Electricity: Significant Changes Are Expected in Coal-Fueled Generation, but Coal is Likely to Remain a Key Fuel Source
Released: 2012-11-28T00:00:00

Letter

Background

Because of its abundance and historically low cost, coal is an important fuel source in the United States, accounting for about 20 percent of total energy use in 2011. Nearly all coal consumed in the United States is produced domestically, and coal represents about 29 percent of all domestically produced energy. U.S. coal production generally increased since 1960 and reached its highest level in 2008. Advancements in mining technology and a shift to using surface mines to a greater extent than underground mines has boosted coal’s overall productivity and enabled production to increase even as the number of workers decreased. In 2011, half as many workers produced 24 percent more coal than in 1985, as shown in figure 1. Data from the Bureau of Labor Statistics indicate that about 86,200 people were employed in coal mining in the United States in 2011.

In the United States, coal is primarily used to generate electricity—over 90 percent of coal was used to generate about 42 percent of electricity in 2011. The amount of electricity generated using coal has generally increased since the 1960s, but decreased recently due to a combination of a decline in overall electricity demand, shifts in the relative prices of fuels, and other reasons. (See fig. 2.) Meanwhile, coal’s share of total electricity generation has fluctuated over time. EIA has stated that several factors, including low oil prices during the late 1960s—which served to increase electricity generation from oil—and the oil price shocks of the 1970s have influenced the mix of fuel sources used to produce electricity.

Two broad trends—recent environmental regulations and changing market conditions—are affecting power companies’ decisions related to coal-fueled electricity generating units. Regarding environmental regulations, as we have previously reported, since June 2010, EPA proposed or finalized several regulations that would reduce certain adverse health or environmental impacts, including impacts associated with coal-fueled electricity generating units.potentially significant implications for public health and the environment. One of the most significant regulations in terms of EPA’s estimated benefits and costs, EPA’s Mercury and Air Toxics Standards, establishes emissions limitations on mercury and other toxic pollutants. Mercury is a toxic element, and human intake of mercury, for example, through consumption of fish that ingested the mercury, has been linked to a wide range of health ailments. In particular, mercury can harm fetuses and cause neurological disorders in children, resulting in, among other things, impaired cognitive abilities. Other toxic metals emitted from power plants, such as arsenic, chromium, and nickel can cause cancer. EPA estimates that its finalized regulation would reduce mercury emissions from coal- fueled electricity generating units by 75 percent, as well as reduce SOemissions.retrofit generating units with controls to reduce pollutants and, when it is not economic to retrofit, may retire some generating units.

In response to these regulations, power companies might Regarding broader market conditions, important market drivers have been weighing on the viability of coal-fueled electricity generating units. Key among these has been the recent decrease in the price of natural gas, which has made it more attractive for power companies to build new gas-fueled electricity generating units and to utilize existing units more. In addition, slow expected growth in demand for electricity in some areas has decreased the need for new generating units. Power companies may weigh the costs of any needed investments compared with the benefits of continuing to generate electricity at a particular unit. When the costs outweigh the benefits, a power company may decide to retire a unit rather than continue to operate the unit or install new pollution control equipment.

The majority of coal produced in the United States is used domestically, though exports represent a small but recently growing fraction of U.S. coal production. In 2010, the United States exported 82 million tons of coal, which accounted for 8 percent of total production. As shown in figure 3, coal exports to European and Asian markets represented 76 percent of total U.S. coal exports in 2011. In 2011, total coal exports were up 31 percent compared with 2010, reaching 107 million tons, due largely to rising exports to Europe and Asia. This was the highest level of exports since 1991. In 2011, 35 percent of U.S. coal exports were of the types of coal typically used to produce electricity, the remainder were of metallurgical coals used in industrial processes, such as steelmaking.

To better understand the potential future of the coal and electricity industries, the federal government, private companies, and others use models to project future industry conditions, including the future use of coal. For example, EIA, IEA, and IHS Global Insight produce long-term projections of electricity generation and generation from coal. Because the future depends on a multitude of factors that are difficult to predict, EIA assesses various scenarios with different assumptions about future conditions to better understand the range of potential future outcomes. For example, EIA’s primary scenario, called its “reference” scenario, is a business-as-usual estimate based on existing policies, known technology, and current technological and demographic trends. Additional scenarios make different assumptions about fuel prices, economic conditions, and government policies, among other things. Some of these scenarios are especially relevant to the question of coal’s future, because they address factors currently affecting the industry, such as the prices of coal and natural gas—a fuel that competes with coal—and possible future policies to address climate change. Appendix II presents further information about the major assumptions behind these forecasts and scenarios.

Retirements, Retrofits, and New Construction May Result in a Smaller but Cleaner Coal- Fueled Electricity Generating Fleet

The nation’s fleet of coal-fueled electricity generating units may have less total generating capacity in the future, and the fleet may be capable of emitting lower levels of pollutants, according to available information. These changes will be driven by industry plans to retire a significant number of units, install pollution control equipment on others, and build a few, new coal-fueled units that may emit lower levels of pollutants than the current fleet’s average emissions.

Power Companies Are Planning to Retire a Significant Number of Older, Smaller, More Polluting Units

According to forecasts we reviewed, power companies may retire a significant number of coal-fueled units in the future. In its reference scenario reflecting current policies, EIA projects that power companies may retire 49,000 MW of coal-fueled capacity from 2011 through 2035 (i.e., 15 percent of coal-fueled capacity in 2011). IHS Global Insight projects that power companies may retire 76,476 MW of capacity from 2011 through 2035 (i.e., 24 percent of coal-fueled capacity in 2011).

Our statistical analysis of Ventyx data on announced retirement plans indicates that, among other things, companies are planning to retire units that are older, smaller, and more polluting. To assess the types of units that may be retired, we analyzed data on current power company plans to retire coal-fueled units. According to Ventyx data, power companies have already reported plans to retire 174 coal-fueled units with a total 30,447 MW net summer capacity through 2020—which accounted for 10 percent of coal-fueled capacity in 2011. As we have previously reported, this would be significantly more retirements than have occurred in the past–– almost twice as much coal-fueled capacity as retired in the 22 years from 1990 through April 2012. Based on our statistical analysis of these plans, power companies are more likely to plan to retire units that are older, smaller, and more polluting. (Appendix I provides further information on our statistical analysis, which included examining several other characteristics that may affect plans to retire units such as (1) whether power companies are traditionally regulated or operate in restructured markets and (2) a unit’s cost of generating electricity relative to regional prices.)

Older. Power companies’ plans indicate they are more likely to retire older coal-fueled electricity generating units than newer units. Today’s fleet of operating coal-fueled units was built from 1943 through 2012, with the bulk of the capacity built in the 1970s and early 1980s. As shown in figure 4, units that power companies plan to retire are generally older, on average 54 years old compared with units with no retirement plans that average 39 years old. Some stakeholders we interviewed said that power companies are more likely to retire older units because these units may be reaching the end of their useful lives, can be less efficient at converting coal to electricity, and can be more expensive than newer units to retrofit, maintain, and operate.

Smaller. The smaller a unit is, the more likely a power company is to be planning to retire it. (See fig. 5.) Size can be important when assessing the economics of additional investments needed to continue to operate coal-fueled units, as smaller units can be more expensive to retrofit, maintain, and operate on a per-MW basis. For example, some power companies may choose to install flue gas desulfurization units—known as scrubbers—to control SO and other air emissions. According to an EPA report, a typical 100 MW coal- fueled unit could incur capital costs 66 to 74 percent higher per MW to install a scrubber than a 700 MW unit. In addition, smaller generating units are generally less fuel-efficient than larger units. Units that are planned for retirement average 175 MW of capacity compared with units that are not planned for retirement that average 351 MW of capacity. Figure 5 shows the number of coal-fueled units by capacity in MW.

Many Units May Be Retrofitted with Pollution Control Equipment

As we reported in July 2012, power companies may retrofit many coal- fueled electricity generating units with new or upgraded pollution control equipment in response to new environmental regulatory requirements.Though the requirements and deadlines these regulations may establish for generating units are somewhat uncertain at this time, EPA’s analyses and two other studies we reviewed in our prior report suggest that one- third to three-quarters of all coal-fueled capacity could be retrofitted or upgraded with some combination of pollution control equipment, including scrubbers and other technologies to reduce SO, mercury, and other emissions. Once retrofitted with this pollution control equipment, the coal- fueled fleet would be capable of generating electricity and emitting much lower levels of pollution. For example, EPA projects that mercury emissions from coal-fueled electricity generating units will decrease by 75 percent as a result of its new regulatory requirements. Nevertheless, even the cleanest running coal-fueled unit may still be more polluting than generating units that use other fuel sources. For example, the 10 least- emitting coal-fueled units emitted over 10 times as much SO per million Btu compared with an average of 0.0006 for combined cycle units. Electricity generating units that rely on solar and wind sources produce no such emissions.

Some New Generating Units May Be Built and Would Be Larger, Cleaner, and More Efficient Than the Fleet Overall

Available information suggests that industry intends to build some new coal-fueled electricity generating units. According to Ventyx data, power companies have plans to build 42 new coal-fueled electricity generating units with 21,634 MW of capacity in various stages of planning or development (see fig. 7). However, as we have previously reported, developers generally have more planned projects than they complete.

The total capacity of coal-fueled electricity generating units in the United States may decline in the future as less capacity is expected to be built than is expected to retire. As discussed, 49,000 to 76,476 MW of coal- fueled capacity is projected to retire by 2035 according to EIA and IHS Global Insight, respectively, and they project that 11,000 MW and 22,134 MW of new coal-fueled capacity will be added by 2035, respectively. EIA officials told us that new coal-fueled capacity in their projections is primarily expected in the next few years and represents units that are already planned or under construction. As less capacity is expected to be built than is expected to retire, total coal-fueled capacity is expected to decline in the future, as shown in figure 8. Coal's share of total electricity generating capacity was about 30 percent in 2011. In EIA’s reference scenario, coal's share of capacity declines to 25 percent in 2035 as retiring coal-fueled units are not fully replaced, and as 176,100 MW of other generating capacity is added in the future.

Any coal-fueled units that are built in the future are likely to be larger, less polluting, and more fuel-efficient than the average of the coal-fueled fleet overall. Units that power companies are currently planning to build average 515 MW of net summer capacity, and the operating fleet averages 319 MW. Additionally, new units must install technologies to control emissions, and so are likely to emit lower levels of pollutants and thus be cleaner than the fleet overall. For example, generating units built after August 7, 1977, have had to obtain preconstruction permits that establish air emissions limits and require the use of certain emissions control technologies such as scrubbers to reduce emissions of SO.addition, some stakeholders we interviewed said that new coal-fueled units were likely to incorporate designs that are able to convert fuel to electricity more efficiently.

Coal Likely to Remain a Key Fuel Source, but Future Use May Be Affected by Fuel Prices, Environmental Regulations, and Other Factors

Coal is likely to continue to be a key fuel source for electricity generation in the United States, but its share as a source of electricity is expected to decline, and the future use of coal to generate electricity in the United States may be affected by several key factors that include the price of natural gas and other competing fuels, environmental regulations, and the demand for electricity, among others. In addition, several stakeholders we interviewed said that coal may increasingly be exported for use in other nations, though the extent of future exports is uncertain.

Coal Likely to Continue to Be a Key Source of Electricity in the Future, though Its Share Is Generally Expected to Decline in the United States

According to stakeholders we interviewed and projections by EIA, IEA, and IHS Global Insight, coal is likely to continue to be a key fuel source for U.S. electricity generation, but its share as a source of electricity is generally expected to decline in the future. Some stakeholders told us that, in the future, electricity generation from coal is likely to be displaced by generation from other fuel sources, particularly natural gas, but they still expect coal’s contribution to electricity generation to be significant. Furthermore, in its reference scenario, EIA estimates that coal will represent 38 percent of U.S. electricity generation in 2035 under current policies––down from 42 percent in 2011.amount of electricity generated using coal is expected to remain relatively constant over this same period under EIA’s reference scenario, growing by 0.1 percent annually. However, the amount of electricity generated using some other fuel sources, for example, natural gas and renewables, will increase at higher annual rates—1.4 percent and 2.3 percent respectively—diminishing coal’s total share of electricity generation.

Agency Comments and Our Evaluation

We met with EIA officials to discuss an early draft of this report and incorporated technical suggestions where appropriate. We also provided a draft of this report to EIA and EPA for formal comment. EIA and EPA did not provide written comments for inclusion in this report. EPA's Office of Air and Radiation did provide technical comments and stated that the report contained a very good description of many of the changes going on in coal and electricity markets that are affecting the use of coal to generate electricity. In its technical comments, EPA suggested that the draft’s emphasis on environmental regulations, particularly on the Highlights page, was misleading and not consistent with the rest of the report, which has a fuller discussion of many factors affecting the future use of coal. EPA stated that market changes, which we discuss in the report, would have significant impacts even in the absence of EPA's regulations. We do not agree that the report was misleading, but given that the Highlights page may be read without the benefit of the fuller discussion found in the report, we moved language from the body of the report to the Highlights page about other factors affecting the use of coal. EPA provided other technical comments, which we incorporated where appropriate.

As agreed with your office, unless you publicly announce the contents of this report earlier, we plan no further distribution until 30 days from the report date. At that time, we will send copies to the appropriate congressional committees, the Administrators of the EIA and EPA, and other interested parties. In addition, the report will be available at no charge on the GAO website at http://www.gao.gov.

If you or your staff members have any questions about this report, please contact me at (202) 512-3841 or ruscof@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made key contributions to this report are listed in appendix III.

Appendix I: Analysis of Characteristics of Coal-Fueled Generating Units That Power Companies Plan to Retire

This appendix describes our statistical analysis of characteristics of coal- fueled electricity generating units, such as age and size, that are likely to affect power companies’ plans to retire certain units. We use this analysis to estimate the number and generating capacity of other coal-fueled units that power companies are likely to consider retiring.

Methodology

To test the hypothesis that power companies are likely to retire older, smaller, and more polluting coal units by 2020, we used logistic regression analysis. We analyzed industry data on all coal-fueled units owned by power companies that have already announced plans to retire one or more of these units. Using unit- and company-level data, primarily from company-reported databases, we developed a model depicting the relationship between companies’ announced plans to retire a unit and that unit’s characteristics—age, size, emissions rates of sulfur dioxide (SO) and nitrogen oxides (NO), and the regulatory status of the power company that owns the unit, specifically whether the company is traditionally regulated or operates in a restructured market. To estimate the number and generating capacity of additional units likely to be retired, we applied our model to a dataset consisting of coal-fueled units owned by power companies that have not announced any retirements.

Model of Plans to Retire Coal-Fueled Generating Units

In developing our model of power companies’ plans to retire coal-fueled units, we relied on economic theory, as well as discussions with stakeholders and our review of studies. Stakeholders included representatives from power companies, a coal company, industry associations, and nongovernmental organizations, and officials from federal and state agencies. Stakeholders and studies mentioned the following characteristics as likely unit-level determinants of power companies’ plans to retire a coal-fueled unit or keep it in operation: age; generating capacity; fuel efficiency (i.e., how efficiently a unit converts fuel to electricity) operating cost and profitability; pollution emission rates and whether a unit already has various types of emissions control equipment; and regulatory status.

As a general matter, the larger, newer, more efficient, and less polluting a generating unit is, the more likely it is that a power company may to want to keep it in service and invest in retrofits that may be needed for it to comply with environmental laws or regulations. For example, if a large, new generating unit that a power company uses to meet a significant portion of customer demand is not in compliance with environmental regulations, retiring it would likely require replacing it with another unit of similar size. Doing so may be very costly, and retrofitting it with the requisite pollution control equipment may be a more economical choice.

It is also reasonable to expect regulatory status to have some impact on power companies’ retirement plans because such plans could involve significant investments. For companies that are traditionally regulated, state public utility commissions review power companies’ plans for major investments in pollution control equipment in the case of a retrofit, or in replacement power generation capacity if it is needed after a unit is retired. Decisions by power companies in restructured markets are not subject to the same state public utility oversight. Furthermore, once state public utility commissions approve a traditionally regulated company’s plan to invest in major retrofits or replacement units, they allow it to charge rates to recover its investment costs. Companies operating in restructured markets have no such cost-recovery provisions, so their investments in retrofits or replacement units may be riskier.

Our model does not include all the characteristics that stakeholders and studies identified as possible characteristics that power companies consider in deciding which coal-fueled units to retire. First, economic theory and our analysis of data on coal-fueled units indicate that there are interrelationships among some of these characteristics; for example, newer, larger electric generating units tend to be more fuel efficient, and this fuel efficiency contributes to lower operating costs. Hence, including all characteristics would be redundant and weaken the statistical results. Below, we discuss some specifications of the model with alternative sets of variables. Second, there are likely other characteristics that may influence power companies’ plans to retire generating units that we were unable to include in our statistical analysis. We discuss limitations of our model below.

Data Used

We used U.S. electricity data at the level of individual coal-fueled generating units that we obtained under contract from Ventyx, a company that maintains a proprietary database containing consolidated energy and emissions data from the Energy Information Administration (EIA),size, measured in megawatts (MW) of generating capacity; fuel efficiency; , and carbon dioxide; types of installed control equipment or whether owners plan to install control equipment in the future; various cost measures, including generating unit marginal cost; and regulatory status: equals 1 if the power company that owns the unit was traditionally regulated or 0 if the company was operating in a restructured market.

We also used regional day-ahead market prices from the IntercontinentalExchange (ICE) company, and spot market prices from the Federal Energy Regulatory Commission (FERC) to calculate an average wholesale market price for the regional markets associated with each unit in our dataset. For each market region, we calculated a simple average of daily prices for the year 2011 from daily ICE price data. For some of the regions, however, there were no price data available from ICE, so we used the 2011 average spot market price from FERC.

While our model does not include all the aforementioned characteristics, we used most of these characteristics in alternative specifications of the model and discuss two of these specifications below.

Our complete dataset includes 959 coal-fueled units. This dataset includes only units that have a net summer generating capacity greater than 25 MW, making them subject to EPA emissions monitoring and reporting requirements. We excluded units that have not reported any electricity generation or SO or NO emissions over the past 5 years.the total 959 units, 482 units belong to power companies that have announced plans for retiring at least one coal-fueled unit.

Results

We used logistic regression (logit) analysis to analyze the characteristics that are affecting power companies’ retirement plans of coal-fueled electricity generation units. Regression analysis in general estimates the effect of a change in an independent variable on the outcome (dependent) variable, while holding other variables constant. Logit is a type of regression analysis for situations in which the dependent variable is a categorical variable—one that can take on a limited number of values—instead of a continuous, quantitative variable. In this case, the categorical variable is binary, which means that the choice is between only two outcomes.

We estimated the logit regression equation for the subgroup of 482 coal- fueled generating units belonging to power companies that have announced plans to retire at least one coal-fueled unit. The dependent variable in our model is whether to retire or not retire a coal unit, and the independent variables are the (1) age of unit; (2) net summer capacity as a measure of unit size; (3) unit’s SO emissions per unit of heat input from the fuel used in the unit’s electricity generation, measured using millions of British thermal units (Btu); (4) unit’s NO emissions rate in lb/million Btu; (5) whether the power company that owns the unit is traditionally regulated or operates in a restructured market.

Table 2 shows our resulting estimated equation and relevant statistics.

These results generally confirm that smaller, older and more polluting units are more likely candidates for retirement. In the table above, the second column gives the estimated value of the coefficient, which describes the relationship between the independent variables and the likelihood of retirement. The remaining columns give the standard error and the significance level. For example, the coefficient on net summer capacity is negative, which means that an increase in capacity decreases the probability that a unit is planned for retirement. Furthermore, as shown in table 2, the estimated coefficient is significant at the 6 percent level. An estimated coefficient is typically considered statistically significant if the significance is less than 10 percent and very significant if it is less than 5 percent. Similarly, the coefficient on unit age is positive, which means that an older unit is more likely to be retired, and this coefficient estimate is significant at the 1 percent level. The coefficients on SO and NO emissions are also positive and significant at the 1 percent level.

Using the resulting logit regression equation, we analyzed “marginal effects” of changes in each of the independent variables on plans to retire an “average” unit owned by a power company in (1) a traditionally regulated market and (2) a restructured market, and the “average unit,” for this purpose, is one with median values for age, size/net summer capacity, SO emissions rates, as shown in tables 3 and 4.

For example, a 10 percent increase in the capacity of an average unit owned by a power company in a restructured market, from 193 to 212 MW, would decrease the probability of that unit’s retirement by about 2 percent, all other variables being held constant. For a unit owned by a power company in a traditionally regulated market, the same 10 percent would decrease the probability of retirement by about 1 percent. Note that the median values for units owned by power companies operating in traditionally regulated and restructured markets are not the same and that a 10 percent increase is therefore different.

Analysis Indicates Units Power Companies Likely to Consider Retiring

The next step in our analysis was to use the resulting logit regression equation to estimate the number and generating capacity of other coal- fueled units that companies are likely to consider retiring among units belonging to companies that have not, as of yet, announced plans to retire coal-fueled units. We also estimated the generation associated with these potential retirements in megawatt-hours (MWh). We assume that some or all of these companies are likely to retire coal-fueled units, but that they either have not decided which ones, or simply have not publicly announced their plans. We further assume that these companies have or will base their decisions on the same characteristics as the companies that have already made announcements. Table 5 shows our analysis of units that power companies may consider for retirement by 2020.

As shown in table 5, for the group of coal-fueled units whose owners have not reported any coal-fueled unit retirements, our analysis indicates from 90 to 138 units may likely be considered for retirement by 2020. This range represents the 95 percent confidence interval around our point estimate of 114 units. In other words, our model indicates that there is a 95 percent probability that the actual number of units that will retire is within this range. These 90 to 138 units account for 15,700 to 25,200 MW of capacity and 91 to 151 million MWh of electricity generation. If we add these units to those that power companies have announced for retirement, the total of coal-fueled retirements could range from 264 to 312 units by 2020, amounting to from 46,100 to 55,600 MW of capacity and average annual generation of 241 to 301 million MWh.percentage terms, this would be 15 to 18 percent of the capacity and 13 to 16 percent of the generation of the current coal-fueled fleet of generating units.

Limitations and Alternative Model Specifications

This section discusses the limitations of our model and alternative model specifications that we tested.

Limitations

A major limitation of our model is that we used a nonrandom sample of the entire population of coal-fueled units to estimate the relationship between the characteristics of coal-fueled units and power companies’ plans to retire a unit. Our sample consisted of companies that announced plans to retire at least one unit but was not a random sample. It is possible that the companies that announced planned retirements and those that did not so announce differ in systematic ways that we do not observe from the data.bias.

Such differences could result in omitted variable Another important limitation of our model is that we did not include all factors that contribute to power companies’ decision to retire coal-fueled units. Apart from unit-level considerations, major factors that affect a power company’s decision to retire a coal-fueled unit include fuel costs, environmental regulations, regional and local market considerations (e.g., expected future electricity demand and supply conditions, and transmission constraints), and technological developments in electricity generation and pollution control. For example, we did not take into account that planned unit retirements might make otherwise marginal units in some regions more valuable and less likely to retire. Companies that own coal-fueled units may have different expectations regarding these factors, which we did not consider in our analysis. Effectively, therefore, we assumed that power companies have very similar expectations regarding these factors.

These above limitations could mean that our model does not accurately or fully reflect power companies’ unit retirement decisions. This would also mean that our estimates of how many unannounced units will retire may be inaccurate. For most of the limitations, the direction of bias in our model—the extent to which it may over- or under-estimate the likelihood of a unit retiring—is unclear. Addressing these limitations was beyond the scope of our review.

Alternative Specifications

To check the robustness of our model, we tested different specifications; that is, we ran logistic regressions using different sets of independent variables. For example, we tried specifications that included a measure of a unit’s fuel efficiency, and another representing whether a unit is planning to install pollution control equipment. We also tried a version with unit average capacity factors in recent years, a measure of how intensively a unit is utilized. Based on our results, none of these variables significantly improved the model. Below, we discuss two other alternative specifications in more detail.

In one alternative specification, we used clustered standard errors. Our model assumes that each individual coal-fueled unit has a unique error term that is independent of every other unit. In this specification, we allow for the possibility that units owned by the same power companies may be related in unobserved ways and, therefore, the error terms may be correlated. As shown in table 6, the estimated coefficients in this alternative specification are very similar to our model, but the standard errors are generally bigger, and the estimated coefficients are generally less statistically significant. This is especially true for net summer capacity, which is no longer statistically significant at the commonly accepted 10 percent level.

In a second alternative specification, we used adjusted marginal cost as a proxy for the profitability of a unit. Based on economic logic and what we heard from stakeholders, we expected some indicator of the cost and profitability of electricity generation to contribute significantly to the retirement decision. Table 7 shows a version with marginal cost adjusted for regional wholesale prices and an interaction term with marginal cost and regulatory status. We adjusted marginal cost by dividing it by the regional wholesale price to account for the fact that units are more or less valuable depending on regional wholesale electricity prices. The interaction term allows us to effectively estimate two coefficients for adjusted marginal cost, one for power companies in traditionally regulated markets, and one for power companies in restructured markets. We included an interaction term to account for the possibility that power companies in traditionally regulated and restructured markets view costs Indeed, as shown in table 7, the estimated adjusted marginal differently.cost coefficients differ—for power companies in restructured markets, the adjusted marginal cost coefficient is about 5.8, while the estimated coefficient for power companies in traditionally regulated markets is the adjusted marginal cost coefficient plus the interaction term (or 5.8 plus - 8.2 = -2.4). These results suggest that while higher adjusted marginal costs increase the probability of retirement of units owned by power companies in restructured markets, they decrease the probability for units owned by traditionally regulated power companies. The interpretation of these results is unclear.

Regarding the costs of producing electricity, our findings differed for companies in restructured markets and companies that are traditionally regulated. Specifically, our results suggest that companies in restructured markets are more likely to retire units with higher adjusted marginal costs. In contrast, our results suggest that companies operating in regulated markets are less likely to retire units with higher adjusted marginal costs. A number of characteristics, not considered in our model, could provide alternative explanations for this difference. For example, it could be the case that the units in our sample have unique characteristics. One such potential case could be that units owned by power companies in traditionally regulated markets may be located in areas where concerns about the reliability of the electricity system are significant, and the costs of retrofitting an older generating unit are less costly than retiring it. Similarly, it could be that our sample contains a number of units located in areas with lower cost alternative suppliers or where prices are low— diminishing the attractiveness of even a relatively low-cost unit.

Appendix II: Description of Selected Scenarios and Forecasts

Table 8 describes key scenarios and assumptions in the EIA, IEA, and IHS Global Insight forecasts discussed in this report.

Appendix III: GAO Contact and Staff Acknowledgments

GAO Contact

Staff Acknowledgments

In addition to the contact named above, Jon Ludwigson (Assistant Director), Mike Armes, Patrick Dudley, Philip Farah, Quindi Franco, Cindy Gilbert, Paige Gilbreath, Alison O’Neill, Kendal Robinson, Jeanette Soares, and Kiki Theodoropolous made key contributions to this report.

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