Electricity Market Module 

The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity.  It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing.  It includes nonutility capacity and generation, and electricity transmission and trade.  A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2010, DOE/EIA-M068(2010). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM.  It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan.  The various electricity and technology cases are also described.

Figure 6. Electricity Market Model Supply Regions

EMM Regions

The supply regions used in EMM are based on the North American Electric Reliability Council regions and subregions shown in Figure 6 (region definitions as of 2004).

Model Parameters and Assumptions Generating Capacity Types

The capacity types represented in the EMM are shown in Table 8.1.

New Generating Plant Characteristics

The cost and performance characteristics of new generating technologies are inputs to the electricity capacity planning submodule (Table 8.2). These characteristics are used in combination with fuel prices from the NEMS fuel supply modules and foresight on fuel prices, to compare options when new capacity is needed.  Heat rates for fossil-fueled technologies are assumed to decline linearly through  2025.

The overnight costs shown in Table 8.2 are the cost estimates to build a plant in a typical region of the country. Differences in plant costs due to regional distinctions are calculated by applying regional multipliers that represent variations in the cost of labor.  The base overnight cost is multiplied by a project contingency factor and a technological optimism factor (described later in this chapter), resulting in the total construction cost for the first-of-a-kind unit used for the capacity choice decision.

The base overnight costs were updated to capture some of the rapid increases due to rising commodity costs for AEO2009.  Cost for coal and nuclear plants were updated for AEO2010 to reflect continued modest increases.   A cost adjustment factor, based on the producer price index for metals and metal products, allows the overnight costs to fall in the future if this index drops, or rise further if it increases.

Technological Optimism and Learning

Overnight costs for each technology are calculated as a function of regional construction parameters, project contingency, and technological optimism and learning factors. The technological optimism factor represents the demonstrated tendency to underestimate actual costs for a first-of-a-kind, unproven technology.   As experience is gained (after building 4 units) the technological optimism factor is gradually reduced to 1.0.

The learning function in NEMS is determined at a component level. Each new technology is broken into its major components, and each component is identified as revolutionary, evolutionary or mature. Different learning rates are assumed for each component, based on the level of experience with the design component (Table 8.3).  Where technologies use similar components, these components learn at the same rate as these units are built.   For example, it is assumed that the underlying turbine generator for a combustion turbine, combined cycle and integrated coal-gasification combined cycle unit   is basically the same. Therefore construction of any of these technologies would contribute to learning reductions for the turbine component.

The learning function has the nonlinear form:

                                             OC(C) = a*C-b,

where C is the cumulative capacity for the technology component.

The progress ratio (pr) is defined by speed of learning (e.g., how much costs decline for every doubling of capacity).   The reduction in capital cost for every doubling of cumulative capacity (f) is an exogenous parameter input for each component (Table 8.3).  Consequently, the progress ratio and f are related by:

                                             pr = 2-b = (1 - f)

The parameter “b” is calculated by (b =-(ln(1-f)/ln(2)).  The parameter “a” can be found from initial conditions. That is,   

                                            a =OC(C0)/C0-b

where C0 is the cumulative initial capacity.  Thus, once the rates of learning (f) and the cumulative capacity (C0) are known for each interval, the corresponding parameters (a and b) of the nonlinear function are known.   Three learning steps were developed, to reflect different stages of learning as a new design is introduced to the market.  New designs with a significant amount of untested technology will see high rates of learning initially, while more conventional designs will not have as much learning potential.   All design components receive a minimal amount of learning, even if new capacity additions are not projected.  This represents cost reductions due to future international development or increased research and development.

Once the learning rate by component is calculated, a weighted average learning factor is calculated for each technology. The weights are based on the share of the initial cost estimate that is attributable to each component (Table 8.4). For technologies that do not share components, this weighted average learning rate is calculated exogenously, and input as a single component. These technologies may still have a mix of revolutionary components and more mature components, but it is not necessary to include this detail in the model unless capacity from multiple technologies would contribute to the component learning.

International Learning.   In AEO2010, capital costs for all new electricity generating technologies (fossil, nuclear, and renewable) decrease in response to foreign and domestic experience.  Foreign units of new technologies are assumed to contribute to reductions in capital costs for units that are installed in the United States to the extent that (1) the technology characteristics are similar to those used in U.S. markets, (2) the design and construction firms and key personnel compete in the U.S. market, (3) the owning and operating firm competes actively in the U.S. market, and (4) there exists relatively complete information about the status of the associated facility.  If the new foreign units do not satisfy one or more of these requirements, they are given a reduced weight or not included in the domestic learning effects calculation.

AEO2010 includes 5,000 megawatts of advanced coal gasification combined-cycle capacity, 5,244 megawatts of advanced combined-cycle natural gas capacity, 11 megawatts of biomass capacity and 47 megawatts each of traditional wind and offshore wind capacity built outside the United States from 2000 through 2003. The learning function also includes 7,200 megawatts of advanced nuclear capacity, representing two completed units and four additional units under construction in Asia.

Distributed Generation

Distributed generation is modeled in the end-use sectors as well as in the EMM, which is described in the appropriate chapters. This section describes the representation of distributed generation in the EMM only. Two generic distributed technologies are modeled. The first technology represents peaking capacity (capacity that has relatively high operating costs and is operated when demand levels are at their highest). The second generic technology for distributed generation represents base load capacity (capacity that is operated on a continuous basis under a variety of demand levels).  See Table 8.2 for costs and performance assumptions.   It is assumed that these plants reduce the costs of transmission upgrades that would otherwise be needed.

Demand Storage

The electricity model includes the option to build a new demand storage technology to simulate load shifting, through programs such as smart meters. This is modeled as a new technology build, but with operating characteristics similar to pumped storage. The technology is able to decrease the load in peak slices, but must generate to replace that demand in other time slices. There is an input factor that identifies the amount of replacement generation needed, where a factor of less than 1.0 can be use to represent peak shaving rather than purely shifting the load to other time periods. This plant type is limited to operating only in the peak load slices, and for AEO2010, it is assumed that this capacity is limited to 3 percent of peak demand in each region.

Representation of Electricity Demand

The annual electricity demand projections from the NEMS demand modules are converted into load duration curves for each of the EMM regions (based on North American Electric Reliability Council   regions and subregions) using historical hourly load data.   The load duration curve in the EMM is made up of 9 time slices.  First, the load data is split into three seasons, (winter - December through March, summer - June through September, and fall/spring).  Within each season the load data is sorted from high to low, and three load segments are created - a peak segment representing the top 1 percent of the load, and then two off-peak segments representing the next 49 percent and 50 percent, respectively.   The seasons were defined to account for seasonal variation in supply availability.

Reserve margins—the percentage of capacity required in excess of peak demand needed for unforeseeable outages—are determined within the model through an iterative approach comparing the marginal cost of capacity and the cost of unserved energy.  The target reserve margin is adjusted each model cycle until the two costs converge.  The resulting reserve margins from the AEO2010 reference case range from 8 to 16 percent.

Fossil Fuel-Fired and Nuclear Steam Plant Retirement

Fossil-fired steam plant retirements and nuclear retirements are calculated endogenously within the model. Plants are assumed to retire when it is no longer economical to continue running them.  Each year, the model determines whether the market price of electricity is sufficient to support the continued operation of existing plants.  If the expected revenues from these plants are not sufficient to cover the annual going forward costs, the plant is assumed to retire if the overall cost of producing electricity can be lowered by building new replacement capacity.  The going-forward costs include fuel, operations and maintenance costs and annual capital additions, which are plant specific based on historical data.  The average capital additions for existing plants are $8 per kilowatt (kW) for oil and gas steam plants, $16 per kW for coal plants and $21 per kW for nuclear plants (in 2008 dollars). These costs are added to existing plants regardless of their age.  Beyond 30 years of age an additional $6 per kW capital charge for fossil plants, and $31 per kW charge for nuclear plants is included in the retirement decision to reflect further investment to address impacts of aging.  Age related cost increases are due to capital expenditures for major repairs or retrofits, decreases in plant performance, and/or increased maintenance costs to mitigate the effects of aging.

Biomass Co-firing

Coal-fired power plants are allowed to co-fire with biomass fuel if it is economical.  Co-firing requires a capital investment for boiler modifications and fuel handling. This expenditure ranges from about $121 to $279 per kilowatt of biomass capacity, depending on the type and size of the boiler. A coal-fired unit modified to allow co-firing can generate up to 15 percent of the total output using biomass fuel, assuming sufficient residue supplies are available. Larger units are required to pay additional transportation costs as the level of co-firing increases, due to the concentrated use of the regional supply.

Nuclear Uprates

The AEO2010 nuclear power projection assumes capacity increases at existing units. Nuclear plant operators can increase the rated capacity at plants through power uprates, which are license amendments that must be approved by the U.S. Nuclear Regulatory Commission (NRC).  Uprates can vary from small (less than 2 percent) increases in capacity, which require very little capital investment or plant modifications, to extended uprates of 15-20 percent, requiring significant modifications. Historically, most uprates were small, and the AEO projections accounted for them only after they were implemented and reported, but recent surveys by the NRC and EIA have indicated that more extended power uprates are expected in the near future.  AEO2010 assumes that all of those uprates approved, pending or expected by the NRC will be implemented, for a capacity increase of 4.0 gigawatts between 2009 and 2035.   Table 8.6 provides a summary of projected uprate capacity additions by region. In cases where the NRC did not specifically identify the unit expected to uprate, EIA assumed the units with the lowest operating costs would be the next likely candidates for power increases.

Interregional Electricity Trade

Both firm and economy electricity transactions among utilities in different regions are represented within the EMM.  In general, firm power transactions involve the trading of capacity and energy to help another region satisfy its reserve margin requirement, while economy transactions involve energy transactions motivated by the marginal generation costs of different regions.  The flow of power from region to region is constrained by the existing and planned capacity limits as reported in the National Electric Reliability Council and Western Electric Coordinating Council Summer and Winter Assessment of Reliability of Bulk Electricity Supply in North America.   Known firm power contracts are obtained from NERC’s Electricity Supply and Demand Database 2007. They are locked in for the term of the contract. Contracts that are scheduled to expire by 2016 are assumed not to be renewed.  Because there is no information available about expiration dates for contracts that go beyond 2016, they are assumed to be phased out by 2025.  In addition, in certain regions where data show an established commitment to build plants to serve another region, new plants are permitted to be built to serve the other region’s needs.   This option is available to compete with other resource options.

International Electricity Trade

Two components of international firm power trade are represented in the EMM—existing and planned transactions, and unplanned transactions.  Existing and planned transactions are obtained from the North American Electric Reliability Council’s Electricity Supply and Demand Database 2007. Unplanned firm power trade is represented by competing Canadian supply with U.S. domestic supply options.  Canadian supply is represented via supply curves using cost data from the Department of Energy report Northern Lights: The Economic and Practical Potential of Imported Power from Canada, (DOE/PE-0079). International economy trade is determined endogenously based on surplus energy expected to be available from Canada by region in each time slice.  Canadian surplus energy is determined using Canadian electricity supply and demand projections from the MAPLE-C model developed for Natural Resources Canada.

Electricity Pricing

The reference case assumes a transition to full competitive pricing in New York, Mid-Atlantic Area Council, and Texas, and a 95 percent transition to competitive pricing in New England (Vermont being the only fully-regulated State in that region). California returned to almost fully regulated pricing in 2002, after beginning a transition to competition in 1998. In addition electricity prices in the East Central Area Reliability Council, the Mid-American Interconnected Network, the Southeastern Electric Reliability Council, the Southwest Power Pool, the Northwest Power Pool, and the Rocky Mountain Power Area/Arizona are a mix of both competitive and regulated prices. Since some States in each of these regions have not taken action to deregulate their pricing of electricity, prices in those States are assumed to continue to be based on traditional cost-of-service pricing. The price for mixed regions is a load-weighted average of the competitive price and the regulated price, with the weight based on the percent of electricity load in the region that has taken action to deregulate. The reference case assumes that State-mandated price freezes or reductions during a specified transition period will occur based on the terms of the legislation. In general, the transition period is assumed to occur over a ten-year period from the effective date of restructuring, with a gradual shift to  marginal  cost  pricing.  In  regions  where  none  of  the  states  in  the  region  have  introduced competition—Florida Reliability Coordinating Council and Mid-Continent Area Power Pool—electricity prices are assumed to remain regulated and the cost-of-service calculation is used to determine electricity prices.

The price of electricity to the consumer is comprised of the price of generation, transmission, and distribution including applicable taxes. Transmission and distribution are considered to remain regulated in the AEO; that is, the price of transmission and distribution is based on the average cost. In competitive regions, an algorithm in place allows customers to compete for better rates among rate classes as long as the overall average cost is met. The price of electricity in the regulated regions consists of the average cost of generation, transmission, and distribution for each customer class. In the competitive regions, the generation component of price is based on marginal cost, which is defined as the cost of the last (or most expensive) unit dispatched. The marginal cost includes fuel, operation and maintenance, taxes, and a reliability price adjustment, which represents the value of capacity in periods of high demand. The price of electricity in the regions with a competitive generation market consists of the marginal cost of generation summed with the average costs of transmission and distribution.

In recent years, the move towards competition in the electricity business has led utilities to make efforts to reduce costs to improve their market position. These cost reduction efforts are reflected in utility operating data reported to the Federal Energy Regulatory Commission (FERC) and these trends have been incorporated in the AEO2010. Both General and Administrative (G&A) expenses and Operations and Maintenance (O&M) expenses have shown declines in recent years. The O&M declines show variation based on the plant type. A regression analysis of recent data was done to determine the trend, and the resulting function was used to project declines throughout the projection. The analysis of G&A costs used data from 1992 through 2001, which had a 15 percent overall decline in G&A costs, and a 1.8 percent average annual decline rate. The AEO2010 projection assumes a further decline of 18 percent by 2025 based on the results of the regression analysis. The O&M cost data was available from 1990 through 2001, and showed average annual declines of 2.1 percent for all steam units, 1.8 percent for combined cycle and 1.5 percent for nuclear. The AEO2010 assumes further declines in O&M expenses for these plant types, for a total decline through 2025 of 17 percent for combined cycle, 15 percent for steam and 8 percent for nuclear.

There have been ongoing changes to pricing structures for ratepayers in competitive States since the inception of retail competition.  The AEO has incorporated these changes as they have been incorporated into utility tariffs.   These have included transition period rate reductions and freezes instituted by various States, and surcharges in California relating to the 2000-2001 energy crisis there.  Since price freezes for most customers have ended or will end in the next year or two, a large survey of utility tariffs found that many costs related to the transition to competition were now explicitly added to the distribution portion, and sometimes the transmission portion of the customer bill regardless of whether or not the customer bought generation service from a competitive or regulated supplier.    There are some unexpected costs relating to unforeseen events.  For instance, as a result of volatile fuel markets, State regulators have had a hard time enticing retail suppliers to offer competitive supply to residential and smaller commercial and industrial customers.  They have often resorted to procuring the energy themselves through auction or competitive bids or have allowed distribution utilities to procure the energy on the open market for their customers for a fee.   For AEO2010, typical charges that all customers must pay on the distribution portion of their bill (depending on where they reside) include: transition charges (including persistent stranded costs), public benefits charges (usually for efficiency and renewable energy programs), administrative costs of energy procurement, and nuclear decommissioning costs.   Costs added to the transmission portion of the bill include the Federally Mandated Congestion Charges (FMCC), a bill pass-through associated with the Federal Energy Regulatory Commission passage of Standard Market Design (SMD) to enhance reliability of the transmission grid and control congestion.

Transmission costs for the AEO are traditionally projected based on regressions of historical spending per non-coincident peak time electricity use to ensure that the model builds enough transmission infrastructure to accommodate growth in peak electricity demand. However, since spending decreased throughout the 1990s we have had to add in extra spending on transmission.  Our additions were based on several large studies, such as the Department of Energy’s National Transmission Grid Study, which set out to document how much spending would be needed to keep the national grid operating efficiently.  Transmission spending has in fact been increasing very recently.  We will be monitoring transmission spending closely over the next several years and updates will be made as new information becomes available.

Fuel Price Expectations

Capacity planning decisions in the EMM are based on a life cycle cost analysis over a 30-year period.  This requires foresight assumptions for fuel prices.  Expected prices for coal, natural gas and oil are derived using rational expectations, or ‘perfect foresight’. In this approach, expectations for future years are defined by the realized solution values for these years in a prior run. The expectations for the world oil price and natural gas wellhead price are set using the resulting prices from a prior run. The markups to the delivered fuel prices are calculated based on the markups from the previous year within a NEMS run. Coal prices are determined using the same coal supply curves developed in the Coal Market Module. The supply curves produce prices at different levels of coal production, as a function of labor productivity, and costs and utilization of mines. Expectations for each supply curve are developed in the EMM based on the actual demand changes from the prior run throughout the projection horizon, resulting in updated mining utilization and different supply curves.

The perfect foresight approach generates an internally consistent scenario for which the formation of expectations is consistent with the projections realized in the model. The NEMS model involves iterative cycling of runs until the expected values and realized values for variables converge between cycles.

Nuclear Fuel Prices

Legislation and Regulations

Clean Air Act Amendments of 1990 (CAAA90) and Clean Air Interstate Rule (CAIR) The Clean Air Interstate Rule is a cap-and-trade program promulgated by the EPA in 2005 to reduce SO2 and NOx emissions in order to help States meet their National Ambient Air Quality Standards (NAAQS) for ozone and particulate matter, and to further emissions reductions already achieved through earlier programs. On July 11, 2008 the U.S. District Court of Appeals overturned CAIR. However, on December 23, 2008, the Court of Appeals issued a new ruling that allowed CAIR to remain in effect while EPA determines the appropriate modifications to address the original objections. Therefore, CAIR is modeled explicitly in the AEO2010.

As specified in the CAAA90, EPA has developed a two-phase nitrogen oxide (NOx) program, with the first set of standards for existing coal plants applied in 1996 while the second set was implemented in 2000.    Dry bottom wall-fired, and tangential fired boilers, the most common boiler types, referred to as Group 1 Boilers, were required to make significant reductions beginning in 1996 and further reductions in 2000.  Relative to their uncontrolled emission rates, which range roughly between 0.6 and 1.0 pounds per  million Btu, they are required to make reductions between 25 and 50 percent to meet the Phase I limits and further reductions to meet their Phase II limits.   The EPA did not impose limits on existing oil and gas plants, but some states have additional NOx  regulations.  All new fossil units are required to meet standards.  In pounds per million Btu, these limits are 0.11 for conventional coal, 0.02 for advanced coal, 0.02 for combined cycle, and 0.08 for combustion turbines.  These NOx limits are incorporated in EMM.

In addition, the EPA has issued rules to limit the emissions of NOx, specifically calling for capping emissions during the summer season in 22 Eastern and Midwestern states. After an initial challenge, these rules have been upheld, and emissions limits have been finalized for 19 states and the District of Columbia (Table 8.7). Within EMM, electric generators in these 19 states must comply with the limit either by reducing their own emissions or purchasing allowances from others who have more than they need.

The costs of adding flue gas desulfurization equipment (FGD) to remove sulfur dioxide (SO2) and selective catalytic reduction (SCR) equipment to remove nitrogen oxides (NOx) are given below for 300, 500, and 700-megawatt coal plants.  FGD units are assumed to remove 95 percent of the SO2, while SCR units are assumed to remove 90 percent of the NOx.  The costs per megawatt of capacity decline with plant size and are shown in Table 8.8.

Mercury Regulation

The Clean Air Mercury Rule set up a national cap-and-trade program with emission limits set to begin in 2010. This rule was vacated in February, 2008 and therefore is not included in the AEO2010. However, many States had already begun adopting more stringent regulations calling for the application of the best available control technology on all electricity generating units of a certain capacity. After the court’s decision, more States imposed their own regulations. Because State laws differ, a rough estimate was created that generalized the various State programs into a format that could be used in NEMS. The EMM allows plants to alter their configuration by adding equipment, such as an SCR to remove NOx or an SO2 scrubber.  They can also add activated carbon injection systems specifically designed to remove mercury.  Activated carbon can be injected in front of existing particulate control devices or a supplemental fabric filter can be added with activated carbon injection capability.

The equipment to inject activated carbon in front of an existing particulate control device is assumed to cost approximately $6 (2008 dollars) per kilowatt of capacity, while the cost of a supplemental fabric filter with activated carbon injection (often referred as a COPAC unit) is approximately $77 per kilowatt of capacity.1 The amount of activated carbon required to meet a given percentage removal target is given by the following equations.2

For a unit with a CSE, using subbituminous coal, and simple activated carbon injection:

• Hg Removal (%) = 65 - (65.286 / (ACI + 1.026))

For a unit with a CSE, using bituminous coal, and simple activated carbon injection:

• Hg Removal (%) = 100 - (469.379 / (ACI + 7.169))

For a unit with a CSE, and a supplemental fabric filter with activated carbon injection:

• Hg Removal (%) = 100 - (28.049 / (ACI + 0.428))

For a unit with a HSE/Other, and a supplemental fabric filter with activated carbon injection:

• Hg Removal (%) = 100 - (43.068 / (ACI + 0.421))

ACI = activated carbon injected in pounds per million actual cubic feet.

Power Plant Mercury Emissions Assumptions

The Electricity Market Module (EMM) of the National Energy Modeling System (NEMS) represents 35 coal plant configurations and assigns a mercury emissions modification factor (EMF) to each configuration Each configuration represents different combinations of boiler types, particulate control devices, sulfur dioxide (SO2) control devices, nitrogen oxide (NOx) control devices, and mercury control devices. An EMF represents the amount of mercury that was in the fuel that remains after passing through all the plant’s systems.  For example, an EMF of 0.60 means that 40 percent of the mercury that was in the fuel is removed by various parts of the plant.  Table 8.9 provides the assumed EMFs for existing coal plant configurations without mercury specific controls.

Planned SO2 Scrubber and NOx Control Equipment Additions

In recent years, in response to state emission reduction programs and compliance agreements with the Environmental Protection Agency, some companies have announced plans to add scrubbers to their plants to reduce sulfur dioxide and particulate emissions.   Where firm commitments appear to have been made these plans have been represented in NEMS.  Based on EIA analysis of announced plans, 40.5 gigawatts of capacity are assumed to add these controls (Table 8.10).  The greatest number of retrofits is expected to occur  in the Midwestern States, where there is a large base of coal capacity impacted by the SO2 limit in CAIR, as well as in the Southeastern Electric Reliability Council because of the Clean Smokestacks bill passed by the North Carolina General Assembly.

Companies are also announcing plans to retrofit units with controls to reduce NOx emissions to comply with emission limits in certain states. In the reference case planned post-combustion control equipment amounts to 20.5 gigawatts of selective catalytic reduction (SCR).

Carbon Capture and Sequestration Retrofits

Although a federal greenhouse gas program is not in place in the AEO2010 reference case, the EMM was updated to include the option of retrofitting existing coal plants for carbon capture and sequestration (CCS). This option is important when considering alternate scenarios that do constrain carbon emissions. The modeling structure for CCS retrofits within the EMM was developed by the National Energy Technology Laboratory3 and uses a generic model of retrofit costs as a function of basic plant characteristics (such as heatrate). The CCS retrofits are assumed to remove 90% of the carbon input. The addition of the CCS equipment results in a capacity derate of around 30% and reduced efficiency of 43% at the existing coal plant. The costs depend on the size and efficiency of the plant, with the capital costs ranging from $900 to $1300 per kilowatt. It was assumed that only plants greater than 500 megawatts and with heatrates below 12,000 BTU per kilowatthour would be considered for CCS retrofits.

Energy Policy Acts of 1992 (EPACT92) and 2005 (EPACT05)

The provisions of the EPACT92 include revised licensing procedures for nuclear plants and the creation of exempt wholesale generators (EWGs).   The EPACT05 provides a 20-percent investment tax credit for Integrated Coal-Gasification Combined Cycle capacity and a 15-percent investment tax credit for other advanced coal technologies.   These credits are limited to 3 gigawatts in both cases.   It also contains a production tax credit (PTC) of 1.8 cents (nominal) per kilowatthour for new nuclear capacity beginning operation by 2020.   This PTC is specified for the first 8 years of operation, is limited to $125 million (per gigawatt) annually, and is limited to 6 gigawatts of new capacity.   However, this credit may be shared to additional units if more than 6 gigawatts are under construction by January 1, 2014.   In the AEO2009 Reference case it is projected that 3 gigawatts of new nuclear capacity will be built by 2020, each receiving the full credit worth 1.8 cents per kilowatthour.   EPACT05 extended the PTC for qualifying renewable facilities by 2 years, or December 31, 2007.   It also repealed the Public Utility Holding Company Act (PUHCA).

Energy Improvement and Extension Act 2008 (EIEA2008)

American Recovery and Reinvestment Act (ARRA)
Updated Tax Credits for Renewables

ARRA further extended the expiration date for the PTC to January 1, 2013, for wind and January 1, 2014, for all other eligible renewable resources.  In addition, ARRA allows companies to choose an investment tax credit (ITC) of 30 percent in lieu of the PTC and allows for a grant in lieu of this credit to be funded by the U.S. Treasury.  Under most circumstances for most technologies, the full PTC would appear to be more valuable than the 30 percent ITC; however, the difference is often small.   Qualitative factors, such as the lack of partners with sufficient tax liability, may cause companies to favor the ITC grant option in the current economic environment.  The AEO2010 generally assumes that renewable electricity projects will claim the more favorable tax credit or grant option available to them.

Loan Guarantees for Renewables

ARRA provided $6 billion to pay the cost of guarantees for loans authorized by the Energy Policy Act of 2005. This provision has been represented by lowering the cost of financing by 2 percentage points for all eligible renewable projects brought on by 2015.  The 2015 date, 4 years after the September 30, 2011, start of construction cutoff date, was chosen to allow for the construction period associated with most renewable generating technologies.

Support for CCS

ARRA provided $3.4 billion for additional research and development on fossil energy technologies.   A portion of this funding is expected to be used to fund projects under the Clean Coal Power Initiative program, focusing on projects that capture and sequester greenhouse gases.  To reflect the impact of this provision, the AEO2010 reference case assumes that an additional 1 gigawatt of coal capacity with CCS will be stimulated by 2017.

Smart Grid Expenditures

ARRA provides $4.5 billion for smart grid demonstration projects.  While somewhat difficult to define, smart grid technologies generally include a wide array of measurement, communications, and control equipment employed throughout the transmission and distribution system that will enable real-time monitoring of the production, flow, and use of power from generator to consumer.  Among other things once deployed, these smart grid technologies are expected to enable more efficient use of the transmission and distribution grid, lower line losses, facilitate greater use of renewables, and provide information to utilities and their customers that will lead to greater investment in energy efficiency and reduced peak load demands.   The funds provided will not fund a widespread implementation of smart grid technologies, but could stimulate more rapid investment than would otherwise occur.

Several changes were made throughout the NEMS to represent the impacts of the smart grid funding provided in ARRA.  In the electricity module, it was assumed that line losses would fall slightly, peak loads would fall as customers shifted their usage patterns, and customers would be more responsive to pricing signals. Historically, line losses, expressed as the percentage of electricity lost, have been falling for many years as utilities make investments to replace aging or failing equipment. This trend was incorporated in the previous AEO reference cases, and after passage of ARRA, the time period for improvements was extended, allowing for greater declines in losses. In AEO2010 it is assumed that line losses fall from roughly 6.9 percent in 2008 to 5.3 percent by 2025.

Smart grid technologies also have the potential to reduce peak demand through the increased deployment of demand response programs.  In the AEO2010, it is assumed that the Federal expenditures on smart grid technologies will stimulate efforts that reduce peak demand in 2035 by 3 percent from what they otherwise would be.  Load is shifted to offpeak hours, so net energy consumed remains largely constant.

FERC Orders 888 and 889

FERC has issued two related rules (Orders 888 and 889) designed to bring low cost power to consumers through competition, ensure continued reliability in the industry, and provide for open and equitable.

Specifically, Order 888 requires open access to the transmission grid currently owned and operated by utilities. The transmission owners must file nondiscriminatory tariffs that offer other suppliers the same services that the owners provide for themselves. Order 888 also allows these utilities to recover stranded costs (investments in generating assets that are unrecoverable due to consumers selecting another supplier).  Order 889 requires utilities to implement standards of conduct and an Open Access Same-Time Information System (OASIS) through which utilities and non-utilities can receive information regarding the transmission system.   Consequently, utilities are expected to functionally or physically unbundle their marketing functions from their transmission functions.

These orders are represented in EMM by assuming that all generators in a given region are able to satisfy load requirements anywhere within the region.  Similarly, it is assumed that transactions between regions will occur if the cost differentials between them make it economic to do so.

Electricity Alternative Cases

Fossil Cost Cases

The high fossil cost case assumes that the base costs of all fossil generating technologies  will remain at current costs during the projection period, with no reductions due to learning.  The annual commodity cost adjustment factor is still appplied as in the reference case. (Table 8.11)   Capital costs of non-fossil generating technologies are the same as those assumed in the reference case. In the low fossil cost case, capital costs, and operating costs for the fossil technologies are assumed to start 10% lower than the reference case and to be 25 percent lower than Reference case levels in 2035. Since learning occurs in the Reference case, costs and performance in the low case are reduced from initial levels by more than 25 percent, across the fossil technologies. Capital costs are reduced by 37 percent to 49 percent between 2010 and 2035.

The low and high fossil cost cases are fully-integrated runs, allowing feedback from the end-use demand and fuel supply modules.

Nuclear Cost Cases

For nuclear power plants, two nuclear cost cases analyze the sensitivity of the projections to lower and higher costs for new plants. The cost assumptions for the low nuclear cost case reflect a 10 percent decline in initial costs and a 25 percent reduction in the capital and operating cost for the advanced nuclear technology in 2035, relative to the reference case. Since the reference case assumes some learning occurs regardless of new orders and construction, the reference case already projects a 35 percent reduction in capital costs between 2010 and 2035. The low nuclear cost case assumes a 45 percent reduction between 2010 and 2035. The high nuclear cost case assumes that base capital costs for the advanced nuclear technology do not decline from 2010 levels (Table 8.12). The capital costs are still tied to key commodity price indices, but no cost improvement from "learning-by-doing" effects is assumed.

Alternate Nuclear Retirement Case

In the nuclear 60-year life case, all existing nuclear plants are assumed to retire after 60 years of operation. In the reference case, existing plants are assumed to run as long as they continue to be economic, therefore implicitly assuming that a second 20-year license renewal will be obtained for those plants reaching 60 years before 2035. This alternate case was run to analyze the impact of additional nuclear retirements, which could occur if the oldest plants do not receive a second license extension. In this case 31 gigawatts of nuclear capacity are assumed to retire by 2035.

Electricity Tables

Electricity Market Module Notes