of the ash is retained in the form of a molten slag.

Stoker-fired Coal Combustion Coal is crushed into large lumps and burned in a fuel bed on a moving, vibrating, or stationary grate. Coal is fed to the grate by a mechanical device called a “stoker.” One of three types of stoker mechanisms can be used that ether feed the coal by pushing, dropping, or flipping coal unto the grate.



### The three technologies currently used for ne w coal-fired power plants are pulverized coal, fluidized bed (FBC), and integrated coal gasification combined cycle (IGCC). Pulverized coal combustion involves pulverizing the coal into a fine powder, which allows the coal to be burned more easily and efficiently. This is the co al-firing configuration predominately used at

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3 existing EGUs, and is the most frequently select ed technology for new coal-fired EGU projects. However, FBC EGUs are becoming more prevalent si nce they have a greater fuel flexibility. The most recent coal technology combustion develo pment involves the integration of coal gasification technologies with the combined cycle electric generati on process. The efficiency of an IGCC power plant is comparable to the latest advanced PC-fired a nd FBC EGU designs using supercritical steam cycles. The advantages of using IGCC technology can include greater fuel flexibility (e.g., capability to use a wider variety of coal ranks), potential improved control of PM, SO 2 

### emissions, and other air poll utants, the need for fewer post-combustion control devices (e.g., almost all of the sulfur a nd ash in the coal can be remove d once the fuel is gasified and prior to combustion), generation of less soli d waste, and reduced water consumption. Older combustion technologies, namely cyclone furnaces and stoker-fired coal combustion, have been replaced at new coal-fired EGUs by more efficient methods that provide superior coal combustion effici ency and other advantages. Howe ver, a few remaining old stokerfired EGUs and cyclone furnaces still remain in se rvice for a small number of existing EGUs in the U.S. electric utility market.
Influence of Heat Rate on Coal-Fired EGU CO 2 

### Emission Rate Heat rate is a common way to measure EGU effi ciency. As the efficiency of a coal-fired EGU is increased, less coal is burned per kilo watt-hour (kWh) generated by the EGU resulting in a corresponding decrease in CO 2 

### and other air emissions. Heat rate is expressed as the number of British thermal units (Btu) or kilojoules (kJ) required to generate a kilowatt-hour (kWh) of electricity. Lower heat rates are associated with more efficient coal-fired EGUs. The electric energy output for an EGU can be expressed as either as “gross output” or “net output.” The gross output of an EGU is the total amount of electricity generated at the generator terminal. The net output of an EGU is the gross output minus the total amount of auxiliary (or parasitic) electri city used to operate the EGU (e.g., electricity to power fuel handling equipment, pumps, fans, pollution contro l equipment, and other on-site electricity needs), and thus is a measure of the electricity de livered to the transmission grid for distribution
and sale to customers. Some EGUs also produce part of their useful output in the form of useful thermal output (e.g., steam for heating purposes). These types of facilities are called combined heat and power, or CHP, facilities. A variety of factors must be considered when comparing the effectiveness of heat rate improvement technologies to increase the effici ency of a given coal-fired EGU. The actual

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4 overall efficiency that a given coal-fired EGU achieves is determined by the interaction of a combination of site-specific factors that impact efficiency to varying de grees. Examples of the factors affecting EGU efficiency at a given facility include:

 EGU thermodynamic cycle – EGU efficiency can be si gnificant improved by using a supercritical or ultra-su percritical steam cycle. Supercriti cal and ultra-supercritical boilers operate above the critical point of wa ter (approximately 374°C (705°F) and 22.1 MPa (3,210 psia)). As a general guideline, the therma l design efficiencies for subcritical EGUs are in the range of 35% to 37%, supercritical EGUs are in the range of 39% to 40%, and ultra-supercritical EGUs in the range of 42% to 45%. However, actual operating efficiencies are lower than design efficiencies . The majority of existing PC-fired EGUs in
the U.S. electric fleet use subcritical boilers

 EGU coal rank and quality – EGUs burning higher quality coals (e.g., bituminous) tend
to be more efficient than EGUs bur ning lower quality co als (e.g., lignite).

 EGU plant size –EGU efficiency generally increase s with size because the boiler and steam turbine losses are lower for larger e quipment compared to smaller equipment. However, as equipment size increases the diffe rences in these losses start to taper off.

 EGU pollution control systems – The electric power consum ed by air pollution control equipment reduces the overall efficiency of the EGU.

 EGU operating and maintenance practices – The specific practices used by an individual electric utility company for combustion optim ization, equipment maintenance, etc. can affect EGU efficiency.

 EGU cooling system – The temperature of the cooli ng water entering the condenser can have impacts on steam turbine performance. Once-through cooling systems can have an efficiency advantage over recirculating coo ling systems (e.g., cooling towers). However, once-though cooling systems typically have larg er water related ecological concerns than recirculating cooling systems.

 EGU geographic location and ambient conditions – The elevation and seasonal ambient temperatures at the facility site poten tially may have a measureable impact on EGU efficiency. At higher elevatio ns, air pressure is lower a nd less oxygen is available for combustion per unit volume of ambient air th an at lower elevations. Cooler ambient temperatures theoretically c ould increase the overall EGU efficiency by increasing the

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5 draft pressure of the boiler flue gases a nd the condenser vacuum, and by increasing the efficiency of a condenser r ecirculating coo ling system.

 EGU load generation flexibility requirements – Operating an EGU as a baseload unit is more efficient than operating an EGU as a load cycling unit to respond to fluctuations in customer electricity demand.

 EGU equipment manufacturers – The efficiency specifications of major EGU components such as boilers, turbines, and el ectrical generators provided by equipment manufacturers can affect EGU efficiency.

 EGU plant components – EGUs using the optimum numberof feedwater heaters, highefficiency electric motors, variable speed driv es, better materials for heat exchangers, etc.
tend to be more efficient. Technologies to Improve Existi ng Coal-Fired EGU Heat Rate
A number of studies have been conducted involving literature reviews of published articles and technical papers identifying potential efficiency improvement techniques applicable to existing coal-fired EGUs. 1 

### For example, a summary of the findings from one study conducted by the Department of Energy’s (DOE) Nati onal Energy Technology Laboratory (NETL) is presented in Table 2-2. The efficiency percentage s were converted to a co mmon basis so that all of the data can be compared. All of the improve ment technologies presented in Table 2-2 cannot necessarily be implemented at every existing coal-f ired EGU facility in the U.S. electric utility fleet. The existing EGU design configuration and other site-specific factors may prevent the technical feasibility of using a given technology. Typically, these studies share as a common basis the estimated potential efficiency improvement percentages and costs from the engi neering study originally completed by Sargent and Lundy in 2009 titled “Coal-Fired Power Plant H eat Rate Reductions.” It describes numerous well known and technically proven methods to impr ove efficiency of coal-fired EGUs. The study lists possible efficiency improvements in the boiler, turbine, flue gas system, air pollution control equipment and the water treatment system. Each of these main areas are expanded upon below.
Boiler The systems to focus on for improving heat input within the boiler area include the materials handling, combustion system, boiler contro l system, sootblowers a nd the air heaters.

1 See HRI Partial Bibliography at the end of this chapter.

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6 Materials Handling The coal handling portion of materials handling typically requires about 0.07% of the gross electrical output of a pow er plant. Depending on the state of the motors and drives, replacing them with energy-effi cient motors and variable freq uency drives (VFDs) can reduce the auxiliary power requirements. The VFDs also limit the stress and strain on the other equipment. Coal pulverizers can be upgraded to provide more consistent si ze and finer coal particles. The fine particles improve combustion efficiency, consequently reducing fuel cost and heat rate. The costs for changes to the pulverizer system ar e significant, and histori cally, the projects have improved the heat rate justifiably only when the existing equipment has degraded. The bottom ash handling system may be a s ource for heat rate improvement. Switching from a water-sluicing bottom ash system to a dry drag chain system can reduce the auxiliary requirements and reduce the amount of water to the water treatment plant. The typical power requirements are about 0.1% of the plant’s gross output. Economizer The replacement of the economizer can lead substantial heat rate improvements around 50-100 Btu/kWh, but is large capital investment (~$2-8M). Due to this high cost, economizers upgrades are not generally performed unless the existing equipment has degraded or a replacement is necessary due to the installation of new control equipment. Boiler Control System The boiler control system has a large impact on the heat ra te of the unit. The process control capabilities can control a nd evaluate many aspects of th e plant’s operations. Commonly
referred to as the Neural Netw ork (NN), computer models are able to control the plant’s processes by predicting performance during stat ic and dynamic changes. Many vendors offer NN systems to improve the overall efficien cy. NN systems are typically around $550,000-$750,000 and offer heat rate reductions up to 150 Btu/kWh.
Sootblowers Intelligent sootblowers (ISB) may be installe d to improve system efficiency. The ISB system monitors the furnace exhaust gas temperat ures and steam temperatures. Other readings may be incorporated into the ISB system whic h also communicates with the boiler control system. This system uses real-time data to identify which areas need sootblowing. Boiler

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7 efficiency improvements have ranges fr om 0.3%-1.5% with capital costs around $300,000- $500,000 and $50,000/year for fixed opera ting and maintenance costs.
Air Heaters Air heaters operate to transfer heat betw een the incoming pre-combustion air and the effluent flue gas. These systems are critical to maintain an efficient power plant. In order to maintain these systems to operate most efficientl y, air heater leakages must be maintained below 6% of incoming air flow. Most leakage is due to the pre-combustion air leaking across the rotating section and leavi ng with the flue gas. This increa ses the flue gas volume going through
the forced draft and induced draft fans to the emissions controls and avoids capturing the heat transferred between the flue gas and pre-combus tion gas. The increased volume requires more power to pump more flue gas. Additionally, impr ovements to seals on the air heaters also reduce the leakages. Improvements to reduce air heater a nd duct leakages generally reduces the heat rate by 10-40 Btu/kWh with capital costs between $0.3-1.2M. A second method to improve the heat rate is to lower the air heater outlet temperature by controlling the acid dew point. Typi cally the air heater outlet is maintained at 20-30°F above the sulfuric acid dew point to prev ent corrosion of cold-e nd baskets. Sorbent injections such as Trona or hydrated lime can be used to lower the dew point. Depending on the sizing of the air heater, the air heater may need to be modified in order to optimize the lower outlet temperature. Generally, a 40°F reduction in the air heater outle t results in 1% efficiency improvement. These systems are costly and depend on whether the air heater is adequate, n eeds modifications or needs a complete replacement. The capital costs can range from $1.5-18M for heat rate
reductions of 50-120 Btu/kWh.
Turbine The systems within the turbine area for whic h to focus heat rate improvements are the turbine, the feedwater heaters, the condenser, and the turbin e drive and motor-driven feed

pumps. Turbine The performance and longevity of turbines is constantly increasi ng with advances in technology. Most turbines in the industry are maintained so that the efficiency improvements are 1-3%; however, some extremely degraded turb ines may benefit up to 10% with a turbine overhaul. The capital costs for these projects ra nges from $2-25M with heat rate reductions of
100-300 Btu/kWh.

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8 Feedwater Heaters The feedwater heaters are heat exchangers to heat the boiler feedwa ter by extracting heat from the steam leaving the turbine section. The efficiency can be increased by improving heat
transfer surface area. This entail s adding heat exchange surfaces to the existing heaters or adding
additional heaters. The costs relativ e to the heat rate improvement associated with these projects typically prohibit the advancement of the project unless the feedwater he aters are in need of repair.
Condenser To obtain the most efficiency from the c ondenser section, the most effective operation
would have the steam from the turbine to reach the lowest temperature possible before entering
the condenser. This allows for th e turbine to extract as much en ergy from the steam as possible. Condensers are subject to fouling and plugging which directly impact the heat transfer rates and water quality. To improve water qua lity, closed cooling water system s provide better control of the water quality and tube cleaning can be perf ormed. Heat rate reductions observed from the condenser upgrades and maintenances are 30- 70 Btu/kWh with annual fixed costs of $30,000- $80,000. Boiler Feed Pumps Boiler feed pumps require a large amount of auxiliary power to pump massive amounts of boiler feedwater through the heaters and boiler. Due to the high use of these pumps, maintenance is extremely important to ensure reli ability and the most efficient operation. As the pumps wear and operate less e fficiently, a pump overhaul may be required. The overhaul can reduce the heat rate by 25-50 Btu/ kWh with capital costs around $250,000-$800,000. Flue Gas System Two aspects of the flue gas system that offer potential improvements to the plant efficiency are to improve the forced draft (F D) and induced draft (ID) fan efficiencies and implementation of VFDs.
ID Fans One of the most important features in the fans is being able to control the flue gas flow. Many fans have dampers, which are the least effective and efficient option. There are many methods, such as variable inlet vanes (VIV), VFD, and variable pitch blades (VPB), available to control the flue gas flow allowing highly e fficient fan performance. These upgrades or replacements provide a heat rate reduction of 10-50 Btu/kWh and cost between $6-$16M.

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9 VFD It is apparent with the control that a VFD o ffers, the plant is able to reduce the auxiliary load immensely. Considering upgrad ing all drives, the capital costs are $6-16M with heat rate
reductions between 10-150 Btu/kWh. Emission Control Technologies With the passage of environmental regulations, additional emission control devices have been and must be implemented in the power plan t. These systems typically require large amounts of auxiliary power with their benefit being improved air quality. Even small upgrades can decrease the power requirements significantly wh ile at least maintaining the same level of
emissions reduction. The three tech nologies discussed are the flue gas desulfurization (FGD), the electrostatic precipitator (ESP), and the sele ctive catalytic reduction (SCR) systems.
FGD Coal-fired power plants contain many vari ances between their FGD systems. A few common technology improvements are discussed furt her in this section. Older units typically
contained a venturi throat that in creased the velocity of the fluid, but resulted in a large pressure drop and greater power to operate the ID fans. To improve this operation, a co-current spray tower quencher may replace the unit. The capital co st is about $2.5M with heat rate reductions
around 13 Btu/kWh. Another technology upgrade affects the vanes and distribution pl ate into an absorber. The improvement of the gas flow coming into cont act with the absorber sorbent increases SO 2 

### capture, reduces maintenance due to erosion, and reduces the amount of energy required from the ID fan. Turning vanes and a perforated gas dist ribution plate improve ga s distribution. The cost of the vanes is around $250,000 with heat rate reductions of 1-2 Btu/kWh. In a wet FGD multiple spray levels are installed to deliver the limestone slurry. If a power plant is operating with SO 2 

### levels below its permit limit, turning off one spray level will reduce the auxiliary power necessary. If this is possible, a unit heat rate reduction of 16 Btu/kWh may be
available.
ESP The best operation for an ESP involves maintaining the maximum applied voltage, but below the level in which spark-over occurs. ESP energy management system (EMS) upgrades often help improve the ESP performance by main taining the optimal performance and lowering

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10 power consumption. The installation for this t echnology can be from minimal to $0.8M and can lower heat rate by 5 Btu/kWh.
SCR For the last 15 years, SCR systems have been in use to reduce NO X 

### emissions from power plants. Extensive modeling was performe d to achieve the necessary reduction with minimum ammonia slip. The results showed that reducing pressure drop and using secondary air as dilution for the ammonia vaporizer can reduce the auxiliary power necessary. The heat rate reduction is 0-10 Btu/kWh and capital costs betw een $0.5-$2M with fixed and variable costs up to $100,000 each. Water Treatment System The water treatment system heat rate im provements can occur for the boiler water treatment and the cooling tower improvements. Th e boiler water is one of the most important aspects of the power plant. The quality of the water plays a huge impact on the scale buildup on the boiler tubes, which reduces the heat transfer in the tubes or can cause tube failures. Proper use of chemicals to maintain pure water is key. Also, high-quality water can reduce the blowdowns required, which allows for more steam in the turbine cycle. If the water is not properly maintained, heat transfer may be reduced up to 10%. Similar to the boiler water, the cooling towe rs are also affected by the water quality. Fouling and scaling remain issues for heat transf er and purity of the water. By maintaining the cooling water system efficiently, the overall wate r quality is improved, whic h branches into other aspects already mentioned.DRAFT April 4, 201411Table 2-2. Existing coal-fired EGU efficiency improvements reported for actual efficiency improvement projectsEfficiencyImprovementTechnologyDescriptionReportedEfficiencyIncreaseaCombustionControlOptimizationCombustion controls adjust coal and air flow to optimize steam production for the steam turbine/generator set.However, combustion control for a coal-fired EGU is complex and impacts a number of important operatingparameters including combustion efficiency, steam temperature, furnace slagging and fouling, and NOXformation. The technologies include instruments that measure carbon levels in ash, coal flow rates, air flow rates,CO levels, oxygen levels, slag deposits, and burner metrics as well as advanced coal nozzles and plasma assistedcoal combustion.0.15 to 0.84%Cooling SystemHeat LossRecoveryRecover a portion of the heat loss from the warm cooling water exiting the steam condenser prior to its circulationthorough a cooling tower or discharge to a water body.The identified technologies include replacing the coolingtower fill (heat transfer surface) and tuning the cooling tower and condenser.0.2 to 1%Flue Gas HeatRecoveryFlue gas exit temperature from the air preheater can range from 250 to 350°F depending on the acid dew pointtemperature of the flue gas, which is dependent on the concentration of vapor phase sulfuric acid and moisture.For power plants equipped with wet FGD systems, the fluegas is further cooled to approximately 125°F as it issprayed with the FGD reagent slurry. However, it may be possible to recover some of this lost energy in the fluegas to preheat boiler feedwater via use of a condensing heat exchanger.0.3 to 1.5%Low-rank CoalDryingSubbituminous and lignite coals contain relatively large amounts of moisture (15 to 40%) compared to bituminouscoal (less than 10%). A significant amount of the heat released during combustion of low-rank coals is used toevaporate this moisture, rather than generate steam for theturbine. As a result, boiler efficiency is typically lowerfor plants burning low-rank coal. The technologies include using waste heat from the flue gas and/or cooling watersystems to dry low-rank coal prior to combustion.0.1 to 1.7%SootblowerOptimizationSootblowers intermittently inject high velocity jets of steam or air to clean coal ash deposits from boiler tubesurfaces in order to maintain adequateheat transfer. Proper control of the timing and intensity of individualsootblowers is important to maintainsteam temperature and boiler efficiency.The identified technologies includeintelligent or neural-network sootblowing (i.e., sootblowing in response to real-time conditions in the boiler) anddetonation sootblowing.0.1 to 0.65%Steam TurbineDesignThere are recoverable energy losses that result from the mechanical designor physical condition of the steamturbine. For example, steam turbine manufacturers have improved the design of turbine blades and steam sealswhich can increase both efficiency and output (i.e., steam turbine dense pack technology).0.84 to 2.6Source: National Energy Technology Laboratory (NETL), 2008.Reducing CO2Emissions by Improving the Efficiencyof the Existing Coal-fired Power PlantFleet, DOE/NETL-2008/1329. U.S. Department of Energy, National Energy Technology Laboratory, Pittsburgh, PA. July 23, 2008. Available at:<http://www.netl.doe.gov/energy-analyses/pubs/CFPP%20Efficiency-FINAL.pdf>.aReported efficiency improvement metrics adjusted to common basis by conversion methodology assuming individual component efficiencies for a referenceplant as follows: 87% boiler efficiency, 40%turbine efficiency, 98% generator efficiency, and 6% auxiliary load. Based on these assumptions, the referencepower plant has an overall efficiency of 32%and a net heat rate of 10,600 Btu/kWh. As a result, if a particular efficiency improvement method was reportedto achieve a 1% point increase in boiler efficiency, it would beconverted to a 0.37 % point increase in overall efficiency. Likewise, a reported 100 Btu/kWhdecrease in net heat rate would be converted toa 0.30% point increase in overall efficiency.

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12 Previous Studies on Heat Rate Improvements A number of studies using varying appro aches have been performed to determine potential efficiency improvement s and associated resulting CO 2 

### emission reductions. These approaches include characterizi ng the current U.S. coal-fired EGU fleet, identifying potential efficiency improvements, and applying improveme nt actions to existing EGUs. The approach taken within each study varies. Five studies are briefly summarized and co mpared in Table 2-3. Studies 1 and 2 used a benchmarking approach that evaluated the design factors that are known to influence efficiency and grouped EGUs based on similar design characteristics. The studies categorized the industry ba sed on fuel type, location, steam cycle, and age of the boilers. Potential efficiency improvements were calcul ated based on an assumption that the lowerperforming EGUs in each group should to be able to do as well as the better performing EGUs in that group. Specifically, the goal for potential im provement: for each subcategory was that the bottom 90% of EGUs in each group improved their he at rate to the average performance of top 10% in that group. While the studi es are different in the level of detail and assumptions, the
results of these studies overal l suggest that a U.S. coal-fir ed EGU fleet-wide improvement ranging from 9% to 15% is theoretically possibl e. Study 3 used a less detailed approach and evaluated technologies applicable to bituminous and subbituminous coals to estimate potential
fleet wide reductions. An alternative approach to evaluate heat ra te improvement is used for Study 4. This study focused on the operating efficiency (synonymous with heat rate) of the enti re existing U.S. coalfired EGU fleet. The authors evaluated decades of data from industrial responses to economic factors such as demand, coal price and energy pol icies. This approach determined that given specific changes in the coal price and a carbon tax, the indust ry will make heat rate improvements on their own. In this specific exampl e, the coal price was assumed to be a 10%
increase and the CO 2 

### emissions tax at $1.64 per ton for h eat rate reductions of 0.3 to 0.9%. Study 5 considered the fleet of coal-fired EGUs and assumes a target heat rate in order for the EGUs to comply with an inferred st andard. As opposed to the above studies that determined by how much the efficiencies can im prove, this approach estimated how the industry will meet any imposed standards and calculated the heat rates necessary to meet a standard. As it has not been determined with regards to how the CO 2 

### emissions limit will be averaged, the paper discusses many potential options th at coal-fired EGUs may have to meet new standards. These

### DRAFT April 4, 2014

13 options include additional options such as adding renewable, na tural gas, and combined-cycle

sources. The EPA observed that most of the exis ting studies develop fleet-wide average HRI potentials/goals that are higher than values c onsidered feasible and sustainable by the power sector engineers with whom the EPA has informa lly discussed this subject. The EPA also noted that all existing HRI studies have relied on a sing le year annual average heat rate data, whereas many of the operational impacts on heat rate (diurn al temperatures, load following, etc) become more apparent in the variability of hourly pe rformance data. We further recognized that an examination of heat rate data over a multiple year period, perhaps a decadal time frame might reveal patterns of performance that should also inform estimates of HRI potential. For these reasons, the EPA has developed in this TSD an additional assessmen t of HRI potential that draws on multiyear historical hourly data. While we understood that engineering judgment would still be essential to a proper interpretation of the resu lts, the EPA intended that this assessment be a more substantial basis for estimating the fleet-wide HRI potential for coal-fired EGUs. Table 2-3. Summary comparison of previous studies on EGU heat rate improvements Study

ID Study Title Author Factors Used for Industry Grouping Key Study Assumptions Study Results 1 “Reducing CO 2 Emissions by Improving the Efficiency of the Existing Coal-fired Power Plant Fleet” NETL • Plant design: age and steam cycle • Category improvement is the bottom 90% of EGUs in each group improving their heat rate to the average performance of top 10% in that category • Units with capacity factors

under 50% were removed from dataset • 15% reduction in overall heat rate of coal-fired EGUs

2 “Improving theEfficiency of CoalFired Power Plants for Near Term Greenhouse Gas Emissions Reductions” NETL • Plant design: coal type, steam cycle, and size • Category improvement is the bottom 90% of EGUs in each group improving their heat rate to the average performance of top 10% in that category • Units with anomalous data, capacity factors under 10%, using less than 97% coal, and gasification plants were removed from dataset • Low pressure subcritical

units and 0-200 MW subbituminous units assumed retired for goal • Lost generation made up by

more efficient coal-fired EGUs • 8.7% reduction in overall heat rate of coal-fired EGUs

### DRAFT April 4, 2014

14 Study

ID Study Title Author Factors Used for Industry Grouping Key Study Assumptions Study Results 3 “Reducing Heat Rates of Coal-Fired Power Plants” Lehigh Energy Update All possible heat rate improvements are made including drying of high moisture coal: • 10% improvementfor bituminous coalfired EGU • 15% improvement for subbituminous coal-fired EGU 4 “Regulating Greenhouse Gases from Coal Power Plants under the Clean Air Act” Resources for the Future • Analyze the actual operating efficiency of theentire fleet of U.S. coalfired EGUs • Assess abatement

opportunities and costs by observing how coal plants respond to market and regulatory incentives to improve energy efficiency Overall efficiency improvements of 2 to 5%, from other literature studies 10% coal price increase, corresponding to a tax on CO 2 emissions of about $1.64 per ton, improving heat rates by 0.3 to 0.9 %

5 “Closing the Power Plant Carbon Pollution Loophole: Smart Ways the Clean Air Act Can Clean Up America’s Biggest Climate Polluters” NRDC • Plant design: coal type and steam cycle Improvements are broken into 3 group • Top 10% for each subcategory, no change • Top 11% to 49%, improve heat rate by 50% of the difference between facility heat rate and performance of top 10% in class or 600 Btu/kWh, whichever is less • Bottom 50%, improve heat rate by 100% of the difference between facility heat rate and performance of top 10% in class or 600 Btu/kWh, whichever is less 

### EPA’s Heat Rate Improvement Assessment This EPA assessment of fleet-wide HRI potential looks at historical data from coal-fired EGUs in the U.S. to identify changes to EGUs’ h eat rates – the amount of heat input required, on average, to generate 1 kWh of electricity – that can be attributed to operation and maintenance practices and equipment upgrades. These heat ra te changes are analyzed to determine their applicability to the rest of the coal-fired EGU fleet and to determine the potential heat rate improvement that, on average, could be achieved by the fleet. This data analysis po rtion of the study relies on unit-le vel heat input and gross generation data reported to the EPA by owners or operators of EGUs to assess in detail the changes in gross heat rates. Potential changes in net heat rates are then addressed later in this se ction. Unit-level
evaluations allowed the EPA to r ecognize the significant heterogene ity of coal-fired EGUs; even

### DRAFT April 4, 2014

15 ‘sister’ units, units built at the same time at a given facility, may disp lay different operating profiles and may have different equipment, c ontrols, fuel mixes or cooling systems. Based on literature reviews; informal interv iews with engineering experts, vendors, and plant operators; and historical information collect ed by the EPA, we believe EGUs achieve heat rate improvements by: 1) operating under reco mmended operation and maintenance conditions (best practices), and 2) instal ling and using equipment upgrades. Best practices include no-cost
or low-cost methods such as the installation or more frequent tuning of control systems and the like-kind replacement of worn existing component s. Upgrades often involve higher costs and greater downtime, such as, extensive overhaul or upgrade of major equipment (turbine or boiler) or replacing existing component s with improved versions. The EPA developed unit-level statistics fr om over 60 million rows of hourly data. We
evaluate each unit on its individual performance using heat rate vari ability as an indicator of the application of best practices a nd potential for improvement. To estimate heat rate improvement through equipment upgrades we survey engineeri ng studies, examine year-to-year trends, and research EGUs where such methods were applied. Study Population and Data The EGU study population consists of 884 coal - and petroleum coke-fired EGUs that reported both heat input 2 

### and electrical output to the EPA’ s Clean Air Markets Division in 2012. 3 

### It includes a wide range of c onfigurations, from 24 to 1,500 MW nameplate capacities, super and subcritical thermodynamic cycles, between 1 a nd 69 years old, and diffe rent coal ranks. It excludes any EGUs at any facility that reported cogeneration to the EPA or the EIA. These units are excluded because a portion of the heat input was used to generate electricity and/or steam heat. Therefore, it is difficult for the EPA, using available data, to make a meaningful comparison of these units’ heat rates. The EPA performed this study using hourly he at input (Btu), and electricity output (MWh) data from the Clean Air Markets Divi sion and meteorological data from NOAA’s National Climatic Data Center for the years 2002 -2012. As described later in this section, these meteorological data were used to account for temp erature impacts on heat ra tes. The eleven year study period is representative of a wide range of conditions, including gr owth and recessionary

2 Sources calculate heat input using an ‘F factor’ for the carbon content of th e fuel being combusted and the average hourly measurements of CO 2 flow and concentration. 3 Information on the Clean Air Markets Division data is available at http://ampd.epa.gov/ampd/

### DRAFT April 4, 2014

16 economic conditions, changing electricity genera tion from renewable and natural gas, and different regulatory constraints. The hourly heat input and ge neration data used in this study is collected under the authority of 40 CFR part 75 (hereafter, Part 75). The EPA designed Part 75 to encourage complete and accurate emission measuremen t and reporting to support emission trading programs, including the Acid Rain Program and Cl ean Air Interstate Rule (CAIR). However, the EPA recognized that there will be times when emission data are not available due to monitoring system malfunctions or maintenance, technical challenges, or missed qua lity assurance/quality control (QA/QC) tests. When data are not available or deemed invalid (e.g., when a QA/QC test was not performed as required), the EPA has specified data substitution methods that are designed to overestimate emissions. This conservative bias is intended to create an incentive for
better emission measurement – the overestimate incu rs an economic penalty because, at the end of the compliance period, an EGU must surrender allowances equa l to total reported emissions. Because of this conservative bias and the impact it would have on the results of this study, the EPA excluded substitute data reported by EGUs from this study’s dataset. These substitute data represent approximately 2% of all reported operating hours. In addition, we excluded partial hours of operation that occur during the first hour of startup and the last hour of shutdown. We also exclude 40 unit-years (0.5% of records) with atypical annual heat rates less than 6,500 or greater than 15,000 Btu/kWh resulting fr om a variety of factors including firing of natural gas, very low operating time, or erro rs reporting gross load. Table 2-4 summarizes the unit counts by year for the study population used in this work. This population corresponds to 9,350 unit-years of data at 884 distinct EGUs.

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17 Table 2-4. Study Population Unit Count by Year 4

Year Unit Count
2002 

### 833
2003 

### 828
2004 

### 833
2005 

### 836
2006 

### 845
2007 

### 844
2008 

### 851
2009 

### 860
2010 

### 865
2011 

### 876
2012 

### 879


### NOAA’s Integrated Surface Data (ISD) pr oduct provides hourly temperature for over 20,000 weather stations worldwide. 5 

### Since EGU performance is sens itive to air temperature and barometric pressure, which vary with elevation, we use meteorological data from stations that are reasonably close to the EGU's location and elev ation to account for the impact of ambient conditions. For each of the plants in this study’s database, we identi fied the nearest stations that reported a minimum of 8,400 hourly obs ervations in the calendar year (i.e., greater than 95% of the hours in a year). Generally, each plant was associated with me teorological data from the two closest stations over the eleven-year study peri od. The average distance between the plant and station was 22 miles and the averag e difference in elevation was 366 f eet. At nine plants we used data with as few as 7,000 observa tions in order to keep the ma ximum difference in elevation under 1000 feet. The EPA believes that nearby weather station measurements are a good approximation of ambient meteorol ogical conditions at each faci lity. Joining the trimmed heat rate and hourly temperature datasets resulted in 61,848,580 hourly records for the study population of EGUs (s ee Table 2-4). The results of this study are based on analys es of data from the population of coal-fired EGUs shown in Table 2-4. These units emitted 1,606 million tons of CO 2 

### in 2012. In contrast,
emissions of CO 2 

### from coal-fired EGUs in the entire U. S. electric power sector in 2012 were at

4 The study population for each year includes those EGUs that reported both heat input and electric generation.

### DRAFT April 4, 2014

18 1,669 million tons according to the EIA. 6 

### Since the study population of EGUs accounted for over
96% of CO 2 

### emissions from the fleet of U.S. coal-fir ed EGUs, the EPA considers the results of this study to be applicable to th e coal-fired flee t at large. Subcategorization In this analysis, units are not categorized by unit specific design characteristics or fuel because: (1) EGU-specific detailed design information on all factors that influence heat rate is not available, and (2) certain de sign characteristics are not eas ily categorized (e.g., EGUs use a large range of steam conditions). Several other studies do categorize EGUs broadly by capacity, thermodynamic cycle, and/or fuel rank. Alt hough the EPA believes grouping by categories can provide a useful way of understand ing the operating profile of an E GU and the fleet, the range of heat rates for the broad categories has significant overlap (see Figure 2-1) and therefore makes it challenging to develop appropriate categoriz ation. The figure below displays available
information on coal-fired EGUs considered in this work for the years 2009-2011 in typical subcategories of capacity, fuel rank, and thermodyna mic cycle. As the figure reflects, the means are clustered and the ranges of heat rates overlap.

Figure 2-1. 3-Year Average Heat Rates by Subcategory 7

6 Preliminary 2012 results from http://www.eia.gov/tools/faqs/faq.cfm?id=77&t=3 . Revised 2012 results will be available in March, 2014. The somewhat lower 2012 CO 2 emissions total in Table 2-5 below is due to the exclusion of substitute data

. 7 Abbreviations in the figure: BIT means bituminous, SUB means subbituminous, LIG means lignite, SUPER means supercritical, SUB means subc ritical OVER/UNDER means greater/less than indicated MW capacity. 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000 BIT SUPER SUB SUPER BIT OVER 200 PC BIT 100 to 200 SUB OVER 100 LIG OVER 100 BIT UNDER 100 SUB UNDER 100 LIG UNDER 100

3-Year (2009-2011) Average Heat Rate (Btu/kWh)Subcategory

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19 Observed Trends in the Period 2002-2012
Three trends are notable for the study population during the period 2002-2012. Comparing the averages of the first three ye ars (2002-2004) to the last three years (2010-2012), electric generation, capacity f actor, and gross heat rate declined by 9%, 21%, and 2%, respectively. The decrease in coal-fired gene ration and capacity factor may be because of reduced demand for electricity re sulting from the recession starti ng in late 2008 and greater use of natural gas and renewables to generate electricity. The 11-year average annual gross heat rate for the study population of coal-fired EGUs (see Table 2-4) was 9,763 (Btu/kWh). The decrease in study population annual heat rate between 2002 and 2012 may be due to several factors. Unit efficiency may have improved or units with lower heat rates may have taken up a larger shar e of generation. In addi tion, changes in reporting methodology described later in this chapter may be partly responsible. The minimum annual heat rate (9,650 (Btu/kWh)) occurred in 2008, near pe ak generation for the years under consideration, and was approximately 1% below the average. Table 2-5 displays the annual heat input, electricity generation, capacity fa ctor, and heat rate for the st udy population of EGUs. Figure 2-2 displays the average annual gross heat rate by year and the 11-year average.
Table 2-5. Trends 2002-2102

Year Heat Input (million Btu) Electric Generation (MWh-gross) Operating Hours Capacity Factor

(%) Heat Rate(Btu/kWhgross) 2002 18,661,321,692 1,877,860,222 6,130,609 64 9,938 2003 18,490,002,370 1,868,191,406 6,044,559 65 9,897 2004 18,488,140,910 1,880,068,323 6,048,381 65 9,834 2005 18,754,700,745 1,916,068,402 6,141,697 66 9,788 2006 18,746,450,250 1,922,588,408 6,155,013 65 9,751 2007 18,787,425,977 1,927,419,559 6,138,888 66 9,748 2008 18,545,285,797 1,921,820,484 6,088,562 64 9,650 2009 16,670,621,043 1,726,641,303 5,448,438 54 9,655 2010 17,771,232,591 1,838,417,252 5,754,116 58 9,667 2011 17,006,597,908 1,750,427,841 5,507,574 53 9,716 2012 15,010,214,648 1,541,305,063 4,816,547 44 9,739

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20 Figure 2-2. Study population Aver age Gross Heat Rate by Year
Startups and Shutdowns - Impact On the Results of This Study During periods of startup and shutdown, EGUs are known to operate at higher heat rates. Therefore, we evaluated the poten tial impact of such events on our evaluation. A startup event, as defined here, occurs when an EGU begins combusting fossil fuel and generates some measurable amount of electricity. Table 2- 6 summarizes the study population average, maximum and total starts by year. On average, coal-fired EGUs start combusting fuel and generating electricity 11 times per year. The total number (approxima tely 9,000) of starts for the study population of EGUs has remained stable over the study period. Our data reflects that some coal-fired units operate in a load following cap acity and may report upwards of 200 starts in a single year, but these units tend to have low annual capacity f actors. The subset of EGUs with more than 20 annual startup and shutdown events is responsible for less than 4% of total generation in any study year. Theref ore while the number of starts is an important variable at a small number of EGUs, its impact on heat rate performance evaluated in this study is considered to be marginal. 9,500 9,550 9,600 9,650 9,700 9,750 9,800 9,850 9,900 9,950 10,00020022003200420052006200720082009201020112012Heat Rate (btu/kwh)

Annual Heat Rate 11-yr Avg Heat Rate

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21 Table 2-6. EGU Start Count by Year

Year Average Maximum (at any single EGU) Total
2002 11.1 209 9,363 2003 10.6 194 8,936 2004 10.7 134 9,081 2005 11.0 183 9,265 2006 10.5 139 8,859 2007 10.5 164 8,908 2008 10.4 134 8,880 2009 10.3 178 8,902 2010 10.5 211 9,110 2011 10.6 206 9,295 2012 9.9 119 8,805


### Impact of capacity factor and ambient temperature Two important factors that a ffect heat rate at an EGU are hourly capacity factor and ambient temperature. In this section, we examine the impact of these two variables on heat rates of the EGUs in the study population. Coal-fired units are designed to operate most efficiently at full capacity. As a unit drops below this level, in general, heat rate will in crease. The average capacity factor over 11 years for the study population is 67%, but as noted above , has moved markedly over the study period. This study looks at utilization level at both hour and year time scales. The two are related but reveal different information about how an EGU is opera ting. For example, for a unit to achieve a high annual capacity factor (e.g., over 90%) it must operate at a high load for most hours in a year. At lower capacity factors interpreting the relationship between hourly and year ly utilization levels becomes more complex. For example, an EGU may run at an annual 60% capacity factor by operating 8 months at near full cap acity and generating no electricity the rest of the year, or it may run at lower utilization levels for most hours of the year in response to weather, generation cost, and transmission constraints. Ambient temperature can affect heat rate in two ways: 1) the efficiency of the thermodynamic steam cycle 8 

### and, 2) in many regions of the c ountry, as temperatures increase

8 The availability of a cold heat sink in the condenser is a ke y factor in that cycle. The design of the heat exchanger, type of cooling system and availability of water all have an impact on performance. An increase in ambient air

### DRAFT April 4, 2014

22 electricity demand capacity factor follows. Figure 2-3 shows the average monthly capacity factor in 2012 alongside the climate normal monthly temperature. 9 

### The lines intersect in the spring as temperatures begin to rise and the need for c ooling drives electricity demand. Peak capacity factor and generation in most parts of the U. S. occur on the hottest days of the year.

Figure 2-3. Monthly Capacity Factor, 2012. 

### Regression Analysis
Using the hourly data set, the EPA perfor med three regression analyses for each unityear: heat rate onto capacity factor, heat rate onto ambient temperat ure and heat rate onto capacity factor and ambient temperature. The si ngle variable analyses help to examine the relative influence of capacity fact or and ambient temperature on h eat rate. Since this analysis seeks to evaluate heat rate under normal opera ting conditions, we removed records with hourly
heat rate values outside of +/ - 2.6 standard deviations (1.9% of records) before performing the regressions. 10 

### Similarly to partial operating hours, thes e outliers tend to o ccur during low load
conditions. The records trimmed amount to one-fourth of a per cent of the total study population generation. Regression results desc ribe the goodness of fit for the model and are expressed as the coefficient of determination or ‘r-squared’. To represent the relative co ntribution of varying unit capacities all results ar e generation-weighted. 11 

### The average study population r-squared for the multivariate regression is 26%. This means that hourly ambient temperature and capacity factor

temperature, and consequent increase in water temperature, typically lower the effectiv eness of the cooling system, the condenser, and, therefor e, overall plant efficiency. 9 Climate normal is the average of temperature (or other meas ure) over a prescribed 30-year interval and location. The chart shows the 1981-2010 climate normal monthl y temperature at Baltimore-Washington Airport, MD. 10 The 2.6 standard deviation bound is used in other EPA regulatory analyses. 11 In a weighted average, each component is multiplied by a factor reflecting its importance. In this case, generationweighted r-squaredis the average of r-squared for each unit multipliedby its annual generation. 0 20 40 60 80 100JanFebMarAprMayJunJulAugSepOctNovDec 

### Electric generation monthly 2012 capacity factor and normal temperature

Capacity Factor (Monthly %, 2012) Climate Normal (BWI, MD)

### DRAFT April 4, 2014

23 together explain 26% of the change in heat ra te for the study population over the study period. The average study population r-squared from the singl e variable analysis of capacity factor is 16%; the corresponding result for temp erature is 10%. This means that approximately 16% of the change in hourly heat rate is attributable to capacity factor and 10% to ambient temperature. These results, however, conceal considerable va riability. Some EGUs, typically load-following, have an 11-year average r-squared for capacity factor exceeding 50%. At those EGUs, the capacity factor is a key variable influencing changes in heat rate. At approximately one-fourth of the study popul ation the response to ambient temperature is larger than the response to capacity factor. At individual EGUs, temperature may explain up to 30% of the change in heat rate. These are typica lly, but not exclusively, units with once-through, fresh water, cooling systems. Identifying temperat ure-responsive EGUs allows us to understand why heat rate may increase during periods of peak demand. These are the EGUs where the ambient temperature ‘signal’ is an important va riable. At a typical EGU, summer month heat rates may increase by 2-4% compared to winter months, but at a temperature-responsive EGU that figure may be as high as 10%. Our results found that as EGUs cycle more, i.e ., move from base load to load following, capacity factor will tend to have a larger effect on heat rate. Since 2008, the study population capacity factors moved from the top load bin into lower load bins. This can be seen from Figure 2-4, which compares the study population duty cy cles in 2008 to 2012. A significant share of 2008 generation occurred at EGUs running at greater than 85% annual capacity factor. In 2012, little generation took place in that bin, and ge neration was reduced by about half in the next lower bin (79-84% cap acity factor).

### DRAFT April 4, 2014

24 Figure 2-4. Change in Annual Duty-Cycle 2008 and 2012
Heat Rate Variability and Indica tion of Improvement Potential This study examines heat rate variability from the standpoint of statistical process control, which is utilized th roughout the power industry. Several years ago, the EPA introduced process control charts for auditing emissions da ta reported under Part 75. Sources and vendors adopted the EPA methodology to identify potential problems earl y, before they significantly
affect emission measurements. Heat rate lends its elf to process control since it is the principal indicator that defines the quality of the electric generation process. 12,13 

### Therefore, in general, high variability in heat rate values would reflect opport unities for process improvement. We use the relative standard deviation (RSD ) of the hourly heat rates to evaluate each unit against its past performance and to comp are with the study population. Each unit has up to eleven RSD values, i.e., one for each opera ting year between 2002 and 2012. The generationweighted mean RSD for the study population across 11 years is 5.4%. Table 2-8 summarizes eleven years of results for the study populati on by quartiles ordered by the 11-year generationweighted RSD (ascending). 14 

### The RSD of the top quartile (3.5 %) is significantly lower than the study population generation-weighted mean RSD of 5.4%. Notably, the EGUs in the top quartile are not outliers; they report a third of all ge neration – the most of any segment. The results display a wide range of heat rate variability in the study population and thereby indicate the potential for heat rate improvement. Table 2-8. RSD in reported heat rate (generation weighted)

Quartile RSD Average RSD Minimum RSD Maximum Share of Generation

1 3.5 1.6 4.2 

### 33 2 4.7 4.2 5.3 

### 26 3 6.1 5.3 7.0 

### 24 4 9.8 7.0 25.2 

### 16

12 “The principal indicator that defines the quality of the process is heat rate.” (Fredrick & Todd, 1993. Statistical Process Control Methods in Performance Monitoring. Available at famos.scientech.us/Papers/1993/1993section11.pdf) 13 Since accurate measurement is essentia l to process control the introduction of increasingly sophisticated digital control systems (DCS) presents new opportunities for find ing inefficiencies. Vendors (ABB, Seimens, Emerson) claim heat rate improvements of 2- 5 percent can result from upgrading to a modern DCS and advanced control technologies. The improvement can be even higher if system-wide real-time optimization is included. 14 Nine EGU RSD values exceeded 2.6 standard deviations above the mean and were removed from the results in the table.

### DRAFT April 4, 2014

25 The study also examined EGU heat rate vari ability using the resi dual heat rate. The residual in a regression analysis is the difference between the observed value of the dependent variable (heat rate) and the predicted value. The intercept is the value where the linear regression crosses the y-axis. For each EGU, we calculated the residual heat rate by summing the residual for each hour to the intercept value. The standard de viation of the residual heat rate statistic is
used to understand the amount of variability that is not explained by capacity factor and temperature. The average RSD corresponding to residual heat rate variability for each EGU is the generation-weighted average of up to eleven annual values. The st udy population generationweighted mean RSD over the study period is 4.5%. This perc entage represents the total variability across the study populat ion that our analysis could not explain by hourly capacity factor or ambient temperature. Possible causes of this variability include changes in plant equipment, operating procedures and maintenance, fuels (particularly coal rank), reporting methodology, and unexplained factors. There is no te mporal trend evident in the RSD. Table 2-9 summarizes the study population gene ration-weighted average RSD of residual heat rate over the study period in quartiles orde red by the 11-year generation-we ighted RSD (ascending). Table 2-9. RSD of residual heat rate (generation weighted) 15

Quartile RSD average RSD Minimum RSD Maximum

1 2.7 0.0 3.2 2 3.6 3.2 4.1 3 4.7 4.1 5.3 4 6.9 5.3 10.4


### The weighted average RSD of the top quart ile is 2.7% – well below the study population average of 4.5 %. This means that the residual hour ly heat rates of these un its generally stay in a narrow range within a given year. The maximu m RSD in the top quartile is 3.2%. From the statistical process control point of view, these units appear to have low variability. The weighted average RSD of the bottom quartile is 6.9%, which is over twice that of the top quartile. This spread indicates that there is likely room for improvement in study population operation to reduce variab ility and heat rate.

15 This table excludes nine units where RSD exceed ed 2.6 standard deviations from the mean.

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26 Heat rate variability and performance
To examine the association between heat rate variability and heat rate performance this study examined the RSD for unit-year heat rate s calculated from reported data. The study population generation-weighted an nual RSD ranges between 5% and 6% during the study period. Figure 2-5 below summarizes the re sults of regressing RSD of heat rate onto annual heat rate. 16 

### The r-squared result is 57%. These results indica te that, other factors he ld equal, if an EGU reduces heat rate variability, generally heat rate performance will improve.

Figure 2-5. Regression analysis of reporte d heat rate RSD onto annual heat rate 

### Units with large heat rate changes Over one third of the study population (355 units) reported at leas t one year-to-year change in heat rate greater than +/- 8.5%. 17 

### We consider this magnitude to be in the upper range of what would be expected due to changes in fuel rank, operations and maintenance, or plant equipment. Table 2-10 presents the counts by thr ee categories: EGUs with at least one year-toyear decrease in heat rate > 8.5%; units with at least one year-to-year in crease in heat rate > 8.5%; and, units with both. We examined whether the large heat rate changes were due to a yearto-year changes in capac ity factor and found no correlation betw een the year-to-year changes in heat rate and capacity factor for a ny of the three groups in Table 2-10. 18 

### This would indicate that other factors account for these large changes to heat rate. The EPA’s research found that approximately two-thirds of the large decreases in heat rate can be associated with changes in

16 The regression analysis was performed on 9,348 unit-years of study data which were trimmed to remove values outside 2.6 standard deviations. 17 After removing unit-years where annu al capacity factor fell under 50 percent the count is 313 EGUs. 18 The correlation remains weak even when limited to cases wh ere capacity factor changed more than 30 percent. y = 0.002x - 14.254 R2 = 0.5704 5.0 5.2 5.4 5.6 5.8 6.0 6.2

9600 9650 9700 9750 9800 9850 9900 9950RSD heat rate %(generation weighted)

Heat Rate

### DRAFT April 4, 2014

27 reporting method implemented to provide more accurate heat input data. 19 

### The large changes noted at the remaining one-third could not be explained by changes in reporting methodology. Moreover, we found no correlation between changes in reporting method and heat rate RSD. Table 2-10. Year-to-Year Heat Rate Change

Description Count Correlation of heat rate to capacity factor Units with only year-to-year heat rate decrease > 8.5% 166 .1 Units with only year-to-year heat rate increase > 8.5% 80 .1 Units with both year-to-year heat rate decrease and increase > 8.5% 355 .1


### The breakdown of the ‘large decrease’ EGUs by qua rtile, in Table 2-11 below, is consistent with the study population results shown in Table 2-8. Th is does not imply that the changes associated with a large year-to-year d ecrease, which may include operations and maintenance, more accurate reporting methods, or new equipment, do not affect heat rate variability. If they occur as part of an engineering effort to improve efficien cy, heat rate variability may also be reduced. Table 2-11. RSD in reported heat rate of 166 ‘large decrease’ EGUs (generation weighted)

Quartile RSD Average RSD Minimum RSD Maximum

1 4.0 2.3 4.8 2 5.3 4.8 5.9 3 6.6 5.9 7.5 4 10.5 7.6 26.5


### Assessment of heat rate improveme nt potential via best practices As mentioned before, across the study period, the effects of hourly capacity factor and ambient temperature explain a generation-weight ed average of 26% of the change in study population heat rate. 20 

### This means that on average 74% of the change remains unexplained after

19 EPA Reference method 2 specifies the normal procedure for measuring stack gas volumetric flow rate during a relative accuracy test audit. Methods 2F, 2G, 2H and CTM-041 are approved alternativ es. Methods 2F and 2G correct measured flow rates for angular (non-axial) flow, Method 2H (for circular stacks) and conditional test method CTM-041 (method J, for rectangular stacks and ducts) are used to correct measured flow rates for velocity decay near the stack wall, using a “wall effects adjustment factor”. These alternative methodologies are optional. Therefore, given the additional complexity and cost of usin g these alternatives a source is likely to use them only if the results are significantly lower volumetric stack gas flow. The EPA was unable to draw conclusions about the effect of changes in flow reporting methods on fleet heat rate performance. 20 The 26% result is the generation weighted average of r-squ ared values from the multivariate regression analysis.

### DRAFT April 4, 2014

28 controlling for those factors. The residual heat ra te analysis determined there is significant variation in the operation of EGUs. Since lower heat rate variability is associated with lower heat rate, other factors held equal, th e range of variation i ndicates that significant potential heat rate improvement is available through the application of best practices.

To control for known factors, the EPA c onstructed a model that groups each EGU’s hourly heat rate data into 14 temperature bins and 12 capacity factor bins, resulting in a 12 by 14
matrix of 168 bins. 21 

### For a given EGU, a temperature and capacity factor bin will have all the relevant hourly values over the eleven-year study period. For each bin with 15 or more values the model finds the reported hourly heat input va lue corresponding to the 10th percen tile(p10). 22 

### This means that approximately 90% of the heat input values in that bin exceed p10. For each unit, the model reduces the repor ted hourly heat input greater th an p10 by a percentage of the distance between the reported value and p10, e.g., 50% of the difference. The same statistical procedure is applied to every hour of heat input data in each bin. These reduced hourly heat input values are then used to calculate a reduced 11-ye ar average heat rate for each unit. The percent difference between a unit’s reported 11-year average heat rate and the heat rate that corresponds to reduced heat inputs is the potential heat rate improvement for that unit. 23 

### Using this approach,
those units with the lowest vari ability (e.g., in the top quartile of residual heat rate variability) take proportionally smaller reductions. Table 2-12 below shows the model results with op tions of 10% to 50% stringency. For example, reducing reported heat input 10 % of the di stance to the p10 value achieves a 1.3% study population wide reduction. Alternatively, a 50% reduction will result in a 6.7% study population wide improvement in heat rate. In effect, the mo del proportionately reduces heat rate variability and improves performance for each unit while cont rolling for temperature and capacity factor. The heat rate improvement for the study population is derived from the performance of each individual EGU as compar ed to its own record.

21 The matrix provides up to 168 bins but only 164 contained hourly values. Temperature bins ranged from -20 to greater than 110 with 10 degrees F in each. Capacity factor bins ranged from 0% to greater than 110% with 10% in each. 22 Performing the calculation with a minimu m of 30 values in each bin has a mode st effect on the results in Table 2- 12. For example, a 30% reduction obtains a 3.9% fleet wide improvement in heat rate (rather than 4.0%). 23 Heat rate is calculated as the sum of heat input (btu, reported or reduced) divided by the sum of generation (kWh) for the given population and time period.

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29 Table 2-12. Assessment of heat rate impr ovement potential via best practices

% Reduction from reported heat input to p10 Study population heat rate (Btu(kWh-gross) 24 Reduced study population heatrate (Btu/kWhgross) Study population heat rate improvement (%)

10

9,755 9,625 1.3 20 9,495 2.7 30 9,365 4.0 40 9,235 5.3 50 9,105 6.7


### Assessment of potential heat rate improvement via equipment upgrades The EPA inspected the study population to find examples of EGUs that made significant year-to-year improvements in heat rate. After fi ltering out those cases that may have been the result of changes in capacity factor, reporting me thod, or other events, we identified 16 EGUs that reported year-to-year heat rate improvements of 3-8%. In tw o of these cases we were able to identify equipment upgrades responsible for 2-3% heat rate improvement using the applicable estimates from the Sargent & Lundy 2009 study. Simila rly, in the other cases, while our research was unable to confirm specific equipment upgrades , based on the elimination of other possible explanations we believe that equipment upgrades were the most likely cause of some of the observed heat rate improvements. The EPA also reviewed the engi neering studies available in th e literature and selected the Sargent & Lundy 2009 study as the basis for our asse ssment of heat rate improvement potentials from equipment and system upgrades. We focused on some thirteen heat rate improvement methods discussed by Sargent & Lundy, seen in Table 2-13. We used the average of the estimated $/kW costs for each method to develop the cost-ranked list of heat rate improvement methods (lowest cost at the top, highest at the bo ttom) shown in Table 2-13. The first nine items in Table 2-13 contribute about 15 percent of the to tal average $/kW cost fo r all items. We believe
it is reasonable to consider those nine no-cost and low-cost heat rate improvement methods as belonging in the category of what has been described above as best practices. The remaining four

24 Fleet heat rate for entire study population is 9,763; the 9,755 value is derived from the dataset that includes hourly temperature values.

### DRAFT April 4, 2014

30 methods are higher cost heat rate improvement items that we be lieve properly fall into the category discussed here as upgr ades. Using an average of the ranges of potential Btu improvements estimated by Sargent & Lundy for the four upgrade methods, upgrades, as defined here, could provide a 4% heat rate improvement if all were applied on an EGU that has not already made these upgrades.

Table 2-13. Sargent & Lundy Heat Rate Improvement Methods No-Cost and Low-Cost Options Condenser Cleaning Intelligent Soot Blowers ESP Modification Boiler Feed Pump Rebuild Air Heater and Duct Leakage Control Neural Network SCR System Modification FGD System Modification Cooling Tower Advanced Packing
Higher Cost Options Economizer Replacement Acid Dew Point Control Combined VFD and Fan Turbine Overhaul
We also examined the annual heat rate trend line for each unit developed using the method of least squares. Using the slope of the tr end line, 2002-2012, as an indicator of heat rate performance of an EGU, a negative slope woul d indicate that the heat rate has improved. The annual trend line incorporates performance due to operating conditions (capacity factor, temperature), coal rank, maintenance, reporting method changes, equipment upgrades, and other factors. Over 40% of units have a positive slope. This would imply that equipment maintenance and upgrades at a significant fraction of the study population have not been sufficient even to maintain the status quo. Combined study population results The EPA’s analysis finds that a total of 6% heat rate improvements for the coal study population can be achieved through two types of cha nges: best practices th at have the potential to improve heat rate by 4% and equipment upgrades that have the potential to improve heat rate by 2%.

### DRAFT April 4, 2014

31 The best practices results ar e supported by the va riability analysis using 11 years of hourly data applied to each un it. This analysis found that th e top quartile of EGUs reported significantly lower heat rate va riability than the st udy population average. Reducing heat rate variability will generally also improve heat rate performance, other factors held equal. We found that a 4% improvement is determined by cons ervatively reducing heat input by 30% of the difference between the reported value and p10 in each unit’s capacity factor and ambient temperature bins. The 30% approach is in the middle of the range of options shown in Table 2-12 and is comparable to other approaches for meas uring potential fleet heat rate improvement. For example, if each unit achieved heat rate performance equal to its best three-year moving average, the study population as a whole would post a 3.9% heat rate improvement. The best two-year moving average would achieve nearly a 5% improve ment and the best single year over 6%. EPA believes that the minimum three-year moving averag e heat rate is a reasonable target for the improvement potential from applying best practice s. Single year results could be due to unusual conditions, such as, an extended outage or weat her. Using three consecu tive years tends to smooth out the effect of equipment maintenan ce cycles and unusual mete orological patterns.
The equipment upgrades results are supported by numerous studies 25 

### and by the EPA’s analysis of the costs and associated improvements in heat rate that can be attributed to equipment and system upgrades. We considered that a 4% reduction in heat rate might be achieved on a coal-steam unit by applying the four higher cost upgrade actions described in Table 2-13 above. However, because details of current actual un it configurations are unknown, and some units may have applied at least some of the upgrades, we co nservatively estimate the heat rate improvement potential for upgrades at 2%. The EPA considers the results of this study to be applicable to the U.S. coal-fired fleet at large since the st udy population of EGUs accounted for over 96% of 2012
electric sector CO 2 

### emissions from coal. Sensitivity Analysis Removing Pla nned or Announced EGU Retirements
The EPA’s research found 230 EGUs that ha ve announced they will retire before 2016. 26 

### A sensitivity analysis was applied to the EGUs in the study population that plan to operate through 2015. The results are identical to the fu ll population – both achieve a heat rate reduction of 4% under the 30 percent di fference option described in best practices.

25 See discussion in Table 2-3 above, and the HRI Pa rtial Bibliography at the end of this section 26 The EPA research was derived from Ventyx Velocity Suite New Entrants database (propr ietary) and other sources,

### DRAFT April 4, 2014

32 Heat Rate Improvement – Economics Most of the methods that can be applied to achieve a sustained Heat Rate Improvement (HRI) on a coal-steam EGU will entail a capital co st. These HRI capital co sts can be economic to incur if they yield sufficient redu ctions in other current or potentia l costs, particularly reductions in coal fuel cost and any cost related to CO 2 

### emissions. For the purpose of this TSD analysis, it is
assumed that HRI can be economic if the annua lized net savings (coal cost savings plus CO 2 

### emission cost savings minus capital cost) is positive: Annual Net HRI Savings = Coal Cost Savings + 

### CO 2 

### Emission Cost Savings – Capital Cost 27 

### Heat Rate Improvement Capital Cost Assumption The 2009 Sargent & Lundy study describes numer ous well known and technically proven
HRI methods for coal-steam EGUs . The study includes an estimated min-max range of heat rate improvement, and the min-max range of associated capital cost for each HRI method, for units ranging in size from 200 MW to 900 MW. If thes e methods and unit sizes are combined, as though they were all applied on a single EGU, th e following range of Sargent & Lundy estimated Btu reductions and associated range of capital cost s are obtained:
Combined Min-Max HRI Btu Reduction: 415-1205 Btu Combined Min-Max HRI Capital Cost: $40-150/kW EPA Assumed Combined HRI Capital Cost: $100/kW The wide ranges of estimated HRI Btu and costs are indicative of the wide range of real differences in the many details of site specifi c EGU designs, fuel types, age, size, ambient conditions, current physical condition, etc. This TSD analysis therefore assumes $100/kW as a representative combined HRI cap ital cost to achieve whatever HRI Btu reduction is possible at an average site. The effect of a lower HRI cost is also examined. Heat Rate Reduction Assumption The weighted average annual net heat rate of the U.S. coal-steam EGU fleet in 2020 is projected at 10,450 Btu/kWh in the EPA’s IPM v5.13 Base Case modeling. As indicated by the Sargent & Lundy estimates given above, HRI met hods could possibly reduce this average coal fleet heat rate by about 400 to 1200 Btu/kWh, or by about 4% to 12% of the projected 2020

27 This TSD analysis assesses a broadly combined application of multiple HRI met hods. As estimated in the 2009 Sargent & Lundy study most HRI-related O&M costs are sufficiently small relative to the associated annualized capital costs, such that they do not ma terially affect the economics of broadl y combined HRI methods. The analysis therefore does not consider the small econom ic impact of HRI-related O&M costs.

### DRAFT April 4, 2014

33 average, provided that all units were able to apply all of the combined HRI methods. The proviso is important to this analysis because the EPA e xpects that a significant fr action of the coal fleet has already applied some or ma ny of the available HRI methods. 28 

### The EPA does not have sufficient site speci fic information to accurately estimate what percentage of the fleet has adopted various HR I methods, nor how effectively, and is not aware of any other investigator havi ng sufficient information. HRI po tential can therefore not be estimated at this time through analysis of the cu rrent equipment configura tions of the coal steamEGU fleet. The EPA therefore analyzed 11 years of historical heat rate da ta and the literature on HRI methods, as discussed earlier in this TSD, to estimate that the U.S. coal-steam EGU fleet might reasonably be expected to reduce its a nnual average gross heat rate by about 6%. The EPA understands that any HRI method that reduces gross heat rate will also reduce net heat rate, and that some HR I methods reduce net heat rate w ithout reducing gross heat rate. We expect that the HRI potential on a net output basis is somewhat greater than on a gross output basis, primarily through upgrades th at result in reductions in auxiliary loads. For purposes of this TSD the EPA conservatively assumes that the coal fleet average net heat rate can be reduced by
6%. Heat Rate Improvement Breake ven Economic Analysis
Figure 2-6 presents a simple breakeven ec onomic analysis for combined HRI methods using the assumptions described a bove, also assuming there is no CO 2 

### emission cost that is
reduced via HRI.

28 Based on the EPA informal discussions with Sargent & Lundy and other power sector engineering firms. The EPA has found no comprehensive data set on the extent to which specific HRI methods have already been applied at individual EGUs. The EPA believes that many EGU owners consider such information to be confidential.

### DRAFT April 4, 2014

34 Figure 2-6. HRI Breakeven Economics
Notes:
1. Capital cost S/MWh assumes the following: HRI capital cost = $100/kW; capital charge rate = 14.3%; IPM projected 2020 annual capacity factor = 78% 2. Coal fleet average 2020 net heat rate = 10,450 Btu/kWh; heat rate reduction = 6%
Figure 2-6 shows that the average fleet-wide savings in coal cost would become greater than the annualized capital cost of an average 6% reduction in heat rate when the average fleetwide coal cost exceeds about $3.25/MMBtu. Fo r comparison, the average U.S. power sector delivered cost of coal in 2020 is projected in EPA’s IPMv5.13 Base Case modeling at $2.62/MMBtu. For different assumptions, the HRI economic breakeven point would change directionally as follows:

 If the HRI capital cost were on average le ss than the assumed $100/kW, 6% HRI would
then become economic at lower coal costs. Fo r example, if the aver age capital cost were actually $75/kW, a fleet-wide 6% HRI would become economic at an average coal cost of about $2.50/MMBtu, which is comparable to the U.S. power sector average costs of $2.38/MMBtu for all coal ranks and $2.89/ MMBtu for bituminous coals in 2012. 29 

### This sensitivity indicates that fuel cost savings alone would make it economic for some of those EGUs currently using high cost bitumi nous coals to make HRI investments.

29 EIA, Electricity DataTable 7.4, Av erage Weighted Cost of Fossil Fuels for the Electric Power Industry 2002- 2012, http://www.eia.gov/electri city/annual/html/epa_07_04.html 0.00 0.50 1.00 1.50 2.00 2.50 3.00

1.00 2.00 3.00 4.00$/MWh‐net

Coal Cost $/MMBtu Coal Cost Savings $/MWh

‐ net Capital Cost $/MWh

‐ net



### HRI Capital Cost = $100/kW

### DRAFT April 4, 2014

35  At an EGU net heat rate that is higher than the IPM projected 2020 average value of 10,450 Btu/kWh, 6% HRI could be economic at coal costs lower than the values
mentioned above.

 If the average heat rate reduc tion were only 4% instead of th e assumed 6%, at a cost of $100/kW, average coal costs would have to exceed $4/MMBtu for 4% HRI to be economic fleet wide,

 But, if the average heat rate reduction were 4% at a cost of $50/kW, HRI could become economic at an average coal cost of about $2.50/MMBtu.

 If there were additional HRI sa vings due to avoided future CO 2 

### emission costs, HRI could become economic at lower coal costs, or at higher capital cost s, or at lower heat
rate reduction percentages.

Estimated Fleet-wide Coal EGU CO 2 

### Reduction and Cost via HRI
It is possible to make an order-of-magnitude estimate of the fleet-wide extent and costeffectiveness of HRI using reasonable a ssumptions as in the following example:
Fleet-wide 2020 Assumpti ons (basis: similar to IPMv5.13 Base Case):

 Coal fleet capacity applying combined HRI methods = 244,000 MW

 Average CO 2 

### emission rate = 0.976 tonne/MWh net

 Average net heat rate = 10,450 Btu/kWh net

 Average capacity factor = 78%

 Pre-HRI CO 2 

### emissions = 1.62 billion tonne/yr (calculated)

 HRI Btu and CO 2 

### reduction = 6%

 HRI capital cost = $100/kW

 Annual capital charge rate = 14.3%

 Average coal cost = $2.62/MMBtu
Estimated Fleet-wide Results:

 Fleet-wide CO 2 

### reduction via HRI = 97 million tonne/yr

 Total HRI capital cost = $24 billion

 Annualized HRI capital cost = $3.5 billion

 Annual coal cost savings (cost) = $2.7 billion

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36  Annual net savings (cost) = ($0.8 billion)

 Annual net savings (cost) of CO 2 

### reduction = ($7.7/tonne)
Conclusion - HRI Economics
This necessarily simplified HRI economic analys is supports the following summary conclusions:

 Some degree of HRI is already economic fo r high heat rate – high coal cost EGUs

 If a fleet-wide average 6% HR I is technically feasible, it would also be economic on the basis of fuel savings alone, before consid eration of the value of the associated CO2 emission reductions, on a fleet-wid e basis at today’s coal prices if the associated average capital cost is about $75/kW or less.

 If a fleet-wide average 6% HRI is technically feasible, and the associ ated average capital cost is as much as $100/kW, 6% HRI coul d become economic on the basis of fuel savings alone, before cons ideration of the value of the associated CO2 emission reductions, if/when average coal prices rise to about $3.25/MMBtu (IPM projects coal at $2.62/MMBtu in 2020).

 Even at a capital cost of $100/kW an d an IPM projected 2020 coal price of $2.62/MMBtu, the fleet-wide cost of CO 2 

### reduction via 6% HRI would be a relatively low $7.7/tonne. Thus, although there is currently some uncertain ty associated with the costs of achieving a particular fleet-wide amount of HRI, it is clear that HRI is an available low-cost approach to CO 2 

### reduction for existing coal-fired EGUs

Definitions/Abbreviations Btu British thermal unit

capacity factor electricity generation expressed as a percentage of maximum electricity generation (i.e., actual generation / maximum potential generation) CO 2 carbon dioxide EGU electric generating unit EIA Energy Information Administration EPA Environmental Protection Agency heat input amount of energy consumed in a combustion unit (e.g., boiler) expressed in Btu heat rate improvement decrease in the amount of heat input required to generate 1 kWh of electricity
heat rate gross heat input required to genera te 1 kWh of electricity, expressed in gross Btu/kWh. MMBtu million Btu

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37 MW megawatt PC pulverized coal (boiler) RSD Relative standard deviation

S & L report Sargent & Lundy engineering study on the potential heat rate improvement from equipment upgrades (EPA 2009 version) [Available at: http://www.epa.gov/airmarket/res ource/docs/coalfired.pdf]

start a startup event in which an EGU begins combusting fossil fuel and generates some measurable amount of electricity before ceasing fossil fuel combustion unit-year data for one EG U over a one year period



### Docket Datasets

Name Description hour_QA_data.txt 2002-2012 hourly dataset hour_QA_regression_data.txt 2002-2012 hourly dataset for regression analysis units_885.txt List of study units and characteristics year_bin_10_50_data.txt 2002-2012 unit-year binned results at 10 – 50% difference options

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38 HRI Partial Bibliography PowerEng 2002, “Heat Rate Optimization Pays Dividends,” Power E ngineering, January 1, 2002, available at http://www.power-eng.com/art icles/print/volume-106 /issue-1/features/heatrate-optimization-pays-dividends.html NETL 2008, Reducing CO 2 

### Emissions by Improving the Efficien cy of the Existing Coal-fired Power Plant Fleet, DOE/NETL-2008/1329, July 2008 NETL 2009, Opportunities to Improve the Efficien cy of Existing Coal-fired Power Plants, Workshop Report, NETL July 2009, available at http://www.netl.doe.gov/energyanalyses/pubs/NETL%20Power%20Plant%20Eff iciency%20Workshop%20Report%20Final.pdf NETL 2010, Improving the Thermal Efficiency of Co al-Fired Power Plants in the United States, DOE/NETL Technical Workshop Repor t, February 2010, available at http://www.netl.doe.gov/File%20Lib rary/Research/Energy%20Anal ysis/Publications/ThermalEf ficCoalFiredPowerPlants-TechWorkshopRpt.pdf NETL 2010a, Improving the Efficiency of Coal -Fired Power Plants for Near Term GHG Emissions Reductions, DOE/NETL-2 010/1411, April 2010, available at http://www.alrc.doe.gov/energy-analyses/ref shelf/PubDetails.aspx?Action=View&PubId=307 Sargent & Lundy 2009, Coal-Fired Power Plant H eat Rate Reductions, SL-009597, Final Report, January 2009, available at http://www.epa.gov/airmarkets /resource/docs/coalfired.pdf Storm 2009, “Applying the Fundamentals for Best H eat Rate Performance of Pulverized Coal Fueled Boilers, Storm Technologies, Inc, EPRI 2009 Heat Rate Conference, available at http://www.stormeng.com/pdf/EPRI2009HeatRateConference%20FINAL.pdf NRDC 2013, Closing the Power Plant Carbon Po llution Loophole, NRDC Report R:12-11-A, March 2013 available at http://www.nrdc.org/air/pollution-st andards/files/pollution-standardsreport.pdf Lehigh 2009, Reducing Heat Rates Of Coal-Fired Power Plants, Lehigh Energy Update, January 2009, available at http://www.lehigh.edu/ ~inenr/leu/leu_61.pdf ESC/OnLocation, Efficient Heat Rate Benchmarks for Coal-Fired Generating Units, draft, B. Roberts, Economic Sciences Corporation, L Goudarzi, OnLocation, Inc., 1998, available at http://www.onlocationinc.com/heatratepaper.pdf CRS 2013, Increasing the Efficiency of Existi ng Coal-Fired Power Plants, Congressional Research Service, December 2013, available at http://www.fas.org/sgp/crs/misc/R43343.pdf Evonik/VGB 2008, “Power Plant Performance Re porting and Improvement under the Provision of the Indian Energy Conservation Act – Output 1.1”, Evonik/ VGB 2008, available at http://www.emt-india.net/Power PlantComponent/Output1.1/Output1.1.pdf IEA 2010, Power Generation from Coal - Measuri ng and Reporting Efficiency Performance and CO 2 

### Emissions, OECD/IEA-CIAB 2010, available at http://www.iea.org/ciab/paper s/power_generation_from_coal.pdf EPRI 2009, Renewed Interest in Reducing Heat Rate, EPRI Jour nal, Spring 2009, available at http://mydocs.epri.com/docs/Corpor ateDocuments/EPRI_Journal/2009- Spring/1019287_Heat%20Rate.pdf

### DRAFT April 4, 2014

39 EPRI/Korellis 2011, Identifying Ways to Improve Plant Heat Rate, Energy-Tech Magazine, March 2011, available at http://www.energy-tech.com/article.cfm?id=30528 EPRI 2011a , Opportunities to Enhance Electr ic Energy Efficiency in the Production and Delivery of Electricity, EPRI Technical Report 1024651, November 2011, available at http://www.google.com/url?sa=t&rct=j&q=& esrc=s&frm=1&source= web&cd=1&ved=0CCsQF jAA&url=http%3A%2F%2Fwww.pserc.wisc.edu%2 Fdocuments%2Fpublica tions%2Fspecial_in terest_publications%2FEPRI_Electricit y_Use_Report_Final_1024651.pdf&ei=Qo9yUvmwMY Xb4AOZz4GYAw&usg=AFQjCNElzekbt oSNCR5SKFwkfbKx83p0Uw&bvm=bv.55819444,d. dmg RFF 2013, Regulating Greenhouse Gases from Coal Power Plants under the Clean Air Act, RFF DP 13-05, February 2013, available at http://www.rff.org/RFF/ documents/RFF-DP-13-05.pdf

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1 

## Chapter 6: Fuel Switching
Coal-to-Natural Gas Switching

Introduction
Firing natural gas in a boiler desi gned for coal-fired generation is one approach to reducing the output-based CO 2 

### emissions rate (lbs/MWh) in these boilers. The CO 2 

### emission rate is reduced when natural gas is substituted for coal becau se the gas has a much higher percentage of hydrogen and a lower percentage of carbon than th e coal it replaces. When quantities of gas and coal are burned with oxygen from air to produc e the same amounts of heat, the higher hydrogen content of natural gas produces more water vapor (H 2 

### O) than coal, but far less CO 2 

### . The discussion below focuses solely on the conve rsion of an existing coal-fired boiler to burn natural gas instead of, or along with, coal. There are other tec hnical options for gas substitution in an existing coal-steam EGU that are not examined in any detail here. They include:

 Repowering an existing coal EGU by providing heat input to the boi ler from the exhaust of a newly installed gas turbine generator; and,

 Gasification of coal, producing substitute natu ral gas (SNG) that prov ides heat input to the existing coal-fired boiler.
These other options have higher capital cost and thus would not be as economic as the direct substitution of natural gas in an existing coal boiler, for reasons th at will become apparent in this analysis.
This chapter evaluates the cost-effectiveness of widespread adoption of coal-to-gas switching at a national level for the purpose of setting CO 2 

### emissions goals consistently in each state.
Description of Technology
Engineering Considerations
Most existing coal-fired EGU boilers can be modi fied to switch to 100% gas input, or to co-fire gas with coal in any desired proportion. This tr ansition typically require s at least some plant modifications and might have some negative imp act on the efficiency of the unit as described later in this chapter.

### DRAFT April 4, 2014

2 A conversion from coal to gas firing first requires either an existing natu ral gas delivery system
to the boiler or the installation of a new gas pipeline to serve th e boiler. While it is sometimes assumed that a need to install a new gas pipe line would render the conv ersion uneconomic, this analysis will show that the cost of a new gas pipelin e is not likely to be th e determining factor for the project’s economic merit, gi ven the significance of the cha nge to the cost of fuel for generation from the converted boiler.
Conversion to natural gas firing in a coal-fired boiler typically involves installation of new gas burners and supply piping, modi fications to combustion air ducts and control dampers, and possibly modifications to the boiler’s steam superheater, reheater, and economizer heating
surfaces that transfer heat from the hot flue gas exiting the boiler furnace. The conversion may
also involve some modificati on of downstream air pollution emission control equipment. Engineering studies are performed to assess ch anges in furnace heat absorption and exit gas temperature; material changes affecting heat tr ansfer surfaces; the need for sizing of flue gas recirculation fans; and operational changes to soot blowers, spray flows, air heaters, and emission
controls.
Whether co-firing with coal or switching completely to natural gas, boilers will become less efficient due to the high hydrogen content of na tural gas. When combusted, the additional hydrogen yields increased moisture content (water vapor) in th e flue gas. The increased moisture content, in turn, results in additional heat lost up the stack in stead of being directed towards electricity generation. Additionally, depe nding on the design of the boiler and extent of modifications, some boilers may incur some derate (reduction in generating capacity) in order to maintain steam temperatures at or within design limits, or for other technical reasons.

Even with a decrease in boiler efficiency, the over all net output efficiency of a coal-steam boiler EGU that switches from coal to natural gas fi ring may change only slig htly, depending on how much auxiliary load is converted to net output by avoiding the need to run coal pulverizers, conveyors, ash sluice pumps, and relevant air pollution control equipment (e.g., PM and SO 2 

### controls).

Fuel Considerations
Delivery of natural gas via pipeline is critical for conversion of a coal-fired boiler to a gas-fired
boiler. Some coal boilers are connected to the natural gas pipe line network for purposes of using

### DRAFT April 4, 2014

3 gas as a startup fuel, or are located at facilities with onsite gas-fired generators. These boilers are likely able to co-fire to some degr ee with gas (at least 10% total output 1 

### ) without constructing additional gas pipeline capacity. For purposes of this analysis, the EPA conservatively assumed that gas use of 10% or greater at these boilers, or any gas use at boilers without an existing gas pipeline, would require construction of additional pipeline capacity.
Unlike coal, natural gas cannot be stored in quan tities sufficient for sustained utilization on site. To the extent that firm (uninterruptible) gas supply is contractually unavailable or costprohibitive, any potential interruption in gas su pply could impact the ability of the unit to continue operating w ithout increasing its CO 2 

### emissions rate (since it would likely need to
substitute more CO 2 

### -intensive fuel for the unavailable natu ral gas). Additionally, for boilers that switch to 100% gas, interruption in gas impacts the ability of th e unit to continue generating at all if gas is unavailable. For these reasons, an EGU switching to a large percentage of gas use may elect to install more than one new gas s upply pipeline from separa te sources. Although the EPA assumes the addition of one gas pipeline in the simplified cost analysis presented below, it will be seen that pipeline cost will generally not be the main driver of economic feasibility.
Cost and Performance Impacts of Coal-to-Gas Switching
The analysis described in this section presents a hypothetical conversion of a boiler from burning 100% coal to burning varying proportions of ga s (10%, 50%, and 100%). The capital cost of modifying a coal boiler to switch to natura l gas includes the new gas burners and piping, combustion air ductwork and control damper modifications, air heater upgrades, gas recirculating fans, control systems modifications, and other site-specific modifications, as well as any pipeline installation costs th at would be necessary to supply the unit’s assumed level of gas combustion following the conversion.
For this analysis, the EPA assumes capital cost s for pulverized coal (PC) and cyclone boiler
modifications are as follows 2 

### : $/kW = 267*(75/MW) 0.35 

### (pulverized coal)

1 Based on assumed use of Class 1 igniters (10% of burner capacity) as defined in NFPA 85 Boiler and Combustion Systems Hazards Code.
2 EPA assumptions on costing and performance associated with coal

‐ to

‐ gas conversion and pipeline additions in this analysis are generally consistent with assumptions presented and discussed in EPA’s power sector modeling documentation, Chapter 5.7, at: http://www.epa.gov/airmarkets/progsregs/epa

‐ ipm/docs/v513/Chapter_5.pdf

### DRAFT April 4, 2014

4 $/kW = 374*(75/MW) 0.35 

### (cyclone)
Based on the above formula, a 500 MW pulverized coal unit would have a capital cost of $137/kW to convert the boiler such that it coul d burn any proportion of natural gas. For this illustrative example, to support 100% gas combustion we assume that a 50-mile gas pipeline 3 

### at $50 million, 4 

### or $100/kW for a 500 MW unit, is also required, which raises the unit’s total capital cost for conversion to $237/kW. Black & Veat ch also used a similar cost level in a recent case study. 5 

### At a 14.3% capital charge rate 6 

### and 75% annual capacity fact or, the total capital cost in this example equates to an annualized capital cost of about $5/MWh. Th is $/MWh capital cost is relatively insignificant compared to the increase in fuel cost discussed later.
Due to a reduced need for operators, maintenan ce materials, and maintenance staff, fixed O&M costs are reduced by 33% as a result of switching from coal to 100% gas. Similarly, variable O&M costs are reduced by 25% due to reduced waste disposal, redu ced auxiliary power requirement, and miscella neous other costs.
EPA also assumed for this analysis that ther e would be no derate in the net EGU output, and estimated that the impact on net heat rate for an average unit would be a 3% increase for a switch from coal to 100% natural gas firing. The assumed 3% increase in net heat rate is conservative compared to the 2% assumption used by Black & Veatch in their previously mentioned case study.
Cost of Fuel
For this analysis, the EPA uses base case projec tions for delivered gas prices that are about double projected delivered coal prices on average ($2.62/MMBTU for coal, $5.36/MMBTU for

3 Based on EPA analysis, the majority of existing coal units would require less than 50 miles of new gas pipelines to switch fuels from coal to 100% natural gas. See Chapter 5 and Table 5

‐ 22 of Documentation for EPA Base Case v.5.13 Using the Integrated Planning Model, available at: http://www.epa.gov/airm arkets/progsregs/epa

‐ ipm/BaseCasev513.html
4 For those plants that require additional pipeline capacity, the average capital cost of constructing new pipelines is assumed to be approximately $1 million per mile of pipeline built, which is consistent with assumptions used in EPA’s IPM modeling.
5 A Case Study on Coal to Natural Gas Fuel Switch, Black & Veatch, Power

‐ Gen International, December 2012, available at http://bv.com/redirects

. 6 Capital charge rate at 14.3% is the average of the regulated utility and unregulated merchant rates as used in IPMv5.13 for environmental retrofits having a 15 year book life.

### DRAFT April 4, 2014

5 gas). 7 

### As a result, the fuel cost for a typical c onverted boiler burni ng 100% gas is expected to be at least double its prior fuel cost on an output basis as well ($27/MWh for coal, $57/MWh for gas). 8,9 

### Compared to the estimated $5/MWh capita l cost impact presented above, a $30/MWh
increase in fuel cost would make the difference in fuel costs the most signifi cant driver of project economics when switching from coal to gas in a coal boiler. 10 

### This difference would increase with higher gas prices, which w ould be projected to result from an increase in overall gas demand caused by widespread a doption of gas co-firing.

Emission Reduction Potential

The CO 2 

### reduction potential is directly related to the amount of gas co -fired, and is due largely to
the different carbon intensities of ea ch fuel. More reductions in CO 2 

### rate are achieved at higher levels of gas co-firing as shown in Table 6- 1. At 10% gas co-firing, the net emissions rate (lbs/MWh net) of a typical unit would decrease by approximately 4%. At 100% gas co-firing, the net emissions rate (lbs/MWh net) of a t ypical unit would decrease by approximately 40%.

Table 6-1. CO 2 

### Rates at Various Levels of Natural Gas Co-Firing

Case Heat Rate CO 2 

### Rate (lbs/MWh net) Reduction in CO 2 

### Rate from 100% Coal (lbs/MWh net) 100% Coal 10,340 2,108 N/A 10% Gas 10,370 2,021 4% 50% Gas 10,490 1,673 21% 100% Gas 10,640 1,239 41%


### In addition to reducing CO 2 

### emissions, natural gas co-firing at a coal-fired steam EGU will generally also reduce criteri a air pollution. Reducing CO 2 

### and criteria air pollution will result in

7 EPA Base Case 5.13, projections for 2020 8 This estimated fuel cost also accounts for the decrease in efficiency that results from switching from coal to gas in

a boiler, as well as the decrease in parasitic power consumption. 9 Combusting natural gas using combined

‐ cycle turbine technology can remain economically attractive notwithstanding these types of fuel price differentials because combined cycle turbine technology converts a substantially higher share of the fuel’s heat input into electricity output as compared to boiler technology. The $/MWh impact of a higher gas price in that instance is significantly mitigated by higher MWh output produced for

a given amount of heat input from the fuel purchased. 10 This demonstration assumes that the converting boiler in question remains a “price taker” in the fuel marketplace, such that the projected gas and coal prices would be unaffected by this hypothetical unit’s potential decision to convert. However, if enough other units might be expected to make similar conversions, the aggregate increased demand for natural gas would be likely to further increase the price differential between coal and gas, making fuel costs an even more influential factor in the evaluation of such a project’s economic merit.

### DRAFT April 4, 2014

6 climate benefits and human health co-benef its. The impacts of th ese pollutants on the
environment and health are discu ssed in detail in Chapter 5 of th e RIA for this proposed rule.
For this analysis, EPA estimated the PM 2.5 

### -related human health co-benefits of SO 2 

### , NO X 

### , and
direct-PM 2.5 

### emission reductions attributable to a range of natural gas co-firing levels at an illustrative coal steam unit burning bituminous coal in 2020. 11 

### The estimated monetized cobenefits do not include climate benefits or health effects from direct exposure to NO 2 

### , SO 2 

### , and HAP; ecosystem effects; or visibility impa irment. Only the unit-level emissions of SO 2 

### , NO X 

### and
direct-PM 2.5 

### are considered in this illustrative ex ercise. Additionally, emissions from the extraction and transport of the fuels used by thes e technologies are not co nsidered. Furthermore, there may be differences in upstream greenhouse gas emissions (in particular, methane) from different technologies but those were not quantifie d for this assessment. The estimated avoided emissions under 10% gas co-firing and a 100% switch to gas are pr esented Table 6-2.

Table 6-2. Avoided Emissions at Various Levels of Co-Fir ing, based on Illustrative Unit (lbs/MWh net)

10% Gas 100% Gas SO 2 0.3 3.1 NO X 0.2 2.04 PM 2.5 0.02 0.2



### To estimate human health co-benefits for this illustrative coal steam unit, the EPA used PM 2.5 

### - related benefit-per-ton estimates for SO 2 

### , NO X 

### , and direct-PM 2.5 

### emission reductions described in detail in Chapter 5 of the RIA for this proposal. To estimate the benefits associated with cofiring, we determine the emission reductions for co -firing in Table 6-2 an d apply the 2020 social benefit values discussed in Chapter 5 of the RIA for this proposal. Specifically, we multiply the
reduction in SO 2 

### , NO X 

### , and direct-PM 2.5 

### emissions by the PM 2.5 

### -related benefit per-ton estimates, and add those values to get a measure of 2020 benefits. Table 6-3 shows the PM 2.5 

### -related benefits expected based on the estimated emission reductions that would occur in this illustrative example. These estimates are purely illustrative as the EPA does not assert a specific location for the illustrative electricity ge neration technologies and is ther efore unable to specifically

11 The illustrative unit in this analysis was assumed to be a 500 MW coal

‐ steam unit burning bituminous coal with a heat rate of 10,339 btu/kWh (net) operating at 75% capacity factor. Furthermore, this unit was assumed to operate a wet scrubber, cold

‐ side ESP, and SNCR.

### DRAFT April 4, 2014

7 determine the population that would be affected by their emissions. Therefore, the benefits for any specific unit can be different than the estimates shown here.

Table 6-3. Rounded PM2.5-related Co-benefits ($/MWh net) of Gas Co-firing (2011$)

Health Co

‐ benefit Discount Rate 3% Discount Rate 7% Discount Rate
Gas Co

‐ firing 10% $6.5 to $15 $5.9 to $13 Gas Co

‐ firing 100% $67 to $150 $61 to $140

Note: All estimates are rounded to two significant figures. Co

‐ benefits are based on national benefit

‐ per

‐ ton estimates for directly emitted PM 2.5 and PM 2.5 precursors, SO 2 and NO X . It is important to note that the monetized health co

‐ benefits do not include reduced health effects from ozone or direct exposure to NO 2 , SO 2 , and HAP; ecosystem effects; or visibility impairment. Emissions of directly emitted particles are disaggregated into EC+OC or crustal components using the method discussed in Appendix. 12 5A of the RIA for this proposal. The health co

‐ benefits reflect the sum of the PM2.5 co

‐ benefits and reflect the range based on adult mortality functions (e.g., from Krewski et al. (2009) to Lepeule et al. (2012)).



### The precise incremental health co-benefits a ssociated with lower emissions would depend primarily on the location of the co-firing unit, th e specific types of coals that natural gas would replace, and the pollution controls installed on that unit. This illustrative assessment is unable to account for these characteristics. However, th ese factors will not ch ange the qualitative conclusion. There will always be incremental human health co-benefits associated with co-firing natural gas in an existing coal steam boiler, independent of the location, coal type, and operating pollution controls.
A related beneficial use of natural gas in exis ting coal boilers can be via gas reburning, a NOx reduction technology. 13 

### Gas reburning involves firing natura l gas (between 10 and 25% of total heat input) above the primary combustion zone in the boiler furnace. This upper-level firing creates a slightly fuel-rich zone. NOx produced in the primary zone of the furnace is "reburned" in this zone and converted to molecular nitrogen and other reduced nitrogenous species. Overfire air is injected downstrea m of the reburn zone to burn out th e remaining combustibles and convert

12 Krewski D.; M. Jerrett; R.T. Burnett; R. Ma; E. Hughes; Y. Shi, et al. 2009. Extended Follow

‐ Up and Spatial Analysis of the American Cancer Society Study Linking Particulate Air Pollution and Mortality. HEI Research Report, 140, Health Effects Institute, Boston, MA. Lepeule, J.; F. Laden; D. Dockery; J. Schwartz. 2012. “Chronic Exposure to Fine Particles and Mortality: An Extended Follow

‐ Up of the Harvard Six Cities Study from 1974 to 2009.” Environmental Health Perspectives, July, 120(7):965

‐ 70. 13 DOE/NETL 2001, Evaluation of Gas Reburning and Low

‐ NOx Burners on a Wall

‐ Fired Boiler, DOE/NETL

‐ 2001/1143, February 2001, available at http://www.netl.doe.gov/File%20Libra ry/Research/Coal/major %20demonstrations/cctdp /Round3/GRLNBPPA.pdf

### DRAFT April 4, 2014

8 the reduced nitrogenous species to molecula r nitrogen. The heat input from gas would approximately substitute for a similar heat input from coal, thus reducing CO 2 

### and other coal emissions in a manner similar to ga s co-firing as discussed above.

Cost of Reductions and Cost Effectiveness This analysis examines the average $/tonne 14 

### cost of avoided CO 2 

### that results from applying a range of natural gas co-firing levels to a typica l baseload coal boiler. We capture the capital costs of boiler modifications and new pipe line construction (assumi ng 50 miles of new pipeline), 15 

### decreased FOM and VOM costs, and incremental fuel costs (based on IPMv5.13 Base Case average delivered fuel price projections for coal and gas in 2020). For a typical coal boiler at current base case fuel prices, the average cost of avoided CO 2 

### ranges from $83/tonne for 100% gas switch to $150/tonne for co-firing at 10% (see Table 6-4).
Table 6-4. Average Cost of Avoided CO 2 

### and CO 2 

### Emission Rate Reductions from 100% Coal at Various Levels of Natural Gas Co-Firing at Base Case Projected Gas Price ($5.36/MMBtu)

Case Average Cost of Avoided CO 2 

### ($/tonne) Change in CO 2 

### Rate from 100% Coal (lbs/MWh net) 100% Coal N/A N/A 10% Gas 150 4% 50% Gas 91 21% 100% Gas 83 41% Note: Based on a typical 500 MW bituminous coal steam unit operating at 75% capacity factor. Assumes construction of new 50

‐ mile pipeline. EPA estimated reduced total capital costs for the 50% and 10% gas cases; for example, total capital cost for 10% gas was estimated to be about one

‐ half of the capital costs for the 100% gas
case. 

### However, widespread adoption of gas co-fir ing would increase overall gas demand and place upward pressure on the natural gas price, which would consequently increase the average cost of
avoided CO 2 

### of a potential bo iler conversion.

Conclusion

14 This document uses “tonne” to refer to a metric tonne. All control costs in this analysis are presented in dollars per metric tonne, or “$/tonne.”
15 Based on EPA analysis, the majority of existing coal units would require less than 50 miles of new gas pipelines to switch fuels from coal to 100% natural gas. See Chapter 5 and Table 5

‐ 22 of Documentation for EPA Base Case v.5.13 Using the Integrated Planning Model, available at: http://www.epa.gov/airm arkets/progsregs/epa

‐ ipm/BaseCasev513.html

### DRAFT April 4, 2014

9 Switching from coal to gas is a re latively costly approach to CO 2 

### reductions at existing coal steam boilers when compared to other measures such as heat rate improvements and re-dispatch of generation supply to other ex isting capacity with lower CO 2 

### emission rates. Moreover, this analysis shows that coal-to-gas conversion of an existing boiler is less efficient than constructing a new natural gas combined cycle (NGCC) turbine in its place. For example, replacing the coal steam plant discussed above with a ne w NGCC facility would reduce the net CO 2 

### emission rate of the generating capacity by 62% at a cost of about $50/tonne of avoided CO 2 

### under the base case projected gas price and a bout $81/tonne of avoided CO 2 

### at a future gas price 50% higher than the base case projection. [INSERT CROSS-REFERENCE TO LOCATION IN RULE
MATERIALS WHERE WE EXPLAIN WHY WE ARE NOT CONSIDERING NEW NGCC
POTENTIAL TO REPLACE EXISTING COAL AS A REDUCTION MEASURE FOR CRAFTING STATE GOALS.]
The EPA is considering cost-effect iveness at a national level for th e purpose of setting emissions goals consistently in each state. While this analysis suggests that co st-effective reductions of
CO 2 

### are not available on a national basis from widespread adopti on of natural gas co-firing, it does not preclude the potential for individual EGUs to utilize co-firing as a way to reduce CO 2 

### and other emissions, nor does it prec lude states from factoring in that unit-level potential into the design of state plans for compliance with the 111(d ) standard. EPA notes th at there are utilities that see merit in converting some existing coal un its to burn 100% gas, and several are currently doing so. 16,17

16 Reuters 2014, “Southern to repower three Alabama coal power plants with natgas,” Reuters U.S. Edition, January 16, 2014 , available at http://www.reuters.com/ar ticle/2014/01/16/utilities

‐ southern

‐ alabama

‐ idUSL2N0KP1WA20140116 17 Dominion 2012, “Dominion Virginia Power Proposes To Convert Bremo Power Station From Coal To Natural Gas,” Dominion News, September 5, 2012, available at http://dom.mediaroom.com/2012

‐ 09

‐ 05

‐ Dominion

‐ Virginia

‐ Power

‐ Proposes

‐ To

‐ Convert

‐ Bremo

‐ Power

‐ Station

‐ From

‐ Coal

‐ To

‐ Natural

‐ Gas

### DRAFT April 4, 2014

10 Biomass Co-firing

Introduction
Co-firing biomass in existing boile rs designed for coal-fired gene ration is another approach to potentially reduce the output-based CO 2 

### emissions rate (lbs/M Wh) of these boilers. In the analysis presented in this techni cal support document, the physical CO 2 

### emissions rate at the boiler stack could increase or decrease, depe nding on the amount of coal energy replaced by biomass energy and differences in the properties of a selected biomass and the coal it replaces. 18



### There are many possible combinations of coals a nd biomass types that could be co-fired. Sitespecific economics and accessibility would determine which combinations might actually be feasible. This TSD analysis does not attempt to estimate an economically feasible national average increase or decrease in CO 2 

### emission rate via biomass co-f iring. Instead, this analysis simply employs one reasonably representative case to evaluate the cost effectiveness of biomass energy substitution in reducing the physical CO 2 

### emission rate based only on the CO 2 

### coming from coal. This analysis indicates that while th e co-firing of biomass with coal is technically feasible as a means of reducing the coal-based CO 2 

### emission rate due to the substitution of biomass for coal, it has limited economic feasibili ty due to the generally higher cost of energy from biomass as compared to coal. This general finding largely explains the very limited amount of biomass co-firing currently pract iced in the U.S. It is also c onsistent with findings by others, including a study by the State of Maryland 19 

### that concluded as follows:
“Due to the higher cost of biomass fuels when compared to coal, cofiring with biomass
will lead to an increase in fuel costs. Without consideration for any environmental benefits, it is unlikely that any Maryland coal -fired facility would make the investments required to cofire with a more e xpensive and less efficient fuel.”
Based on the basic analysis of the cost effec tiveness of biomass energy substitution in reducing the physical CO 2 

### emission rate based only on the CO 2 

### coming from coal presented below, the

18 Fuel properties particularly affecting relative CO 2 emission rates are: higher heating value, carbon and hydrogen contents, and as

‐ fired moisture content. 19 The Potential for Biomass Cofiring in Maryland, Maryland Department of Natural Resources, March 2006, (pg 53) http://esm.versar.com/pprp/biblio graphy/PPES_06_02/PPES_06_02.pdf

### DRAFT April 4, 2014

11 EPA concludes in this TSD that biomass co-f iring would not be a cost-effective measure on which to base state goals. 20



### This TSD’s analysis indicates that while the co -firing of biomass with coal is technically feasible, in some cases it can yield incr eases in the stack emission rate of CO 2 

### (lb/MWh) and has limited economic feasibility given the delivered cost of available biomass versus the cost of coal.
Description of Technology
Engineering/Economic Considerations
The technical feasibility of biomass co-firing in existing co al-fired boilers has been thoroughly investigated in many research and engineering stud ies, as well as in test burns at coal power plants in the U.S. and globally. 21 

### It has been demonstrated that the boiler and rela ted systems of almost any existing coal-fired EGU can accept or be modified to support co -firing of at least some small percentage of biomass. In some cas es, major modifications can be made to support a
switch to 100% biomass.
A decision to actually modify an existing coal -fired boiler for biom ass co-firing at any percentage level depends on numerous technical and economic factors, including reliable availability of suitable biomass at an economic cost; adequate onsite space for biomass receiving, storage, preparation, and handling systems; poten tial corrosive effects of biomass ash in the boiler furnace; potential imp acts of co-firing on boiler effi ciency even at low biomass percentages, and the likely re duction (derate) in unit generati ng output at very high biomass percentages.

20 This analysis does not include evaluation of stack biogenic CO 2 emissions relative to the net landscape and process

‐ related carbon fluxes associated with the production and use of the biogenic feedstocks combusted. Issues related to methods for assessing biogenic CO 2 emissions from stationary sources are currently being evaluated by the EPA. In general, the overall net atmospheric contribution of CO 2 resulting from the use of a biogenic feedstock by a stationary source, such as an EGU, will ultimately depend on the stationary source process and the type of feedstock used, as well as the conditions under which that feedstock is grown and harvested. In September 2011, the EPA submitted a draft Accounting Framework to the Science Advisory Board (SAB) Biogenic Carbon Emissions (BCE) Panel for peer review. The SAB BCE Panel delivered its Peer Review Advisory to the EPA on September 28, 2012. In its Advisory, the SAB recommended revisions to the EPA's proposed accounting approach, and also noted that biomass cannot be considered carbon neutral a priori, without an evaluation of the carbon cycle effects related to the use of the type of biomass being considered.
21 See Partial Bibliography

– Biomass Co

‐ firing at end of this section.

### DRAFT April 4, 2014

12 There are considerable physical differences between coal and biomass that will generally limit the extent to which biomass can be reasonably us ed to replace coal in a boiler. For example, compared to most coals, many solid biomass fuels have both a signifi cantly higher as-fired moisture content and a significantly lower heatin g value per unit of weig ht. Most solid biomass fuels are also significantly less dense than most co als. For example, a typical biomass might have twice the moisture, half the heating value, and less than half the density of coal. 22 

### Important consequences of these physical differences are th at the weight of biomass needed to provide a given amount of heat energy could be twice th e weight of the coal it replaces, and the volume (cubic feet) of biomass needed could be four-t o-eight times the volume of coal replaced.
Biomass requires space for storage after delivery to a facility, and the length of time that the biogenic material would remain on site prior to use can differ. For example, wood chips could be delivered year-round while crop residue delivery would follow sp ecific seasons in which the crop was grown. As noted above, the four-fol d or greater increase in volume occupied by biomass relative to coal means that the necessary additional storage space could be large. Stored biomass can be at even greater risk of spontaneo us combustion than stored coal; this may limit the safe height of biomass piles and fu rther increase storage area requirements. 23



### The volumetric differences alone can have other unexpected cons equences. For this analysis, experienced EPA engineering sta ff estimated that a 500 MW baselo ad coal plant co-firing 10% biomass and receiving biomass deliveries 10 hours per day and 5 days per week would require a 20-ton truck delivery to the plan t every 10 minutes, in addition to the ongoing coal deliveries. Limiting traffic issues may arise in some situatio ns. Also, because of the low energy density of biomass and its relatively higher transportation cost pe r unit of delivered energy, it may only be economically viable to transport biomass a limited distance from where it is grown. This could limit the both the percentage of biomass co-firing in a sing le boiler and the maximum MW output from biomass at a single site.
The relatively higher moisture content and lo wer heat content of biomass reduces boiler efficiency, and typically requires a derating in unit generation at very high co-firing percentages as furnace volume and boiler fan capacities become inadequate.

22 Biomass Energy Data Book ‐ Edition 4, October 2012, DOE

‐ EERE

‐ ORNL, http://cta.ornl.gov/bedb/index.shtml 23 Properties of Wood Waste Stored for Energy Production, Purdue University, 2011, http://www.extension.purdue.edu/extmedia/ID/ID

‐ 421

‐ W.pdf

### DRAFT April 4, 2014

13 For all of the above reasons, the EPA assumed for this analysis th at coal-steam EGU boilers will generally only co-fire with biomass to a limited degree. While the actual level at which any plant can co-fire with biomass is highly site-speci fic, this analysis adopts the assumption used in EPA’s fleet wide IPM modeling of the electr ic power sector: a reasonable average limit on biomass co-firing is up to 10% on any single boil er, not to exceed 50 MW total biomass powered output at an individual plant si te. This amount of co-firing ha s been used as representative practical limit in other studies as well. 24



### Costs and Performance Impacts of Retrofitted Biomass Co-firing
For this analysis the EPA adopted capital and O&M costs, and performance impacts for retrofitted biomass co-firing capability that are approximately representati ve of EPA assumptions used in its IPM modeling and discus sed in the documentation for IPM v.5.13. 25



### EPA estimated that the capital cost to install 50 MW of biomass co-firing capability would be at least $10 million. 26 

### As applied to a 500 MW coal unit, th e minimum cost of this 10% co-firing capability would then be $20/kW. Fixed O&M cost was estimated by EPA engineering staff to be 10% greater than with co al alone, and variable O&M cost was estimated to remain unchanged.
The heat rate impact (Btu/kWh) of 10% biomass co-firing as estimated by EPA engineering staff for this analysis was an increase of slightly more than 1% compared to coal alone. At low biomass cofiring rates, this fact or slightly affects calculated bi omass fuel consumption and any
associated CO 2 

### emission from biomass.
Cost of Fuel
For this analysis, the EPA uses a delivered bi omass cost of $4/MMBtu, representative of delivered woody crops grown specifica lly for energy-generating combustion, 27 

### and roughly 50%

24 The Potential for Biomass Cofiring in Maryland, Maryland Department of Natural Resources, March 2006, http://esm.versar.com/pprp/biblio graphy/PPES_06_02/PPES_06_02.pdf
25 See Sec 5.3, pg 5

‐ 19 at: http://www.epa.gov/airm arkets/progsregs/epa

‐ ipm/docs/v513/Chapter_5.pdf
26 Generally consistent with EPA assumptions in IPM modeling; also see the following source using the same retrofit capital cost assumption: Cofiring Biomass and Coal for Fossil Fuel Reduction and Other Benefits

– Status of North American Facilities in 2010, USDA, August 2012, http://www.fs.fed.us/ pnw/pubs/pnw_gtr867.pdf
27 Average biomass price as projected by EPA modeling in IPMv5.13 Base Case

### DRAFT April 4, 2014

14 greater than IPM projected 2020 average delivered coal costs. 28 

### This analysis also considers a sensitivity scenario assuming a higher $6/MMBtu biomass price.
The EPA recognizes that the cost of biomass is hi ghly site-specific, and in some cases could be largely comprised of collection and transportation cost (as is the case for opportunity fuels with little to no other market value). The transportation component depends primarily on the distance that biomass needs to be transported. For exampl e, the EPA engineering staff estimate that for a one-way distance of 50 miles with a 20-ton semi-t railer truck, transportation costs could be $10- 20/ton. For biomass at a total delivered price of $4/MMBtu with an indi cative heating value of 5,000 Btu/lb (higher heating value (HHV) basis), transportation cost in this example case could account for 25-50 percent of the total delivered biom ass cost. In any case, it is the total delivered price of biomass on a $/MMBtu basis that will pr imarily determine the economic feasibility of biomass co-firing.

Emission Reduction Potential

The CO 2 

### reduction potential of biomass co-firing is directly relate d to the amount and type of
biomass co-fired and is due to the differen ce in heating value, moisture content and hydrogen/carbon ratios 29 

### for a selected biomass fuel compared to the particular coal it replaces. The types of biomass typically available to E GUs in the United States include woody-based feedstocks such as wood chips, forest industr y byproducts, and to a le sser degree agricultural crop residues, as well as emerging dedicated ener gy crops such as switchgrass and short-rotation woody crops. 30 

### In general, when comparing coal-only versus co-firing coal with biomass, cofiring may result in either an in crease or decrease in the stack CO 2 

### emission rate.

Cost of Reductions and Cost Effectiveness

In order to evaluate cost-effec tiveness of potential reductions, the EPA first estimated the cost of
avoided coal CO 2 

### emissions in a hypothetical scenario where biomass CO 2 

### emissions are not
included in total stack CO 2 

### emissions (in effect, biogenic CO 2 

### emissions are subtracted from

28 EIA, Electric Power Annual 2012

– Electricity (Table 7.4) http://www.eia.gov/electricit y/annual/html/ epa_07_ 04.html 29 IFRF Combustion Handbook, Combustion File No. 23, What is Biomass? (Van Krevelen Diagram), http://www.handbook.ifrf.ne t/handbook/cf.html?id=23
30 Biomass Combined Heat and Power Catalog of Technologies, U.S. EPA, September 2007, http://www.epa.gov/chp/docume nts/biomass_chp_catalog.pdf

### DRAFT April 4, 2014

15 total CO 2 

### emissions measured at the stack). The es timated results presented below are based on a reasonably representati ve case using a baseload bituminous coal-fired boiler with a net heat rate of 10,340 btu/kWh that shifts from 100% bituminous coal to 90% coal and 10% biomass (assuming fuel prices of $2.62/MMBtu for coal in 2020 as projected in IPMv5.13 Base Case and $4/MMBtu for biomass as explained above). When biogenic stack emissions are not counted as part of total emissions, the cost of avoided CO 2 

### for a “typical” baseload coal boiler co-firing 10% biomass is $30/tonne. This estimated cost of avoided coal CO 2 

### emissions would increase if CO 2 

### emissions from the co-fired biomass were includ ed. At higher delivered fuel price differentials,
the cost of avoided coal CO 2 

### emissions would increase (for ex ample, at a biomass price of $6/MMBtu, cost of avoided CO 2 

### is $80/tonne if CO 2 

### emissions from biomass are not counted).

Conclusion
Replacing some coal with low levels of biomass co-firing may result in stack CO 2 

### emission
increases. 31 

### Even if biogenic CO 2 

### emissions are not counted as pa rt of stack emissions, biomass co-firing is a relatively costly approach to CO 2 

### reductions at existing co al steam boilers when compared to other measures such as heat rate improvements and re-dispatch of generation supply to other existing capacity with lower CO 2 

### emission rates.
The EPA is considering cost-effect iveness at a national level for th e purpose of setting emissions goals consistently in each state. While this an alysis concludes that cost -effective reductions of
CO 2 

### are not available on a national basis from widespread adopti on of biomass co-firing, it does not preclude the potential for individual EGUs to utilize co-firing as a way to reduce overall CO 2 

### emissions, nor does it preclude states from factori ng in that unit-level potential into the design of state plans for compliance with the 111(d) standard. 32



### Partial Bibliography for Technical Feasibility of Biomass Co-firing
(a) Briggs, J. and J. M. Adams, Biomass Combus tion Options for Steam Generation, Presented at Power-Gen 97, Dallas, TX, December 9 – 11, 1997.

31 Depending on biogenic feedstocks used and whether or not an assessment system is applied that evaluates biogenic CO 2 emissions from the stack in relation to the terrestrial carbon cycling associated with the production and use of that biogenic feedstock. 32 EPA notes that states will need to consider any future EPA finding regarding an assessment framework that considers carbon fluxes on the biogenic feedstock production landscape applied when evaluating net stack CO 2 emissions from biomass co

‐ firing.

### DRAFT April 4, 2014

16 (b) Grusha, J and S. Woldehanna, K. McCarthy, a nd G. Heinz, Long Term Results from the First
US Low NOx Conversion of a Ta ngential Lignite Fired Unit, pr esented at 24th International Technical Conference on Coal & Fuel Sy stems, Clearwater, FL., March 8 – 11, 1999.
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