Environmental policies and their effects on utility planning and operations

Pergamon

0360-5442(94)00082-4

ENVIRONMENTAL

Ewrgv Vol. 20, No. 4. pp. 255-27 I, 1995 Copyright 0 I995 Elsevier Science Ltd Printed in Great Britain. All rights reserved 03fK-5442/95 $9.50 + 0.00

POLICIES AND THEIR EFFECTS ON UTILITY PLANNING AND OPERATIONS

BENJAMIN

F. HOBBSt$

and PAUL

CENTOLELLArj

of Systems, Control, and Industrial Engineering, Case Western Reserve University, Cleveland, OH 44106 and $Science Applications International, 655 Metro Place S, Suite 745, Columbus, OH 43017. U.S.A.

tDepartmem

(Received

18 August

1994)

Abstract-We present a taxonomy and analysis of public policies that address the environmental impacts of power production. The paper consists of two parts. The first is a classification of policy options, including command-and-control regulations, emission caps, taxes, marketable permits. emission adders, and environmental performance standards along with a review of recent developments. Examples are drawn from U.S. institutions, but the principles involved apply to environmental regulation in any nation. In the second part, we explore how various policies can affect a utility’s choice from among emission dispatch, fuel switching, and resource options. Some policies yield inefficient outcomes: i.e., strategies for which there exist alternatives that would result in both lower emissions and costs. Other policies are more likely to motivate the utility to choose efficient strategies, which generally involve a mix of DSM, investments in clean capacity, and emissions dispatch. Some policies which appear to be very different, such as emission allowances, taxes, and environmental performance standards, can yield similar-and efficient-outcomes.

INTRODUCTION

It is becoming more widely accepted that traditional command-and-control environmental regulation is an inefficient means of achieving emission reductions from the electric power sector for pollutants which mix uniformly over broad geographic areas. Energy conservation, emissions dispatching, and other pollution prevention measures often are not counted towards compliance with command-andcontrol requirements, although they can substantially reduce the cost of achieving environmental objectives.‘-3 Alternate regulatory policies, including emission caps, taxes, allowances, adders, and performance incentives are receiving greater attention. In the first part of this paper, we provide a comprehensive overview and classification of policy options for limiting the environmental impacts of utility operations. The second section of the paper illustrates the economic and environmental implications of alternate policies. Our frame of reference is the extent to which alternate policies tend to produce economically efficient results from a societal perspective. Environmental regulation is intended to address the existence of environmental externalities, environmental impacts which shift costs from the sources of pollution to other people in a manner not directly controlled by markets for goods and services. A negative environmental externality arises when some individual’s utility (e.g., health, security, enjoyment, etc.) or production relationships are affected by real (i.e., non-monetary) environmental variables under the influence or control of others who are not required to pay a price for their activities equal to the cost which those activities impose on others.4 As this definition implies, not all residual emissions are environmental externalities. In an efficient world in which all environmental costs were internalized (i.e., where pollution sources were required to pay for each incremental ton of emissions an amount equal to its societal cost), there would still be pollution. Further emission reductions would not be made if the damage caused by the last ton of emissions were less than the cost of an additional ton of emission reduction. Under conditions of economic efficiency, sources of pollution (and customers in the product markets they serve) would adopt every measure to avoid or reduce emissions which had an incremental cost less than the marginal societal benefits from such emission reductions. Our analysis focuses on utility operations and resource acquisition and the extent to which alternate policies permit or encourage the

: To whom all correspondence

should be addressed. 255

Benjamin F. Hobbs and Paul Centolella

256 identification policies

and implementation

may have pricing

of least-cost

implications

which

environmental affect

strategies.

the efficient

We also recognize

allocation

that different

of resources.

CLASSIFICATION OF ENVIRONMENTAL POLICIES AFFECTING UTILITY PLANNING AND OPERATIONS

In this section, we identify types of environmental and utility regulatory policies affecting the environmental impacts of utility operations. It includes a brief history of policy development, examples of policy implementation, and general comments on the effectiveness of policies in internalizing environmental costs.? Command-and-control regulation

Most U.S. environmental

the form of command-and-control requirements. sources to use a specific control technology or comply with a uniform emission rate requirement, typically expressed for utility air emissions in pounds of emissions per million B.t.u. of boiler heat input. Command-and-control regulation developed as a result of historical limitations on emissions monitoring technology, fear that more sophisticated approaches could be circumvented, and the apparent administrative efficiency and fairness of uniform standards. Although continuous emissions monitoring and data management technology has advanced, environmental regulation largely has continued to follow the command-and-control model. Command-and-control air pollution control requirements typically must be met either through the use of a specified fuel or by the installation of a specified combustion or post-combustion control technology. For an electric utility, this means that the potential environmental benefits of demand-side management, improvements in heat rates, power purchases from cleaner sources, or emission (“full cost”) unit commitment and dispatching are not recognized for purposes of environmental compliance. The residual emissions, after the required control measures are implemented, are treated as having a zero economic value. Economists and policymakers have been critical of the command-and-control approach because: (i) some low cost emission reduction measures are not pursued; (ii) uniform requirements for broad categories of sources ignore differences in the costs of control at and the environmental impacts of emissions from different facilities; (iii) regulators are not in a position to identify the most cost-effective portfolio of control measures or how that mix may change over time; (iv) it creates disincentives to technology development, in that new, potentially more efficient facilities are typically subject to more stringent requirements and that sources may be required to place any new emission control technology on all their facilities; and (v) development of detailed technology standards has been time-consuming, politically controversial, and administratively costly. Command-and-control

regulation

approaches

require

has been groups

in

of similar

Emission caps

An emission cap imposes a tonnage or average emission rate limitation on a set of sources typically owned by a single firm. The emissions bubble or averaging created by this approach offers sources internal flexibility in selecting compliance strategies. Firms cannot, however, go outside the sources included in the cap to find less costly emission reduction options. One example of emission caps is Rule 1135 of the South Coast Air Quality Management District (SCAQMD), which sets system-wide caps on nitrogen oxide (NO.,) emissions from Southern California Edison, the Los Angeles Department of Water and Power, and the municipal utilities of Burbank, Glendale, and Pasadena.h The rule contains three NO., emissions limitations. First, it sets maximum daily average NO,cemission rates expressed in pounds of emissions per megawatt hour of net generation for each utility system’s total generation in the District. Because district-wide rates are utilized, each utility can adjust its generation within the District and use of other resources to meet this limit. The rule also imposes on each utility a maximum daily number of pounds of NO., emissions and, beginning in the year 2000, a maximum annual tonnage of NO_,emissions.

tFor a useful historical study of the chronology of environmental policirs impacting electric utilities, see Curlee.

Environmental

Market-based

systems of regulation:

policies, utility planning

and operations

257

taxes and emissions rights/allowances

There are two basic types of market-based systems of environmental regulation: emissions taxes or effluent fees and marketable permit or allowance systems.t Such systems provide affected sources the incentive and flexibility to achieve the lowest cost mix of pollution prevention and emission reduction measures. One classical solution to the problem of environmental externalities is a Pigovian tax, a tax on emissions equal to the marginal environmental damage cost at the point where the marginal control cost and marginal damage cost functions intersect. To date, emissions taxes have not been popular in the United States because of the costs which can be imposed on affected sources. Sources pay both for their emission reductions (with an incremental cost below the tax rate) and taxes on any residual emissions. For example, if the 1990 Clean Air Act Amendments had relied on a tax, rather than an allowance, system for Title IV sulfur dioxide (SO,) controls, the direct costs paid by utilities could have more than doubled. These direct costs do not, of course, represent the overall economic impact. The macroeconomic impact of emissions taxes is highly dependent on the distribution of tax revenues. If broad-based and used to reduce other taxes, emissions taxes can increase economic efficiency by moving prices towards societal marginal costs and redistributing demand to less polluting substitutes. An alternative form which reduces direct impacts on some sources is the “feebate” in which fees collected from high emission rate sources are rebated to cleaner sources. Marketable permit or allowance systems distribute limited authorizations to emit, which can be traded among sources as fungible commodities and are exhausted when a specified quantity of pollutant is emitted. In some systems, unused allowances may be banked from period to period. Given unhindered trading, actual emission reductions are made by the sources which can most cost-effectively do so. The distribution of compliance costs, however, depends on the original distribution of allowances. Allowances may be either distributed to specified sources-existing sources may receive allowances at no cost-or sold at auction. If allowances are auctioned off, sources’ compliance costs may resemble their costs under an equivalent emissions tax. In some marketable permit systems, a small fraction of allowances is held back from distribution and sold in a zero revenue auction to ensure market liquidity, provide price discovery, and inhibit oligopoly power. In a “zero revenue” auction, auction revenues would not be retained by the government and may be distributed in proportion to the original distribution of allowances. From 1977 to 1986, the U.S. Environmental Protection Agency (U.S. EPA) began to supplement command-and-control requirements with limited Emission Reduction Credit (ERC) trading programs: netting, offsets, bubbles, and banking.7 In each of the ERC trading programs, to create a tradeable ERC the underlying emission reduction had to be: surplus to that required to meet existing requirements; enforceable by state and federal authorities; permanent; and quantifiable in comparison to an established level of baseline emissions.x The cost and difficulty of identifying potential transactions and securing prior regulatory approval has substantially limited the creation and transfer of such credits. Because only permanent and enforceable reductions can be certified, ERC trading programs have not certified reductions based on energy conservation, emissions dispatching, or other pollution prevention measures. Despite limited use, these mechanisms reduced air pollution control costs by billions of dollars.” The 1990 Clean Air Act Amendments include two major market-based reforms: the Title IV Acid Deposition Control SOZ Allowance Program and Title I Economic Incentive Programs (EIPs). Covering virtually all electric generating facilities, Title IV will set a permanent ceiling on annual SOZ allowance allocations to utilities at 8.95 million tons. The allowance system internalizes the acid deposition costs by attaching potential economic value to each increment of SOZ emissions. For every ton of emissions, the utility either must pay to acquire an allowance, or suffers an opportunity cost, in that it could have sold an allowance. To date, over $125 million of allowances have been traded. Title I authorizes use in State and Federal Implementation Plans of EIPs, including emission fees, emission allowance systems, and other economic incentives for achieving emission reductions. U.S. EPA rules governing EIPs offer greater flexibility than EPA policies governing ERC trading programs.“’ Some areas with significant ozone (0,) non-attainment problems are developing NO., EIPs to reduce NO, contributions to O3 formation. For instance, the SCAQMD Regional Clean Air Incentives Market

?It is also possible to have a hybrid system in which regulators intervene to set a price ceiling or Hoor for home or all participants in a marketable permit system. See, for example. 42 U.S.C. 5 76510(c).

258

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(RECLAIM) program allocates NO, (and to non-utility sources SOZ) RECLAIM trading credits to most major stationary sources and provides for the generation of credits from mobile source reduction programs. ’’As another example, a collaborative design team including representatives from the Illinois EPA, Commonwealth Edison, and the Environmental Defense Fund have developed a proposed NO, trading system for 63 major utility and non-utility sources in Northeast Illinois.‘* Finally, the Northeast States for Coordinated Air Use Management (NESCAUM), a regional air quality regulation coordination agency, is developing a proposed regional system of NO, caps which could cover the states of Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont (and potentially could be extended to other states in the Ozone Transport Region).‘” NO, EIPs such as these are an attractive O3 attainment strategy because the alternative could be a costly second phase of Reasonably Available Control Technology standards requiring installation of retrofit control technology on all existing sources.2 The basic difference between the tax and allowance approaches is that a tax system limits the maximum amount that any source is likely to spend on emission reductions, while an allowance system ensures that emissions from covered sources will not exceed a specified (annual or cumulative) quantity without regard to the cost of the last unit of emission reduction. If policymakers had perfect knowledge, either approach could be structured to achieve an equivalent result. Under conditions of uncertainty, however, if the marginal cost of further emission reductions is rising more rapidly than the rate of change in the value of marginal emission reductions (i.e. slope of the marginal cost function exceeds the slope of the marginal benefit function), an emissions tax approach may tend to produce smaller distortions from an economically efficient result.4 Adders and consideration of externalities in resource planning Public utility commissions are requiring utilities to consider environmental externalities in resource planning and long-term resource acquisition, either qualitatively or through the use of an adder or shadow price that is added to the direct costs of resource options for planning and resource selection purposes only. By 1992, utility regulators in 41 states had begun implementing integrated resource planning (IRP). In 3 1 of these states, regulators are in some way considering environmental externalities in the resource planning or resource acquisition process. Of these, 13 states reported that externalities are either explicitly quantified and included in economic tests (8 states), considered on both a qualitative and quantitative basis (8 states, with overlap of 4), or considered quantitatively through the internalization of the risk of future regulation ( 1 state).14 For some states (e.g. Massachusetts, Nevada, and New York), the application of adders reflecting quantified monetary valuations of environmental impacts has been a logical result of applying benefit/cost tests which seek to quantify the total cost of alternate resource options. In other jurisdictions (e.g. Utah and Wisconsin), adders were quantified in order to meet narrower objectives, such as prudent anticipation of likely future environmental regulation or of factors which would be raised in siting proceedings. In a few states (e.g. Virginia), state statutes have been found to limit the authority of state utility regulators to use quantified externality values. Other commissions have proceeded slowly in quantifying externalities recognizing the complexity involved in imposing adders on top of existing environmental regulation. For example, the Maine Commission recommended further study citing: (i) the need for analytical work on the relationship between consideration of externalities and environmental regulation; (ii) the lack of sufficiently reliable methods for quantifying environmental impacts; (iii) in the short and intermediate term few and generally environmentally beneficial resources would be selected in any event; and (iv) a lack of Commission staff and financial resources.‘s Connecticut is the first state to adopt a trade-off analysis approach in which the direct costs and emission levels associated with alternate resource plans are compared, but externality valuations are not monetized in advance.16 Multi-attribute trade-off analysis can identify relatively low cost emission reductions and resource options that are robust under alternate futures, help parties supporting different externality valuations to focus on actual resource choices, and preserve regulatory discretion.‘7,‘x The discussion of adders has led commissions to consider the often significant environmental impacts of electricity generation, but adders have not been used to fully internalize environmental costs.‘“.” First, application of adders has been limited to the planning or acquisition of new resources, where such decisions are subject to explicit Commission review, and has not yet been extended to unit commit-

Environmental

policies. utility planning

and operations

259

ment and dispatch or other aspects of utility operations. Second, adders, in some cases, have been applied to the emissions of new resources, ignoring the impact of introducing such resources into the existing utility generation mix. Third, adders do not create the direct incentives to lower emission reduction costs that would be created by an actual emissions tax. Fourth, the use of adders does not result in adjustments in electric rates to reflect external costs; thus, externalities are not internalized into consumer decisions to consume electricity. Because of the difficulty in developing reliable and comprehensive environmental damage cost assessments, adder values in some cases have been based on marginal control costs which may greatly exceed the minimum cost for achieving desired environmental objectives. It should be remembered that command-and-control environmental regulations are designed not only to lower emissions, but to allocate costs among new and existing units. Indeed, in some cases, more stringent new source standards imply higher total regional emissions as the purchase of fewer offsetting emission reductions would be required to permit the new source. While several efforts are underway to improve damage cost assessment, uncertainty over valuation continues to hinder public utility commission consideration of environmental impacts. Performance standards and shared environmental savings Utility regulators could use performance standards to mimic the incentives of market-based environmental regulation. Performance standards could function as a “soft” emissions cap, in that the utility would have an emissions reduction target, but would not be expected to implement measures with an incremental cost higher than a pre-specified limit. There have been efforts to negotiate environmental performance incentives, although, to date, no commission has adopted this approach. There are four key elements in an incentive-based performance standard: (i) a baseline level of emissions from which to measure environmental performance; (ii) a reasonable target for environmental improvement such that incentives (and disincentives) may be tied to the percentage of target improvement achieved; (iii) a maximum authorized incremental cost per ton of reduction up to which the utility may reasonably spend; and (iv) a structure of incentives (and disincentives) sufficient to motivate performance. Baseline emissions could be average historical emissions for a representative period. This approach, however, does not take into consideration the range of external factors, e.g. population, economic growth, fuel costs, weather, etc., that may influence a utility’s environmental performance. An altemative would be the development of a statistical baseline. Much as utilities develop statistical models for making short term load forecasts, for many utilities it may be possible to develop a reasonable statistical model which would estimate emissions based on coefficients developed from historical data. Actual utility emissions could then be compared to a model backcast of expected emissions and the percentage change used as an indicator of progress. Public utility commissions could develop standards based on a broad index of emissions or find performance incentives to be an attractive policy for rewarding achievement of utility carbon emission stabilization commitments under the U.S. Department of Energy’s Climate Challenge program. The Climate Challenge Program is a voluntary program under which agreements will be negotiated with utilities to limit greenhouse gas emissions. Resulting emission reductions can be reported to the Department under the 1992 Energy Policy Act 5 1605(b) voluntary reporting guidelines and might receive credit in any future mandatory program. The relatively simple but elegant approach of environmental performance standards could provide the utility shareholders an opportunity to share in the public benefits of reduced greenhouse gas or other emissions. EFFECT OF POLICIES

ON UTILITY PLANNING

AND OPERATIONS

The various environmental policies discussed above-command-and-control regulations, emission caps, taxes, marketable permits, and emission adders-can impact all aspects of utility system planning and operation. In the remainder of this paper, we explore the relationships between utility choices and environmental impacts, as they are affected by the particular policies adopted. We do this using as an example a simple generation system that has two “products”: electricity and COZ. Different planning and operating decisions result in different combinations of generation cost and emissions. We focus here on resource operation and acquisition; however, there are also other options

Benjamin F. Hobbs and Paul Centolella

260

available to utilities for lowering net emissions. One is offsets, such as the purchase of SO2 allowances or the planting of trees in Central America. Another is the adoption of rate policies that reflect external costs in the price of power. *’We explore how various regulatory policies can affect a utility’s resource decisions. Some policies will yield inefficient outcomes: i.e., plans and operating strategies for which there exist alternatives that would result in both lower emissions and costs. Other policies are more likely motivate the utility to choose efficient mixes. A multiobjective

framework

for evaluating

resource options and operating strategies

Multiobjective plots, such as Fig. 1, are a useful tool for understanding how coherent environmental compliance plans can be assembled. We use this device to illustrate how long-run resource acquisition decisions and short-run system operation strategies complement each other; both are needed in order to ensure an efficient outcome. Multiobjective plots can show how the options available to the utility affect important objectives, such as costs, rates, emissions, resource use, and financial indices. Figure 1 is a two-dimensional plot in which the only objectives are incremental internal cost (the y-axis) and CO2 emissions (the x-axis). Internal cost represents all variable costs of generation plus the annualized expense of any new generation plants and DSM programs. In general, each point can be a distinct plan representing a particular combination of supply sources, environmental controls, demand-side management programs, and rate design, along with a unique operating strategy. To be concrete, we illustrate the concepts by examining the options facing a hypothetical small utility in the year 2010. The utility’s peak load in that year is projected to be 1050 MW. Its present generation mix consists of three coal units (totaling 500 MW), an oil-fired steam unit (150 MW), and natural gasfired combustion turbines (200 MW). The options it has available for meeting loads and decreasing emissions include emissions dispatch (operating cleaner plants more and dirtier plants less), fuel switching (in particular, cofiring natural gas at the second coal unit), acquiring supplies (new pulverized coal plants, gas-fired combined cycle, or combustion turbine capacity), and investing in energy efficiency (DSM-EE) and load controls (DSM-LC). The costs of the DSM options are described using a “conservation supply curve” in which the per unit cost increases for larger programs. The linear programming model used to analyze this system is summarized in the Appendix, where we also tabulate our numerical assumptions. The exact cost assumptions do not affect our conclusions concerning the relative efficiency of the different policies. Figure 1 shows the resource additions made in each of several plans, under the assumption that least Incremental

Cost ($Million/Yr)

‘6sm

160 -

155

4.4

4.5

4.6

4.7

COz Emissions Fig.

I.

Tradeoff

4.6

4.9

(Mllllon

plot: CO, vs cost for seven plans (least utility

5

5.1

5.2

Tons/W) cost dispatch assumed in each case).

Environmental

policies, utility planning and operations

261

cost dispatch is used to operate the system’s power plants.? Some plans in Fig. 1 yield both high internal costs and high emissions (e.g., Plan G). These plans are obviously less desirable than other plans which have both lower costs and emissions (such as Plan A). Plans that are not dominated by any other plans are known as efficient alternatives (here, Plans A, B, C, and D, which we connect by a dotted line). Alternatives to a particular efficient plan have either worse costs or worse emissions. If all a planner cares about is revenue requirements and CO*, then only efficient plans are of interest.2”-26 In Fig. 2, we expand the options to include emissions dispatch and natural gas cofiring. Emissions dispatch is the operation of a power system so that more generation is obtained from cleaner units than would be the case under least cost dispatch. Emissions dispatch is usually implemented in practice by constructing the merit order of generating units using the sum of variable utility cost plus a penalty on emissions. In Fig. 2, a range of penalties between $0 and $30/tori are applied; increasing the penalty results in lower emissions but higher costs. Thin lines connect points that represent different operating policies using the same set of facilities. One plan (Plan D) also includes the operating option of burning natural gas in one of the coal units; this is done if the CO2 penalty is sufficiently high to overcome the cost penalty of gas relative to coal. Comparing Figs. 1 and 2, we see that including operational strategies has greatly increased the possibilities for decreasing emissions. Indeed, it turns out that every efficient strategy except the least cost point involves some degree of emissions dispatch. Several recent studies of actual utility systems confirm this fact (e.g., Refs. 3,27,28,29). In Fig. 2 we label the efficient points PO through P,,, and connect them with a dotted line. The subscript represents the CO, penalty at which an efficient point minimizes the sum of utility costs plus CO2 penalties. For example, P20 is the strategy which has the lowest value of utility cost plus $20/tori times the COZ emissions. Environmental planning can be viewed as the process by which the utility chooses from the possibilities in Fig. 2. The government sets some rules as to which points are admissible and how the utility should weigh the tradeoffs between the two objectives of minimizing internal costs and minimizing emissions. These rules may be very tight, giving the utility little discretion, or they may allow considerable flexibility. In the remainder of this paper, we discuss how in general alternative government environmental incremental Cost ($Million/Yr) 175 ..

150

-

155

-

of strategies

3.8

4

4.2

4.4

4.6

4.5

5

CO, Emissions (Million Tons/Yr) -A:

No DSM

+ B: 40 MW DSM

x

C: 00 MW DSM

*D:

DSM & Cotire

x

8

G: New Coal

E: 126 MW DSM, (No Comb. Cycle)

Fig. 2. Identitication of efficient combinations of resource and operating strategies.

?Details on the case study results can be found in our full report.”

5.2

Benjamin F. Hobbs and Paul Centolella

262

The policies we consider include: traditional command-and-control regulations; emissions caps; internalization of environmental costs via taxes or marketable emissions rights; and internalization of environmental costs via planning regulations. The policies are compared in terms of whether they motivate the utility to choose an efficient plan, and whether that plan also minimizes total social cost. “Social” cost is defined for our purposes as the sum of utility costs plus emissions of each type times the appropriate damage cost per ton for each type. As a hypothetical case, if damages are, say, $lO/ton for CO*, then the least social cost plan in Fig. 2 is Plan P,,, which is the point at which the marginal internal cost of reducing emissions further by moving to Plan PIs exceeds $lO/ton.t policies affect utility planning.

Command-and-control

regulations

Examples of command-and-control regulation include local restrictions on fuel sulfur content and New Source Performance Standards. The effect of policies of this type would be to render some of the points in Fig. 2 illegal. Only those plans that conform to the regulations can be considered. The utility is then free to choose from the permissable plans in order to minimize its internal cost; thus, the emissions of those plans are disregarded at this stage. For instance, say that a CO2 policy is adopted that prohibits new coal plants or new fossil-fuel plants with heat rates worse than 9000 B.t.u./kWh. For our hypothetical utility, this results in elimination of all alternatives involving new combustion turbines and coal plants, leaving just the strategies represented by the thin line in Fig. 3. The utility will choose Plan PcsLc (“Command-and-Control”), which is the cheapest plan that excludes new plants of that type. By focusing on individual supply resources, fuels, and emissions controls, the command-and-control approach ignores the environmental control benefits of DSM and emissions dispatch. As a result, superior solutions that have lower costs and emissions may be prematurely eliminated. For instance, Plan PI0 in Fig. 3 represents a combination of DSM programs and emissions dispatch together with some combustion turbine additions. The new turbines lower the system’s cost, but also makes the plan Incremental Cost ($Mlllion/Yr)

175) a ho ‘.,

Only hssible set of options under bsn of new coal It CT

Strstegy selected

3.4

3.6

3.8

4

4.2

4.4

4.6

4.8

5

J

5.2

CO, Emissions (Mlllion Tons/%)

??

??

A: No DSY

_

D: DSM & Coflre

+B:4oMWDSM *F:

m C: 80 MW DSM

No CT or Coal, X G: New Coal (222Mw

cc,

2oMw

DSM)

Fig. 3. lnefticiency of a ban on new coal and combustion turbine facilities.

tWe

assume that changes in the expense of electricity do not induce consumers to alter the amount of power they consume. Rate feedback tends to lower cos&, emissions, and the value received by customers (see Refs. 3.21.22). We also ignore emissions from energy sources that compete with electricity, which might increase if the price of electricity is raised.

263

Environmental policies, utility planning and operations

illegal in this case. The utility could compensate for the higher emissions rate of the turbines through dispatch and DSM, but command-and-control regulations do not permit consideration of that strategy. The result is that the utility will choose Pcac instead, which unfortunately gives both higher costs and more emissions than point P,(). An unfortunate consequence of command-and-control regulation is that even if the environmental damages of CO, are high, the utility has no incentive to use dispatch and DSM to reduce emissions beyond what the law requires. This is true even if the cost of doing so is small compared to those damages. Thus, the utility’s choice under command-and-control regulation is unlikely to minimize total social cost. Emissions cap

Another philosophy of environmental regulation involves imposing a cap on total emissions, and has performance standards, disbeen called “environmental least-cost utility planning.““’ Environmental cussed above, can be viewed as a variant of this approach. This policy specifies the problem as follows: the utility is to minimize its internal cost, subject to a constraint on overall emissions. For instance, Fig. 4 shows the effect of imposing of a cap of 4.4 million tons/year of CO?, 10% below the least cost level. It would motivate the utility to choose point P,sr as all the lower cost points to the right of the constraint are rendered infeasible by the cap. The advantage of emissions caps over the command-and-control approach is that the utility can freely choose from any combination of supply resources, emissions controls, DSM programs, and dispatch strategies in order to meet the constraint. Unlike command-and-control regulations, an efficient point will always result from this process, at least in theory. If the cap happens to be set at the least social cost point, then this policy is also optimal. A variation of the cap approach is to constrain the average emission rate, measured in terms of kg/kWh or Ib/MB.t.u. of heat input. Constraining a rate rather than total emissions can yield operating difficulties” and dominated solutions, especially if the rate is based on only the generation of a subset of units. No incentive is given for DSM or to shift generation to less sensitive areas by, for instance, power purchases.

Incremental

Cost ($Million/Yr)

175

C

r \. pm

Pd\

170

\

\

\

Stretegies violate

Strategies comply with cap

x \

)

cap

x

165

X XX

160

* P-5 ‘1 Utility chooses least-cost? strategy that meets cap

3.4

3.6

3.6

4

4.2

CO, Emissions

I

4.4 (Mlllion

4.6

4.6

5

Tons/Yr)

’ A: No DSM

-c B: 40 MW DSM

+&C: 80 MW ----I DSM

m D: DSM 81 Cofire

X F: No CT or Coal,

X G: New Coal

(255MW CC, WMW DSM)

Fig. 4. Effect of imposition of a CO, cap upon utility’s choice of resource plan

5.2

264

Market-based

Benjamin F. Hobbs and Paul Centolella

systems: taxes and emissions rights/allowances

External environmental costs can be internalized by imposing emissions taxes or by creating marketable rights to pollute. The effect of taxes and marketable rights is to make emissions an internal cost from the utility’s perspective. For instance, let us assume that a CO2 tax of $lYton is levied or, alternatively, that a utility must secure emissions allowances whose market price is $15/tori..”Our hypothetical utility will minimize its costs by minimizing the sum of its capital, fuel, and variable costs Cost (the y axis of the figures) plus $15*C02, where CO2 is its emissions (the x axis). This process is shown in Fig. 5 in which isoquants of the quantity Cost + $15*CO, are shown. The point lying on the lowest such isoquant is the plan that minimizes the utility’s total cost. In Fig. 5, this is point P,s. Like the emissions cap approach, but unlike command-and-control regulations, the chosen strategy is in theory efficient because the benefits of all options for reducing emissions, including DSM and dispatch, are recognized. If the allowance price/tax happens to equal the marginal damage of emissions, then the solution is also socially optimal. Adders and other requirements

for considering

external costs

Another means of internalizing environmental costs is for the government to require that the utility estimate and consider external costs when making resource acquisition or operation decisions. Environmental impact statements are examples of such requirements. Several states have gone further by specifying particular numerical adders to be considered in the decision calculus. The utility does not actually pay these costs, unlike the tax or emissions allowance systems; it is merely forced by regulation to make decisions as if it does. The most common version of this requirement in the U.S. applies only to decisions concerning resource acquisition. For our hypothetical utility, this would mean that the “cost”, including adders, of new combustion turbines, combined cycle facilities, and coal plants would be increased relative to energy conservation. In theory, however, adders could also be extended to dispatch and pricing decisions.“‘.“* If the utility is forced to consider external costs in all its resource operation and procurement decisions, the effect would be the same as an emissions tax (Fig. 5). An efficient plan would be chosen and, if the estimated external cost was an accurate estimate of actual damages, the least social cost plan would be achieved. This happy outcome is unlikely to occur, however, if external costs are only factored into resource Incremental Cost ($Milllon/Yr)(Excludes

taxes, allowance costs)

175 170 ~-

p%F., p,. .

*. x f. -. *. x 165 pk booquants of )p.8 *. . .+ c0.H + $15*co*

X XX

Ut///ty chooses strategy that minlmlzes Cost + $lS/CO,

160 -

, 5o _ for Coat + SWCO,

3.4

3.6

3.6

4

4.2

4.4

4.6

4.6

5

5.2

CO, Emissions (Mllllon TonslYr) I

I

a A:

No DSM

m D: DSM & Co&e

_L B: 40 MW DSM

m C: 60 MW DSM

X F: No CT or Coal X 0: New Coal (106Mw cc, OOMW DSM)

Fig. 5. Effect of CO2 tax of $lYton

upon utility’s choice of resource plan.

Environmental policies, utility planning and operations

265

procurement decisions and not into operation. The environmental costs of capacity expansion and DSM programs would be considered, but the utility would dispatch its resources to minimize internal cost. This is inefficient because, as we pointed out earlier, efficient alternatives almost always include some degree of emissions dispatch. These inconsistent incentives can lead to inefficient decisions, such as the adoption of expensive pollution controls when changes in dispatch order would accomplish the same emissions reductions at less cost. Thus, just like command-and-control regulations, this policy can result in the choice of an inferior alternative over a superior one.24.33 As another example of such an inefficiency, uneconomic life extension of coal units might be encouraged because such decisions would not be subject to the adders system. Consider three resource options that might be compared by our hypothetical utility: (i) construction of 145 MW of combined cycle capacity; (ii) a load control program that clips 40 MW off the system peak, plus 86 MW (peak) of energy efficiency programs; and (iii) life extension of a 145 MW coal-fired unit that would otherwise be retired. Each option is paired with 2 12 MW of new combustion turbines. The amount of each resource is chosen so that the system achieves a 15% reserve margin. Table 1 summarizes the costs and emissions of each resource, based on how they would be dispatched in our hypothetical system. Under least-cost dispatch, the combined cycle unit would be cycled (capacity factor = 0.29), while the repowered coal unit would instead be base loaded (capacity factor = 0.85). The different resources might be compared on a $ per MWh basis, with the following definitions of the numerator and denominator. The numerator would be either the utility cost (which excludes CO2 costs) or total societal cost (which includes those costs) directly associated with the investment and operation of the new resources. Changes in the dispatch and resulting variable costs of existing resources are ignored. Meanwhile, the denominator would be the anticipated energy output of the resource (if a new supply) or the energy savings (if DSM). Again, we disregard changes in the operation of existing resources. For the sake of argument, we assume in the societal cost calculation that the external cost of CO, emissions is $30/tori but no emissions dispatch takes place. Under these assumptions, life extension has the lowest $ per MWh cost from the utility’s perspective, costing $43/MWh. But from so&q’s point of view, the CO, penalty causes repowering’s cost to jump to $76/MWh; in that case, the DSM program is the least expensive, costing $70/MWh. In contrast, the combined cycle plant is apparently the most costly program from either perspective, with a utility cost of $74/MWh and a social cost of $89/MWh. Yet these results are misleading because those resources are used very differently. Table 2 presents the resulting costs and emissions for the entire system. A comparison of the total system results reveals that the combined cycle unit yields the lowest system-wide cost for the utility, mainly because of its dispatching flexibility. The DSM option is most expensive. So, in the absence of an adder or tax upon CO? emissions, the utility would recommend construction of the combined cycle unit. But if a $30 adder was applied to CO, emissions from just new resources, 2-d not life extension of existing units, then the decision would be different. Regulators would conclude that DSM was definitely cheaper-whether by the $/MWh or total social cost figure (which includes a $30/tori CO2 adder on new source emissions). As a result, the combined cycle plant would not be approved. In that case, the utility would decide instead to extend the life of the coal unit, since that decision is not subject to the adders system and has the next lowest utility system cost. If that happens, the effect of the adders policy is a decision that yields both higher costs and higher emissions than would have been the case if there was no adders policy (compare the combined cycle and repowering alternatives in Table 2). Although this example is contrived, it does illustrate the possibility that adders applied only to new resource additions can make matters worse from both an economic and environmental perspective. CONCLUSIONS

At least with respect to pollutants which mix uniformly over broad geographic areas, such as SO,, NO.,, greenhouse gases, and some air toxics, broad market-based environmental regulation offers the greatest potential for minimizing the costs of achieving emission reductions. In the absence of a marketbased system of environmental regulation, utility regulatc;rs can achieve similar results by implementing environmental performance standards. Such standards can efficiently produce near-term emission reductions and create incentives to identify and implement lower cost pollution prevention and emission reduction measures. If a guideline on maximum allowable incremental cost for emission reduction is

Resource option

14.5 MW combined cycle, gas fired 126 MW DSM Repowering of 145 MW coal plant

_

$ I3,9000.000 $27,000,000 $24,100,000

$13,400,000 $0 $22,700,000

(Vyr)

Annual variable cost

I76.000 0 1.195,OOo

comparison.

368,000 385,000 I ,080,OOO

Energy produced or saved (MWh/yr)

three-resource

CO? produced by resource (tons/yr)

1. Per-MWh utility and societal cost calculations,

Annualized capital cost ($lyr)

Table

$74.2 $70.1 $43.3

Utility cost of option ($/MWh)

$88.5 $70. I $75.7

Social cost of option (@$30/tan) ($IMWh)

Environmental policies, utility planning and operations

267

Table 2. Total utility system cost and societal cost calculations, three-resource comparison. Resource option

145 MW combined cycle, gas fired+ I26 MW DSM Repowering of 145 MW coal plants

Utility cost for entire system

System CO? produced

System costs adjusted by CO2 adder (including CC CO, costs)

(Vyr)

(tonslyr)

($lyr)

$ I50,300,ooo $153,6oo,ooo $152,000,000

4,880,ooO 4,660,000

$ I55.600,000 $ I53,600,000 $ I52,ooo.ooot

5,090,~

System societal cost (@$30/tan)

($/yr) $296,7OO,OCO $293,400,000 $304,700#00

tSystem cost excludes coal-plant CO, because these emissions are not subject to the CO, adder. *Preferred by utility if no adder policy. #Preferred by utility under adder policy.

included, performance standards are less likely to depart significantly from an efficient balance of costs and environmental quality than an absolute emissions cap. By contrast, externality adders provide limited near-term benefits, no direct incentive to reduce emission control costs, and, under some conditions can worsen both utility costs and environmental impacts. If retail competition is introduced into the generation services market, new policy tools may be required to reconcile the commodity price reduction incentives produced by competition and other energy and environmental policy objectives. Market-based environmental regulation represents one means of achieving environmental objectives given a competitive generation services market. With a spot market or U.K.-style pool for generation services, an environmental performance standard implemented by the pool through revenue neutral “feebates” can approximate the effects of marketbased environmental regulation. Acknowledgements-An earlier version of this paper was presented at the 1994 Summer Study of the American Council for an Energy Efficient Economy. We gratefully acknowledge the sponsorship of this research by the National Regulatory Research Institute, funded by the National Association of Regulatory Utility Commissioners. However, the opinions expressed are the responsibility of the authors, and do not necessarily represent the position of NRRI, NARUC. or its member commissions.

REFERENCES

I. P. A. Centolella,

E. L. Miller, H. S. Geller, and P. M. Miller, “Clearing the Air: Using Energy Conservation to

Reduce Acid Rain Compliance Costs in Ohio,” Ohio Office of the Consumers’ Council, Columbus, OH ( 1988). Conference,” p. 125, Synergic 2. P. A. Centolella, in “Proceedings of the DSM and the Global Environment Resources Corp., Bala Cynwyd, PA ( 1993). 3. B. F. Hobbs and J. S. Heslin, in “ACEEE 1990 Summer Study on Energy Efficiency in Buildings,” pp. 4.654.77, American Council for an Energy Efficient Economy, Washington, DC ( 1990). Policv, 2nd ed., Cambridge Univ. Press, Cam4. W. J. Baumol and W. E. Oates, The Theor?/ of Environmental bridge ( 1988). 5. T. R. Curlee, Energy Policy 22, 926 ( 1993). 6. South Coast Air Quality Management District, “Rule 1135. Emissions of Oxides of Nitrogen from Electric

7. 8. 9. 10. Il. 12. 13.

14.

Power Generating Systems,” Los Angeles, CA, adopted August 4, 1989 and amended 21 December 1990 & I9 July 1991 (1991,. T. H. Tietenberg, “Emissions Trading and Exercise in Reforming Pollution Policy,” Resources for the Future. Inc., Washington, DC ( 198.5). U.S. Environmental Protection Agency, Federal Register 51, 43829 ( 1986). R. W. Hahn and G. L. Hester, Yale J. Regul. 6, 109 ( 1989). U.S. Environmental Protection Agency, “Economic Incentive Program Rules,” Federal Register 59, 16690. 7 April ( 1994). South Coast Air Quality Management District, “Regulation XX, Rule 2000 et seq..” Los Angeles, CA ( 1993). Illinois Environmental Protection Agency, “Draft Proposal: Design for NO, Trading System,” Springfield, IL (1993). “Development of a Market-Based Emissions Cap Northeast States for Coordinated Air Use Management, System for NO, in the NESCAUM Region: Project Summary for Section I05 State Air Grant Funds for Market-Based Initiatives,” Boston, MA ( 1992). National Association of Regulatory Utility Commissioners, “Utility Regulatory Policy in the United States and Canada,” p. 420, Washington, DC ( 1993).

Benjamin F. Hobbs and Paul Centolella

268

15. Maine Public Utilities Commission, “Environmental and Economic Impacts: A Review and Analysis of its Role in Maine Energy Policy” ( 199 1). 16. Connecticut Department of Public Utility Control, “Investigation of the External Costs and Benefits Associated with Energy Consumption, Docket No. 92-90-29, Report to the General Assembly, Hartford, CT ( 1993). 17. C. J. Andrews, Environmental Impact Assessment Rev. 12, 185(1992). 18. B. F. Hobbs and P. Meier, IEEE Trans. Power Systems, 9(4), 181 I (1994). 19. P. L. Joskow, Elec. J. S(4), 53 ( 1992). 20. J. Tschirhart, The Energy J. 15(l), 121(1994). 21. C.-K. Woo, B. F. Hobbs, R. Orans, R. Pupp, and B. Hot%, The Energy J. 15(3), 43 ( 1994). 22. K. Rose, P. A. Centolella, and B. F. Hobbs, “Public Utility Commission Treatment of Environmental Externalities,” Report NRRI-94-10, National Regulatory Research Institute, Columbus, OH (June 1994). 23. W. J. Burke, H. M. Merrill, and F. C. Schweppe, IEEE Trans. Power Systems 3, 1284 (1988). 24. C. J. Andrews, Energy Policy 20, 450 (1992). 25. T. Gjengedal, 0. Hansen, and S. Johansen, IEEE Trans. Energy Conversion 7, 367 ( 1992). 26. E. 0. Crousillat, P. Dorfner, and H. M. Merrill, IEEE Trans. Power Systems 8, 887 (1993). 27. S. W. Hess, D. Parker, and J. E. Alms, “Planning System Operations to Meet NO, Constraints,” IEEE Computer Appl. Power 5, 10 (July, 1992). 28. T. M. Jackson, C. C. Stansberry Jr., and S. Ester, IEEE Computer Appl. Power 6, 46 (April 1993). 29. C. Mamay, “Intermittent Electrical Dispatch Penalties for Air Quality Improvement,” Ph.D. Dissertation, University of California, Berkeley, CA (1993). 30. S. Brick and G. Edgar, Elec. J. 56 (July 1990). 3 1. S. Bemow, B. Biewald, and D. Matron, Elec. J. 20 (March 199 1). 32. J. F. Busch and F. L. Krause. IEEE Trans. Power Systems 6 (1993). 33. K. L. Palmer and A. 3. Krupnick, Resources 105,Resources for the Future, Washington, DC ( 1991). 34. R. Turvey and D. Anderson, Electricity Economics: Essays and Case Studies, The Johns Hopkins Univ. Press,

Baltimore, MD (1977). 35. D. T. Hoog and B. F. Hobbs, Energy-The

International Journal 18, 1153 ( 1993).

APPENDIX

A Simple Linear Programming

IRP Model

We use a linear programming (LP) model to optimize the mix of resource acquisition and generation dispatch, based upon the generation model of Turvey and Andersons4 modified to accommodate DSM programs. 3s The formulation of any optimization model consists of a description of its decision variables, objective(s), and constraints. Lower case letters designate decision variables, while capital letters define fixed parameters supplied by the analyst. There are three basic decision variables in our model. The first is xi, the generation capacity (MW) of supply resource i, i = 1,2,. . .,I. Supply resources can include not only utility-owned generation plants, but also purchases from other utilities or independent generators of power. For existing plants, the value of this variable is fixed and is not altered in the LP. Second is g;,, the MW output during subperiod t, t = 1,2, . . .,T of supply resource i. The 8760 hours in each year are divided into T demand periods. The first period represents peak demand, while the last period T is the lowest demand period. Commonly, these models include three to six periods; additional periods generally contribute little to model accuracy. This variable was modified for the cofired generating unit to allow the unit to choose between using 100% coal and 85% coal/l5% natural gas. The third decision variable is d,, which equals 1 if DSM program k is fully implemented, k = 1,2,. . .K. Intermediate values between 0 and 1 represent partial implementation. Our objective is to minimize the annual worth of capital and operating costs, viz.,

Min Cost = c

CRF*CXsi

+ 2

i=l,2...../ +c

i=l,Z...,/

CRF*CDJL k=1.2,...,K

c

H, (CGi, + PEN*C02;,)g;,

,=1,2.....T

(Al)

where the fixed parameters are defined as follows. CD, is the capital and other fixed costs ($) of fully implementing DSM program k. CO2i, is the CO2 emissions (tons/MWh) of generation from unit i

Environmental

policies, utility planning and operations

269

during subperiod r. This is the product of the unit’s heat rate and the CO* resulting from burning one unit of fuel. CRF is the capital recovery factor (l/yr) used to annualize capital costs. CX; represents capital and other fixed costs ($/MW) of building capacity of type i. In general, this parameter should include the present worth of the resource’s fixed O&M costs, while deducting the resource’s salvage value at the end of the planning period. For existing plants, this cost is omitted, as their capacity is fixed. CG, equals the variable operating cost ($/MW/hour) during subperiod t of supply type i. This cost includes fuel and any miscellaneous variable operating costs, i.e. CG;, = HR;, FC, + VO&M;, ,

C.42)

where HR;, is the unit heat rate (fuel energy/kWh), FC;, is the fuel cost ($/fuel energy), and VO&M, is the nonfuel variable O&M cost. For some supply resources, variable costs may be the same in all t of a given year, but for others, costs may vary due to temperature-dependent heat rates or seasonal variations in fuel prices. The parameter H, is the number of hours in time period t. Finally, PEN represents the $/ton penalty applied to CO, emissions. If the values of all xi and dk are fixed, then application of this penalty results in emissions dispatch (i.e. some reduction in emissions with an increase in other operating expenses). If, on the other hand, those capacity resources are allowed to vary, then the mix of resources will be chosen to minimize the utility’s cost plus CO* penalties. Demand, operating, and reliability constraints restrict which values of the decision variables can be chosen. Simple yet typical formulations of these constraints are given below. Consistent with standard mathematical programming notation, we list terms involving decision variables on the left hand side of the equation, while constants are placed on the right. Load must be met in each subperiod t of each year y:

c

gir-

,=1,2.....1

c

SAV,&

2 LOAD, for all

t,

(A3)

k=1,2,....K

where LOAD, is the MW load during t, including transmission and distribution losses, and SAVI, is the MW savings resulting from fully implementing DSM program k. This constraint states that the sum of the MW output in subperiod t from all plants must equal or exceed the electricity demanded LOAD, at that time, as modified by any DSM programs. Generation must be no more than derated capacity for each resource in each t and y: g,,-(1

-FOR,)x,
1,2 ,..., T-l.

(A4)

where FOR, is the forced or unplanned outage rate of resource i. This constraint is usually not needed for the time of lowest demand (subperiod T), as long as the annual energy constraint (A6) is also imposed. If the resource is an existing plant, then x, is fixed and its term is instead placed on the right side of the equation. Generation must be no less than the must run capacity for each resource in each t and y: g,, - MR$; 1 0 ,

(AS)

with MR, being the minimum level of output (as a fraction of total capacity). Annual energy constraint for each resource:

c

H,g, - 8760 CF,J; c 0 for all i , ,=I.?.....T

(Ah)

where CF, is the maximum possible capacity factor (output/capacity) for resource i. Again, for existing resources, x, is a constant and instead appears on the right side of the equation. Reserve margin constraint:

c

r=l.2...../

EGY 20:4-G

x, + 2

SAVmw4 !.=1,2.....K

2 LOAD,md l+M) ,

(A71

Benjamin F. Hobbs and Paul Centolella

270

where LOADPEAKis the peak demand, and M is the desired reserve margin. Upper bound on new capacity: xi S XiMAXfor all i .

(As)

This constraint allows additions to be no more than a predetermined maximum size XjMAX. Upper bound on DSM programs: dk S 1for all k .

(A9)

Nonnegativity restrictions for all variables: (AlO)

Once the model is formulated and its parameter values estimated (Tables Al, A2, and A3), then it can be inserted into standard linear programming software and solved. The solution consists of the best values of the decision variables and the resulting total cost. Plans A-D in Fig. 1 were generated by varying PEN from $0 to $30/tori,,”and noting the resulting optimal values of Xi and dk. Varying degrees of emissions dispatch were simulated for those solutions by fixing the values of Xiand dk at their optimal values, and then using the model to dispatch the plants (gi,) under a range of values of PEN. The other plans (E, F, and G) were obtained by assuming a certain mix of plants and DSM programs (i.e., fixing the values of Xiand dk) and then using the model to dispatch those resources under various values of PEN.

Table Al.

Miscellaneous data for linear programming example.

Value

Parameter Minimum reserve margin, M Maximum additional capacity of a single type Xi,,, Capital recovery factor for plant investment CRF Load block widths If,, t = I ,2,3,4,5 Load block heights LOAD,, r=l,2,3,4,5 Coal cost, CO, emissions Natural gas cost, CO2 emissions Heavy fuel oil cost, CO? emissions

15% 400 MW I2%/year 100, 620, 1950, 2545, 3545 hours 1050, 950, 825, 525, 275 MW $1.60/mmB.t.u., 221 1blmmB.t.u. $3.80/mmB.t.u., II6 Ib1mmB.t.u. $2.6O/mmB.t.u., 168 Ib/mmB.t.u.

Table A2. Demand-side program characteristics, linear programming IRP model.

Program k A B C D tCDl

Type Energy Energy Energy Load

efhciency efficiency efticiency control

Load decrease SAV,, 40.0, 40.0, 40.0, 40 MW

by subperiod I

36.2, 31.4, 20.0, 10.5 MW 36.2, 31.4. 20.0, 10.5 MW 36.2, 31.4, 20.0. 10.5 MW peak only (no energy savings)

is obtained by multiplying the per MWh cost by Z,HR,SAV,,.

cost: $55/MWh $65/MWh $75IMWh $8OO/Peak kW

Note: n.a. = not applicable.

Install 157~ National Gas Cotire Capability,

New Combined Cycle New Combustion Turbine

G H

I

Existing Combustion Turbines Existing Coal 2 Existing Coal 3 New Coal Plant

(Scrubbers)

C D E F

I

Existing Oil Steam

Existing Coal

Type

B

A

i

Plant

Coal 2

n.a.

500 (max) 500 (max)

200 150 150 200 (max)

150

200

(MW)

Capacity x,

Table A3.

0.4

0 0

0 0.4 0 0.4

0

0.4

MR, (fraction)

Must run capacity

IO.400

8.230 13,800

13,800 10,400 Il.500 10,000

IO.200

I0,ooo

(B.t.u./kWh)

Heat rate HR,

unit data, linear programming

3

5 8

9 5 5 5

3

9

Nonfuel variable O&M VO&M (UMWh)

IRP model.

9

800 550

n.a. n.a. n.a. 1000

n.a.

n.a.

($/kW)

Capital cost CX,

0.05

0.05 0.035

0.035 0.05 0.05 0.05

0.04

0.05

Forced outage rate FOR, (fraction)

0.85

0.85 0.8

0.8 0.85 0.85 0.85

0.85

0.85

Max. capacity factor CF, (fraction)

$

f g.

B a

2. =: u” P B t. rz

8 E _. _-

$

z