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Demand Response in Capacity Markets: Reliability, Dispatch and Emission Outcomes
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Paul J. Hibbard is a Vice President at Analysis Group’s Boston office, where he applies technical, economic, and regulatory expertise to financial, policy, and strategic issues in energy industries. Mr. Hibbard has over a decade of experience in state environmental and economic regulatory agencies, most recently as Chairman of the Massachusetts Department of Public Utilities. In his dozen-year consulting career before and after the DPU, he has continuously focused on the intersection of economic and environmental policy goals in regulated industries and wholesale energy markets. As a policymaker and energy expert, Hibbard has testified extensively before legislative and regulatory agencies. Andrea M. Okie is a Manager at Analysis Group, where she specializes in energy economics, strategy, and policy in electric and natural gas industries. Ms Okie has consulted with companies, government agencies, non-profits, and other organizations on energy markets, economic and environmental regulation and strategy, and energy facility development and siting. Ms. Okie has managed projects developing business and strategic plans for regulated utilities and private energy industry companies, and assessments of electricity market design and natural gas futures price manipulation. Ms. Okie holds a Masters degree in Public Policy from the University of California at Berkeley. Pavel G. Darling is an Associate at Analysis Group, where he focuses on technical and economic analysis of key electric and natural gas industry challenges. Mr. Darling is an expert in modeling of electric power systems, policy designs, and economic impacts, and has applied modeling techniques to investigate asset development, utility merger impacts, environmental policy benefits and costs, and dispatch implications of renewable resource integration. He holds an MBA from MIT’s Sloan School of Management.
November 2012, Vol. 25, Issue 9
Demand Response in Capacity Markets: Reliability, Dispatch and Emission Outcomes Demand response plays a vital and growing role in the reliability, economics, and environmental footprint of the power industry. As the opportunity for DR integration in wholesale markets grows, so does the diversity of DR types, and the influence of DR in wholesale market outcomes. A review of DR’s roles in evolving capacity markets and the impact on power system dispatch and emissions of generation-backed DR finds some unexpected results. Paul J. Hibbard, Andrea M. Okie and Pavel G. Darling
I. Introduction Demand response (DR) plays a vital and growing role in the reliability, economics, and environmental footprint of the power industry. It is vital because it opens the door to truly effective real-time price-responsive demand in electricity markets, something that has eluded the industry (to any meaningful extent) to this point.
In an industry that requires the instantaneous balancing of supply and demand with limited economic storage capability, and that faces relatively high price volatility in underlying fuel markets, the absence of truly effective price-responsive demand contributes to several key challenges – such as the purchase of greater quantities of capacity and reserves than would otherwise be needed, and the
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prevalence of policy measures to constrain price spikes during times of scarcity. Consequently, it is difficult to overstate the potential value of wide scale and economic integration of demand response, from the perspectives of economics and energy policy. his combination of technical/economic immaturity on the one hand, and potential value on the other, has appropriately spurred the implementation of financial and policy support to accelerate the development and commercialization of demand response. Both federal and state governments and regulatory agencies have acted through a wide array of financial and policy mechanisms, including research, development, and commercialization grants, loan guarantees, and tax incentives; state ratepayer-funded support of small-scale and distributed technologies and rate policies promoting real-time pricing; exceptions to emission control requirements for behind-themeter generation that supports DR resources; and wholesale market design policies that provide favorable conditions for the integration of DR. While the past several years have seen almost continuous change in how demand resources participate in wholesale markets, it is hard to imagine rapid growth in these sectors without government and regulatory support. And grow it has. For example, the Federal Energy Regulatory Commission reported that
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demand response in organized power markets increased by more than 16 percent between 2009 and 2010 alone, increasing from 27,189 MW to 31,702 MW, accounting for between 2.3 percent (ERCOT) and 10.5 percent (PJM) of peak demand in regional transmission organizations (RTO).1 This is a remarkable rate of growth, and one that is expected to continue in the coming years.
The combination of technical/economic immaturity on the one hand, and potential value on the other, has appropriately spurred the implementation of financial and policy support.
But there are several different forms and functions of DR, and these differences affect their role in wholesale markets and their attributes from reliability and emissions perspectives. DR resources may reduce annual consumption of energy, or be ‘‘on call’’ to suddenly reduce demand on the system for a finite period of time. ‘‘On call’’ DR can be designed to respond in real-time to energy market prices (sometimes referred to as ‘‘price-responsive demand’’ or ‘‘economic load response’’), or only episodically as load curtailment (sometimes referred to as ‘‘emergency load
response’’ or ‘‘reliability-based DR’’). The technologies or approaches that back DR resources are similarly varied. DR can involve technologies to moderate or curtail actual customer loads (e.g., air conditioner or water heater control devices, that sometimes allow for rapid response to dispatch signals), or can be based on the availability of backup, supplemental, or emergency generation that is on site. DR backed by on-site generation (often powered by diesel fuel, referred to as ‘‘generation-backed’’ or ‘‘dieselbacked’’ DR) allows continued consumption and uninterrupted site operations, but reduces load drawn from the bulk power system. rice-responsive DR bids into energy markets as a resource, responds to economic signals associated with real-time energy prices, and generally does not participate in capacity markets. Emergency load response serves primarily as a capacity market resource, and is dispatched only in temporally limited conditions. That is, RTOs are limited in the frequency and duration with which they can call upon emergency DR resources.2 As DR grows to be a major presence in electricity markets, so too does the impact of its presence on system operations, planning, cost, and emissions. In particular, most regions that provide for DR participation in capacity markets are struggling with how to ensure comparable treatment between
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demand and supply resources,3 and several groups have recently questioned the impact of DR resources on air quality, particularly with respect to DR resources that are backed by small, stationary (mostly dieselfueled) engines.4 he benefits of existing DR resources that respond to energy price signals or produce continuous reductions in consumption are significant, and are tied to the benefits of responding to price and reducing energy. In addition, DR resources that respond to price signals to reduce load through automatic controls on consuming devices (e.g., air conditioners, water heaters) lead to load reductions, and a reduction in power system generation at the time of their activation. However, it is more challenging to decipher the impacts of DR resources that (1) are selected in organized, forward capacity markets, (2) have limits on their availability, and (3) when called on require turning on diesel or other generation sources onsite. In this article, we focus on this subset of DR resources, and on the long-term implications of the forward selection of such resources in capacity markets in place of generation alternatives. That is, when a DR resource backed by on-site generation is selected as a capacity resource, how will it affect system operations, price, and emissions in those future years compared to the alternatives? We review in particular two aspects of capacity market integration of
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generation-backed DR that have relevance to renewable energy goals and environmental policy: (1) its potential contribution to managing the rapid integration of variable renewable resources; and (2) its impact on system dispatch emission outcomes relative to the selection of alternative supplyside resources.5 In short, from the perspective of forward capacity market selections and system reliability,
perspective of environmental policy, the selection of generationbacked DR instead of competing supply-side resources (which in most advanced organized wholesale market regions is dominated by natural gas combined-cycle (NGCC) and wind facilities in RTO interconnection queues) leads to significantly higher levels of system emissions on an annual basis, across all pollutants.6
The distinction between DR and supply-side capacity resources may lead to important differences in market valuation.
II. DR and Capacity Resource Attributes
generation-backed DR provides an important contribution; but its contribution is no more – and in some senses less – than the impact on reliability of supply-side resources against which it competes in capacity markets. As regions seek to differentiate among competing capacity resources with respect to operational/performance attributes – a task driven in part by the need to manage the growing integration of variable renewable resources – the distinction between DR and supply-side capacity resources may lead to important differences in market valuation. From the
Differences in power system needs – and thus differences in the value of capacity resource operating attributes – are illustrated conceptually in Figure 1. From the broad perspective of power system reliability – including both resource adequacy and system security – different resources provide a wide range of values. For example, a variable resource that may not be online or operable at the time of a system contingency cannot provide the same value for contingency response as a thermal generating resource with the same capacity rating (provided it is not on planned or forced outage). Similarly, a unit that takes many hours to start and come to full output or that can change output schedules only very slowly cannot be as effective in managing hour-to-hour and minute-tominute variability in net load (e.g., due to changes in renewable
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Fig. 1: Representative Load Shape and Resource Needs
output) as a unit that can be online in 10 minutes, or ramp to full capacity in an hour. Whereas some resources are capable of contributing under all load conditions represented in Figure 1, others simply cannot be relied on for heavy cycling or peaking contributions. et in wholesale capacity markets, a MW is a MW.7 This means a poor-performing, slow-ramping resource with a long start time and excessive minimum-run and minimumdown times has the same capacity value (and typically receives the same capacity payment) as an efficient, fast-start, fast-ramp, flexible resource. To date, accounting for – and placing a value on – generating resource attributes beyond simple MW of capacity has been accomplished either administratively, or
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imperfectly through reserve and ancillary service markets. Such supplemental payments generally do not contribute enough to revenue expectations – relative to energy and capacity markets – to be a significant factor in new capacity investment decisionmaking. DR’s rapid emergence as a competitive capacity resource has brought this into stark relief, as the presence of DR as a resource in capacity markets has grown rapidly. For example, as noted above, DR in organized power markets has grown to over 31,000 MW, representing 7.0 percent of peak demand in 2010, in the RTOs where DR is a major contributing resource.8 Most generation-backed DR capacity resources may by definition only be called on a limited number of times per year, and a limited
number of hours per event. This is not comparable to the requirement on generation capacity resources, which generally are obligated to bid hourly into energy markets, or be available (other than when in outage) and respond to system operator dispatch signals. To date, however, DR resources generally have received comparable capacity market compensation as supply resources in wholesale markets.9 he differences between DR and supply resources – and among different types of each – are highlighted by the emerging challenges associated with the integration and expansion of variable renewable resources, an expansion expected to accelerate in many regions in the coming years. The integration of these variable energy resources (VERs)
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has two effects that tend to feed off one another: first, growth in variable resources can significantly increase system net load variability, requiring a greater level of flexible resources that can be cycled on and off, and ramp up and down, with far greater frequency and speed than currently required. However, as VERs grow and are dispatched whenever available (given the low variable costs associated with VER operations), they reduce output from – and energy market revenues to – the very cycling resources needed to manage the impacts of VERs on system operations. ystem operators are considering ways to address
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this challenge through the evolution of capacity markets, to include greater resolution (and potentially price separation) for capacity resources with different attributes.10 Table 1 summarizes for potential capacity resource technologies the attributes that are important for preserving power system reliability as the integration of VERs grows. The performance characteristics needed to meet load requirements and manage the potential increase in net load variability include the following: On-Peak Capacity Value – the ability of a resource to reliably serve as a capacity resource during periods of peak demand.
Day-Ahead Schedule & Commitment – the availability of a resource to be scheduled in advance throughout the year, either a day in advance or with shorter lead time. 30-Minute Intraday Ramp Rate – the ability of a capacity resource to quickly vary its output through signals issued by the power system operator and/or manual changes by the facility owner in response to dispatch instructions. Fast Start Capability – the ability of a resource to either quickly increase its output (‘‘spinning reserves,’’ provided by units already generating electricity but not at full output), or that can turn on and synchronize to the grid quickly (e.g., within 10 or
Table 1: Resource Characteristics
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30 minutes, or at least within the operating day (‘‘non-spinning reserves’’)). Regulation/Automatic Generation Control (AGC) – the ability of online, synchronized generation capacity to respond to a system operator’s electronic signals to change dispatch levels on a second-by-second basis. DR can be helpful in aiding integration of variable renewable resources given several of its characteristics: Some types of DR can be relatively fast-start resources, and can be timed for peak load activation. DR can be scheduled a day in advance, or in some cases on shorter notice depending on actual variable resource output. Some DR programs are seasonally focused (e.g., airconditioning-based programs), and most are focused for on-peak hours, and thus match well with system peak needs. At the same time, the use of DR as a tool for integrating variable resources poses several challenges: Some types of DR are not particularly flexible, and are relatively new. In addition, the performance of some types of DR is not well resolved. The potential of some types of DR is diminished (or cost is increased) as the frequency of calling on it increases. Further, there is not currently a lot of experience with DR called on multiple times per year. 6
DR ‘‘calls’’ are typically limited in number and duration; this does not match well with the frequency of need to support VERs. DR in significant quantities can require aggregation of many different sources, increasing resource uncertainty. The point here is not to draw a conclusion that DR has no place in
wholesale electricity markets; to the contrary, the rapid and wide growth in DR reflects the depth of its current value and future potential. All resources available to system operators to balance power systems and operate reliably through system peaks and contingencies have value, and should be compensated through capacity market or similar mechanisms. Rather, as the complexity of system operation increases with the integration of variable resources, it will become more important to pursue capacity market designs that properly differentiate among resource types and attributes, and provide efficient incentives to attract resources with valuable
characteristics, develop resources in the right locations, and let resources of limited value retire. As this occurs, the monetary value of some types of DR as a capacity resource is likely to decline relative to competing resource types.
III. Generation-Backed DR and its Impact on Energy Markets and Emissions Forward capacity markets are designed to procure sufficient capacity resources to meet power system needs, in all hours of the year. The total available installed capacity needs to be sufficient to satisfy forecast demand, including consideration of potential resource outages and system contingencies. In this sense, the quantity procured is an ability to operate if called on; it does not determine whether, and how much, a capacity resource will actually be called upon on to generate energy. et it is exactly this dispatch of available capacity resources in the energy market that determines the energy prices and environmental footprint of power system operations. Once the capacity market procures resources, the actual annual energy output of each resource is determined based on relative short-run variable costs and dayto-day, hour-to-hour system conditions. Consequently, the results of capacity market procurements can have a profound effect on system energy pricing and emissions by adding
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one type of resource – with specific variable cost and emission rate characteristics – in place of a competing resource with different cost and emission factors. n some senses, this is particularly true today, given current industry conditions, resource options, market structures, and underlying cost factors. Interconnection queues in organized wholesale markets are largely dominated by wind and natural gas-fired generation development; these – along with DR options – are nearly certain to be the technologies and fuels competing in capacity markets for at least the next several years. Given these conditions, we sought to identify the implications of capacity market decisions on energy market pricing and system emissions. To illustrate the differences, consider the potential impacts on system emissions under two scenarios that differ only in the resources chosen in a region’s forward capacity market. In one scenario is an aggregation of DR that is backed by on-site, behindthe-meter generation; and in the second scenario, in the absence of DR, is a new NGCC plant (or multiple plants) of equal capacity value as the aggregated DR resource. On peak, when needed the most, each resource would contribute to meeting load and preserving power system reliability. In the forward capacity market construct, where new resources are being compared to one another, one or the other is chosen to meet the identified
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future-year capacity need. The resulting forward market commitment allows the successful resource to move forward with development and operation, while the competing (and losing) resource will not. However, the similarity and equivalence ends with selection in the forward capacity market. The impact of the resource selection
forms of generation.11 These emissions impacts are small on an annual basis when compared to larger units that run more frequently, but should not be discounted completely, since they often operate at times of system summer peak, in densely populated locations, when generation needs are their greatest and air quality is already poor.12 he NGCC plant, on the other hand, would also be called upon to operate in the same hours as the DR, but additionally would operate at various levels of output for a significant percentage of the remaining hours of the year. Holding all else equal, these two scenarios lead to very different system emissions. To review this – and in particular to review the potential energy cost and emission impacts of generation-backed DR versus alternative, competing capacity resources – we simulated the dispatch of the PJM Interconnection under different assumptions regarding the level of new DR likely to be backed by generation and selected in capacity markets for future operation, compared to an equivalent amount of new generating capacity.13 Specifically, we modeled dispatch (1) with estimates of DR capacity clearing in PJM’s capacity market, and (2) with various percentages of DR (as a proxy for the portion of DR possibly backed by diesel-fired generation) replaced with resources representative of development interest in the region – namely, NGCC and wind.14
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on energy market prices and emissions depends on how and when each resource would operate throughout the year, once it has been selected in the capacity market. The generation-backed DR resource would be called upon rarely, if at all, depending on system conditions and specific RTO rules regarding the limited number, frequency and duration of ‘‘calls’’ on the DR resource. Specifically, most DR is called upon only during peak conditions and operates in only a few hours each year. However, even during these few hours, the generation resources behind the DR assets (often diesel-fired generators) have extraordinarily high emission rates relative to other
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A. Analytic method. Our analysis simulates the dispatch of the PJM power system over a 10-year period (2016–2025, corresponding to the start year for the most recent PJM Base Residual Auction (BRA)) using the Analysis Group simulated dispatch model (SDM), under several scenarios representing different capacity market outcomes. The purpose of the analysis was to evaluate system dispatch with and without postulated quantities of generation-backed DR, in order to assess the potential emissions impact associated with participation of these resources in capacity markets. DM models the dispatch of generating resources to meet the electrical load requirements in every hour of each year in the modeling period (in this case, the modeling period involves future years during which either the DR or alternative capacity resources would be in operation). It identifies the total MWh of generation from power system assets, the marginal generating unit operating on the system in each hour, the marginal energy market price, and emissions of carbon dioxide (CO2), nitrogen oxides (NOx), sulfur dioxide (SO2), and mercury (Hg). Modeling data and assumptions included in the Base Case are the following: Peak load forecasts for the PJM system: based on actual hourly load profiles in PJM and adjusted for future load expectations as forecasted by PJM.
Existing capacity resources: based on supply curve data for PJM, including costs, heat rates, fuel and technology types, and other information.15 Existing resources assumed in the Base Case include approximately 15,000 MW of DR, consistent with the amount cleared in the most recent BRA. Outages and deratings for generating units are
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based on NERC Generation Availability Data System (GADS) data for PJM, and emissions information is based on Environmental Protection Agency (EPA) Continuous Emissions Monitoring Systems (CEMS) data16 and Hg emissions collected in EPA’s Mercury and Air Toxics Standards rulemaking docket.17 Resource additions and retirements: based on data from SNL Financial, and supplemented by calculating reserve margin thresholds and adding generic capacity units to maintain resource adequacy. Fuel prices: natural gas price forecasts are derived from NYMEX futures contracts for Henry Hub and a historical basis
differential between Henry Hub and the PJM region. Coal and oil forecasts are from the EIA’s Annual Energy Outlook, and reflect delivered prices to electricity producers.18 ith these inputs, dispatch is simulated for the Base Case for the modeling period, and for scenarios that only differ from the Base Case in the assumed level of DR. Specifically, the results presented below are for two scenarios: Scenario 1 removes 50 percent of DR resources and replaces them with generating resources representative of those in PJM’s interconnection queue (which is roughly two-thirds NGCC, and one-third wind (derated)). Scenario 2 replaces 10 percent of DR resources with an equivalent quantity of capacity resources (using the same queue-based resource mix). It is not possible to estimate precisely the portion of DR associated with on-site diesel generators in PJM; consequently, for modeling purposes we chose to bracket the potential impacts of diesel-backed DR by assuming the range of 10 percent to 50 percent of existing DR as a proxy for the portion associated with onsite generation. In effect, we model the dispatch of generationbacked DR as being at the top of the supply curve, since it is by definition only dispatched in rare circumstances. In its place, the scenarios add queue-based resources (NGCC and wind generators) which, by virtue of their low variable costs, would be lower in the supply curve than the
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Minimum hourly load
Peak hourly load
capacity market resources, the system-wide emissions of all pollutants are lower than the Base Case emissions.
Marginal Cost ($/ MWh )
Emergency generationbacked DR resources
Original supply curve
New supply curve with added wind/NGCC capacity
Additional wind/NGCC capacity
Cumulative Capacity (MW)
Fig. 2: Simplified Illustration of Supply Curve
DR resources. A simplified representation of this difference is presented in Figure 2. B. Results. The results, shown in Table 2, are surprising at first glance. Knowing that the generation which backs the DR
would rarely run, one would expect that replacing it with – in part – NGCC capacity would in fact increase emissions. We find the opposite effect: that is, in both scenarios in which potential future DR capacity resources (in the Base Case) are replaced with alternative
Table 2: Total Emissions by Pollutant; Base Case vs. Scenarios, 2016–2025 Emissions Type
Scenario 1
Scenario 2
5.436 billion 5.165 billion
5.436 billion 5.354 billion
CO2 (tons) Base case Scenario Difference SO2 (tons)
272 million
82 million
Base case
10.6 million
10.6 million
Scenario Difference
10.2 million 451,982
10.5 million 135,740
NOx (tons) Base case
5.0 million
5.0 million
Scenario Difference
4.7 million 240,080
4.9 million 78,779
Base case Scenario
36.86 35.30
36.86 36.40
Difference
1.56
0.46
Hg (tons)
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The reduction in emissions is driven primarily by a displacement of energy production at older, less-efficient fossil-fuel resources with the combination of output from new, efficient, and inframarginal natural-gas-fired and windpowered generation. We also modeled the results assuming other levels of replacement of generation-backed DR between 10 and 50 percent, and assuming that the resources selected in place of DR included no wind resources (that is, they were all NGCC). While the results changed quantitatively, they were the same qualitatively – namely, a reduction in emissions across the board.19 Figure 3 presents the changes in generation from existing resource types, revealing how the dispatch of new, efficient resources reduces emissions through the displacement of older, less efficient fossil-fuel resources higher on the supply curve. dditionally, we find that when the replacement resources that would be added (but for the generation-backed DR) are dispatched, the impact is not only a reduction of emissions, but also a reduction in marginal energy prices across the PJM market, since the more efficient and lower-cost NGCC and wind are displacing more expensive generation further up the supply
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Scenario 1 Renewables
Scenario 2
Fossil Fuels
More generation
Less generation
Natural Gas
Oil
Coal
-400
-300
-200
-100
0
100
200
300
400
Difference in Net Generation (millions of MWh) Notes: [1] Values shown represent the difference between scenario case and base case. [2] Renewables include biomass, solar and wind. [3] Only significant changes are shown. Changes in other fuels are either zero (e.g., nuclear, hydro) or small (e.g., other non-renewable).
Fig. 3: Differences in Net Generation by Fuel Type, 2016–2025
curve. These lower prices are paid by all purchasers of power within PJM, meaning another effect of replacing generation-backed DR with alternative capacity is to reduce energy market costs for all consumers. In fact, our analysis reveals that annual energy cost savings range from $0.65 billion to $2.56 billion in 2016, depending on the scenario, and from $1.45 billion to $5.67 billion by 2025, again depending on the scenario. Importantly, these cost data reflect only changes in energy market prices, and should not be interpreted as representing the overall net impact on costs to consumers. DR is selected in capacity markets because, in part, it is less expensive than competing resources on a 10
capacity basis. Whether the net impact on consumers is positive or negative would depend on the direction and magnitude of the price impact in capacity markets of clearing the NGCC and wind resources relative to the DR resources, compared with the energy market pricing impact. The capacity market impact could be large enough to more than offset the energy market savings. We did not evaluate this net price impact in our analysis.
IV. Conclusions Despite their relative newness, demand response resources play an increasingly important role in electricity markets, contributing
to wholesale market efficiency, power system operations, and clear benefits to participating end users. As capacity markets evolve and DR matures, it can and should continue to play a growing role and help improve wholesale market outcomes. In this article, however, we take a critical look at the potential challenges that DR integration faces, particularly those associated with DR resources that are backed by onsite or backup generation. Based on a review of capacity market characteristics and dynamics, we find that while generation-backed DR provides an important contribution, its contribution is no more – and in some senses less – than the impact on reliability of supply-side resources against
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which it competes in capacity markets. Further, given the performance/operating attributes of such resources relative to capacity market alternatives, the value of DR may diminish as regions seek to differentiate among competing capacity resources in light of the need to manage the growing integration of variable renewable resources. We also find, based upon a simulated dispatch analysis of resources that compete to meet forward capacity obligations, that differences between DR and supply-side capacity resources may lead to important differences in energy prices and emissions of several key pollutants. From the perspective of environmental policy, the selection of generation-backed DR instead of competing supply-side resources (which is dominated by NGCC and wind facilities in RTO interconnection queues) leads to significantly higher levels of system emissions on an annual basis, across all pollutants.& Endnotes: 1. Assessment of Demand Response & Advanced Metering, FERC Staff Report, Nov. 2011, at 9–10. 2. For example, in PJM, beginning with the auction for capacity in the 2014/2015 delivery year, DR must be categorized as one of the following: Limited Demand Resources, Extended Summer Demand Resources, or Annual Demand Resources. Limited Demand Resources must agree to up to 10 interruptions for at least 6 hours between June and September during any weekday between the hours of 12 pm and 8 pm. Extended Summer Demand Resources must agree to unlimited interruptions for at least 10
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hours between June and October between the hours of 10 am to 10 pm. Annual Demand Resource must agree to unlimited interruptions for at most least 10 hours between October and April between the hours of 10 am 10 pm in months May-October and between the hours of 6 am-9 pm for November to April. See Monitoring Analytics, LLC, 2011 State of the Market Report for PJM, Vol. 2: Detailed Analysis, Mar. 15, 2012, at 99. 3. See, for example, ISO New England, ISO Discussion Paper – Aligning Markets and Planning, June 13, 2012, at http://www.iso-ne.com/ committees/comm_wkgrps/ strategic_planning_discussion/ materials/mra_discussion_paper_ 06132012_vtransmit.pdf. 4. See, for example, California Public Utilities Commission, Order Instituting Rulemaking to Oversee the Resource Adequacy Program, Consider Program Refinements, and Establish Annual Local Procurement Obligations, Rulemaking 09-10-032, Oct. 10, 2011, at 26. 5. The analysis and results described in this article – in particular the modeling of relative environmental impacts – derive from analysis originally conducted on behalf of Calpine Corporation for submittal to the U.S. Environmental Protection Agency in connection with Docket No. EPA-HQ-OAR-2008-0708. See Paul J. Hibbard, Reliability and Emission Impacts of Stationary Engine-Backed Demand Response in Regional Power Markets, Aug. 2012 (‘‘Hibbard report’’) (at: http://www.analysisgroup.com/ demand_response_report.aspx). 6. In this article we focus on those regions that have organized wholesale markets with forward capacity auctions, since these are the regions where DR is emerging as a significant capacity resource. While these regions’ new resource development interest (as represented in new generation interconnection queues) is dominated by wind and NGCC resources, other regions may have greater contributions from peaking and other resource types. 7. Notable but limited exceptions to this rule include unit location where
capacity markets have a locational element, and the specific capacity derating of certain resource types (such as wind and solar). 8. FERC, supra note 1, at 9–10. The RTOs counted include ISO-NE, NYISO, PJM, MISO, ERCOT, CAISO, and SPP. 9. A further distinction that is relevant to the generation profile of DR is whether the DR is based on technologies to moderate or curtail actual customer loads or based on the availability of backup, supplemental, or emergency generation that is on site. In the latter case, the system load reduction is not tied to absolute reductions in energy use; instead it relies on the use of behind-the-meter generation that displaces electricity that otherwise would be provided by the grid. 10. See, e.g., ISO-NE, Using the Forward Capacity Market to Meet Strategic Challenges, May 2012, at http:// www.iso-ne.com/committees/ comm_wkgrps/strategic_ planning_discussion/materials/ fcm_whitepaper_final_may_11_ 2012.pdf. 11. See, e.g., Northeast States for Coordinated Air Use Management (NESCAUM), Air Quality, Electricity, and Back-up Stationary Diesel Engines in the Northeast, Aug. 1, 2012. 12. NESCAUM. 13. We chose PJM because of the rapidly expanding contribution from DR in that region. 14. For a more detailed description of model approach and results, see Hibbard report. 15. Supply curve data are from SNL Financial. 16. EPA CEMS data used are those reported in SNL Financial. 17. See http://www.epa.gov/ airquality/powerplanttoxics/ actions.html for more details. 18. More detail on SDM structure, data and assumptions may be found in the Hibbard report. 19. See Hibbard report for details on the results of the additional scenarios.
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Paul J. Hibbard is a Vice President at Analysis Group’s Boston office, where he applies technical, economic, and regulatory expertise to financial, policy, and strategic issues in energy industries. Mr. Hibbard has over a decade of experience in state environmental and economic regulatory agencies, most recently as Chairman of the Massachusetts Department of Public Utilities. In his dozen-year consulting career before and after the DPU, he has continuously focused on the intersection of economic and environmental policy goals in regulated industries and wholesale energy markets. As a policymaker and energy expert, Hibbard has testified extensively before legislative and regulatory agencies. Andrea M. Okie is a Manager at Analysis Group, where she specializes in energy economics, strategy, and policy in electric and natural gas industries. Ms Okie has consulted with companies, government agencies, non-profits, and other organizations on energy markets, economic and environmental regulation and strategy, and energy facility development and siting. Ms. Okie has managed projects developing business and strategic plans for regulated utilities and private energy industry companies, and assessments of electricity market design and natural gas futures price manipulation. Ms. Okie holds a Masters degree in Public Policy from the University of California at Berkeley. Pavel G. Darling is an Associate at Analysis Group, where he focuses on technical and economic analysis of key electric and natural gas industry challenges. Mr. Darling is an expert in modeling of electric power systems, policy designs, and economic impacts, and has applied modeling techniques to investigate asset development, utility merger impacts, environmental policy benefits and costs, and dispatch implications of renewable resource integration. He holds an MBA from MIT’s Sloan School of Management.
November 2012, Vol. 25, Issue 9
Demand Response in Capacity Markets: Reliability, Dispatch and Emission Outcomes Demand response plays a vital and growing role in the reliability, economics, and environmental footprint of the power industry. As the opportunity for DR integration in wholesale markets grows, so does the diversity of DR types, and the influence of DR in wholesale market outcomes. A review of DR’s roles in evolving capacity markets and the impact on power system dispatch and emissions of generation-backed DR finds some unexpected results. Paul J. Hibbard, Andrea M. Okie and Pavel G. Darling
I. Introduction Demand response (DR) plays a vital and growing role in the reliability, economics, and environmental footprint of the power industry. It is vital because it opens the door to truly effective real-time price-responsive demand in electricity markets, something that has eluded the industry (to any meaningful extent) to this point.
In an industry that requires the instantaneous balancing of supply and demand with limited economic storage capability, and that faces relatively high price volatility in underlying fuel markets, the absence of truly effective price-responsive demand contributes to several key challenges – such as the purchase of greater quantities of capacity and reserves than would otherwise be needed, and the
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prevalence of policy measures to constrain price spikes during times of scarcity. Consequently, it is difficult to overstate the potential value of wide scale and economic integration of demand response, from the perspectives of economics and energy policy. his combination of technical/economic immaturity on the one hand, and potential value on the other, has appropriately spurred the implementation of financial and policy support to accelerate the development and commercialization of demand response. Both federal and state governments and regulatory agencies have acted through a wide array of financial and policy mechanisms, including research, development, and commercialization grants, loan guarantees, and tax incentives; state ratepayer-funded support of small-scale and distributed technologies and rate policies promoting real-time pricing; exceptions to emission control requirements for behind-themeter generation that supports DR resources; and wholesale market design policies that provide favorable conditions for the integration of DR. While the past several years have seen almost continuous change in how demand resources participate in wholesale markets, it is hard to imagine rapid growth in these sectors without government and regulatory support. And grow it has. For example, the Federal Energy Regulatory Commission reported that
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demand response in organized power markets increased by more than 16 percent between 2009 and 2010 alone, increasing from 27,189 MW to 31,702 MW, accounting for between 2.3 percent (ERCOT) and 10.5 percent (PJM) of peak demand in regional transmission organizations (RTO).1 This is a remarkable rate of growth, and one that is expected to continue in the coming years.
The combination of technical/economic immaturity on the one hand, and potential value on the other, has appropriately spurred the implementation of financial and policy support.
But there are several different forms and functions of DR, and these differences affect their role in wholesale markets and their attributes from reliability and emissions perspectives. DR resources may reduce annual consumption of energy, or be ‘‘on call’’ to suddenly reduce demand on the system for a finite period of time. ‘‘On call’’ DR can be designed to respond in real-time to energy market prices (sometimes referred to as ‘‘price-responsive demand’’ or ‘‘economic load response’’), or only episodically as load curtailment (sometimes referred to as ‘‘emergency load
response’’ or ‘‘reliability-based DR’’). The technologies or approaches that back DR resources are similarly varied. DR can involve technologies to moderate or curtail actual customer loads (e.g., air conditioner or water heater control devices, that sometimes allow for rapid response to dispatch signals), or can be based on the availability of backup, supplemental, or emergency generation that is on site. DR backed by on-site generation (often powered by diesel fuel, referred to as ‘‘generation-backed’’ or ‘‘dieselbacked’’ DR) allows continued consumption and uninterrupted site operations, but reduces load drawn from the bulk power system. rice-responsive DR bids into energy markets as a resource, responds to economic signals associated with real-time energy prices, and generally does not participate in capacity markets. Emergency load response serves primarily as a capacity market resource, and is dispatched only in temporally limited conditions. That is, RTOs are limited in the frequency and duration with which they can call upon emergency DR resources.2 As DR grows to be a major presence in electricity markets, so too does the impact of its presence on system operations, planning, cost, and emissions. In particular, most regions that provide for DR participation in capacity markets are struggling with how to ensure comparable treatment between
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demand and supply resources,3 and several groups have recently questioned the impact of DR resources on air quality, particularly with respect to DR resources that are backed by small, stationary (mostly dieselfueled) engines.4 he benefits of existing DR resources that respond to energy price signals or produce continuous reductions in consumption are significant, and are tied to the benefits of responding to price and reducing energy. In addition, DR resources that respond to price signals to reduce load through automatic controls on consuming devices (e.g., air conditioners, water heaters) lead to load reductions, and a reduction in power system generation at the time of their activation. However, it is more challenging to decipher the impacts of DR resources that (1) are selected in organized, forward capacity markets, (2) have limits on their availability, and (3) when called on require turning on diesel or other generation sources onsite. In this article, we focus on this subset of DR resources, and on the long-term implications of the forward selection of such resources in capacity markets in place of generation alternatives. That is, when a DR resource backed by on-site generation is selected as a capacity resource, how will it affect system operations, price, and emissions in those future years compared to the alternatives? We review in particular two aspects of capacity market integration of
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generation-backed DR that have relevance to renewable energy goals and environmental policy: (1) its potential contribution to managing the rapid integration of variable renewable resources; and (2) its impact on system dispatch emission outcomes relative to the selection of alternative supplyside resources.5 In short, from the perspective of forward capacity market selections and system reliability,
perspective of environmental policy, the selection of generationbacked DR instead of competing supply-side resources (which in most advanced organized wholesale market regions is dominated by natural gas combined-cycle (NGCC) and wind facilities in RTO interconnection queues) leads to significantly higher levels of system emissions on an annual basis, across all pollutants.6
The distinction between DR and supply-side capacity resources may lead to important differences in market valuation.
II. DR and Capacity Resource Attributes
generation-backed DR provides an important contribution; but its contribution is no more – and in some senses less – than the impact on reliability of supply-side resources against which it competes in capacity markets. As regions seek to differentiate among competing capacity resources with respect to operational/performance attributes – a task driven in part by the need to manage the growing integration of variable renewable resources – the distinction between DR and supply-side capacity resources may lead to important differences in market valuation. From the
Differences in power system needs – and thus differences in the value of capacity resource operating attributes – are illustrated conceptually in Figure 1. From the broad perspective of power system reliability – including both resource adequacy and system security – different resources provide a wide range of values. For example, a variable resource that may not be online or operable at the time of a system contingency cannot provide the same value for contingency response as a thermal generating resource with the same capacity rating (provided it is not on planned or forced outage). Similarly, a unit that takes many hours to start and come to full output or that can change output schedules only very slowly cannot be as effective in managing hour-to-hour and minute-tominute variability in net load (e.g., due to changes in renewable
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Fig. 1: Representative Load Shape and Resource Needs
output) as a unit that can be online in 10 minutes, or ramp to full capacity in an hour. Whereas some resources are capable of contributing under all load conditions represented in Figure 1, others simply cannot be relied on for heavy cycling or peaking contributions. et in wholesale capacity markets, a MW is a MW.7 This means a poor-performing, slow-ramping resource with a long start time and excessive minimum-run and minimumdown times has the same capacity value (and typically receives the same capacity payment) as an efficient, fast-start, fast-ramp, flexible resource. To date, accounting for – and placing a value on – generating resource attributes beyond simple MW of capacity has been accomplished either administratively, or
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imperfectly through reserve and ancillary service markets. Such supplemental payments generally do not contribute enough to revenue expectations – relative to energy and capacity markets – to be a significant factor in new capacity investment decisionmaking. DR’s rapid emergence as a competitive capacity resource has brought this into stark relief, as the presence of DR as a resource in capacity markets has grown rapidly. For example, as noted above, DR in organized power markets has grown to over 31,000 MW, representing 7.0 percent of peak demand in 2010, in the RTOs where DR is a major contributing resource.8 Most generation-backed DR capacity resources may by definition only be called on a limited number of times per year, and a limited
number of hours per event. This is not comparable to the requirement on generation capacity resources, which generally are obligated to bid hourly into energy markets, or be available (other than when in outage) and respond to system operator dispatch signals. To date, however, DR resources generally have received comparable capacity market compensation as supply resources in wholesale markets.9 he differences between DR and supply resources – and among different types of each – are highlighted by the emerging challenges associated with the integration and expansion of variable renewable resources, an expansion expected to accelerate in many regions in the coming years. The integration of these variable energy resources (VERs)
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has two effects that tend to feed off one another: first, growth in variable resources can significantly increase system net load variability, requiring a greater level of flexible resources that can be cycled on and off, and ramp up and down, with far greater frequency and speed than currently required. However, as VERs grow and are dispatched whenever available (given the low variable costs associated with VER operations), they reduce output from – and energy market revenues to – the very cycling resources needed to manage the impacts of VERs on system operations. ystem operators are considering ways to address
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this challenge through the evolution of capacity markets, to include greater resolution (and potentially price separation) for capacity resources with different attributes.10 Table 1 summarizes for potential capacity resource technologies the attributes that are important for preserving power system reliability as the integration of VERs grows. The performance characteristics needed to meet load requirements and manage the potential increase in net load variability include the following: On-Peak Capacity Value – the ability of a resource to reliably serve as a capacity resource during periods of peak demand.
Day-Ahead Schedule & Commitment – the availability of a resource to be scheduled in advance throughout the year, either a day in advance or with shorter lead time. 30-Minute Intraday Ramp Rate – the ability of a capacity resource to quickly vary its output through signals issued by the power system operator and/or manual changes by the facility owner in response to dispatch instructions. Fast Start Capability – the ability of a resource to either quickly increase its output (‘‘spinning reserves,’’ provided by units already generating electricity but not at full output), or that can turn on and synchronize to the grid quickly (e.g., within 10 or
Table 1: Resource Characteristics
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30 minutes, or at least within the operating day (‘‘non-spinning reserves’’)). Regulation/Automatic Generation Control (AGC) – the ability of online, synchronized generation capacity to respond to a system operator’s electronic signals to change dispatch levels on a second-by-second basis. DR can be helpful in aiding integration of variable renewable resources given several of its characteristics: Some types of DR can be relatively fast-start resources, and can be timed for peak load activation. DR can be scheduled a day in advance, or in some cases on shorter notice depending on actual variable resource output. Some DR programs are seasonally focused (e.g., airconditioning-based programs), and most are focused for on-peak hours, and thus match well with system peak needs. At the same time, the use of DR as a tool for integrating variable resources poses several challenges: Some types of DR are not particularly flexible, and are relatively new. In addition, the performance of some types of DR is not well resolved. The potential of some types of DR is diminished (or cost is increased) as the frequency of calling on it increases. Further, there is not currently a lot of experience with DR called on multiple times per year. 6
DR ‘‘calls’’ are typically limited in number and duration; this does not match well with the frequency of need to support VERs. DR in significant quantities can require aggregation of many different sources, increasing resource uncertainty. The point here is not to draw a conclusion that DR has no place in
wholesale electricity markets; to the contrary, the rapid and wide growth in DR reflects the depth of its current value and future potential. All resources available to system operators to balance power systems and operate reliably through system peaks and contingencies have value, and should be compensated through capacity market or similar mechanisms. Rather, as the complexity of system operation increases with the integration of variable resources, it will become more important to pursue capacity market designs that properly differentiate among resource types and attributes, and provide efficient incentives to attract resources with valuable
characteristics, develop resources in the right locations, and let resources of limited value retire. As this occurs, the monetary value of some types of DR as a capacity resource is likely to decline relative to competing resource types.
III. Generation-Backed DR and its Impact on Energy Markets and Emissions Forward capacity markets are designed to procure sufficient capacity resources to meet power system needs, in all hours of the year. The total available installed capacity needs to be sufficient to satisfy forecast demand, including consideration of potential resource outages and system contingencies. In this sense, the quantity procured is an ability to operate if called on; it does not determine whether, and how much, a capacity resource will actually be called upon on to generate energy. et it is exactly this dispatch of available capacity resources in the energy market that determines the energy prices and environmental footprint of power system operations. Once the capacity market procures resources, the actual annual energy output of each resource is determined based on relative short-run variable costs and dayto-day, hour-to-hour system conditions. Consequently, the results of capacity market procurements can have a profound effect on system energy pricing and emissions by adding
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one type of resource – with specific variable cost and emission rate characteristics – in place of a competing resource with different cost and emission factors. n some senses, this is particularly true today, given current industry conditions, resource options, market structures, and underlying cost factors. Interconnection queues in organized wholesale markets are largely dominated by wind and natural gas-fired generation development; these – along with DR options – are nearly certain to be the technologies and fuels competing in capacity markets for at least the next several years. Given these conditions, we sought to identify the implications of capacity market decisions on energy market pricing and system emissions. To illustrate the differences, consider the potential impacts on system emissions under two scenarios that differ only in the resources chosen in a region’s forward capacity market. In one scenario is an aggregation of DR that is backed by on-site, behindthe-meter generation; and in the second scenario, in the absence of DR, is a new NGCC plant (or multiple plants) of equal capacity value as the aggregated DR resource. On peak, when needed the most, each resource would contribute to meeting load and preserving power system reliability. In the forward capacity market construct, where new resources are being compared to one another, one or the other is chosen to meet the identified
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future-year capacity need. The resulting forward market commitment allows the successful resource to move forward with development and operation, while the competing (and losing) resource will not. However, the similarity and equivalence ends with selection in the forward capacity market. The impact of the resource selection
forms of generation.11 These emissions impacts are small on an annual basis when compared to larger units that run more frequently, but should not be discounted completely, since they often operate at times of system summer peak, in densely populated locations, when generation needs are their greatest and air quality is already poor.12 he NGCC plant, on the other hand, would also be called upon to operate in the same hours as the DR, but additionally would operate at various levels of output for a significant percentage of the remaining hours of the year. Holding all else equal, these two scenarios lead to very different system emissions. To review this – and in particular to review the potential energy cost and emission impacts of generation-backed DR versus alternative, competing capacity resources – we simulated the dispatch of the PJM Interconnection under different assumptions regarding the level of new DR likely to be backed by generation and selected in capacity markets for future operation, compared to an equivalent amount of new generating capacity.13 Specifically, we modeled dispatch (1) with estimates of DR capacity clearing in PJM’s capacity market, and (2) with various percentages of DR (as a proxy for the portion of DR possibly backed by diesel-fired generation) replaced with resources representative of development interest in the region – namely, NGCC and wind.14
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on energy market prices and emissions depends on how and when each resource would operate throughout the year, once it has been selected in the capacity market. The generation-backed DR resource would be called upon rarely, if at all, depending on system conditions and specific RTO rules regarding the limited number, frequency and duration of ‘‘calls’’ on the DR resource. Specifically, most DR is called upon only during peak conditions and operates in only a few hours each year. However, even during these few hours, the generation resources behind the DR assets (often diesel-fired generators) have extraordinarily high emission rates relative to other
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A. Analytic method. Our analysis simulates the dispatch of the PJM power system over a 10-year period (2016–2025, corresponding to the start year for the most recent PJM Base Residual Auction (BRA)) using the Analysis Group simulated dispatch model (SDM), under several scenarios representing different capacity market outcomes. The purpose of the analysis was to evaluate system dispatch with and without postulated quantities of generation-backed DR, in order to assess the potential emissions impact associated with participation of these resources in capacity markets. DM models the dispatch of generating resources to meet the electrical load requirements in every hour of each year in the modeling period (in this case, the modeling period involves future years during which either the DR or alternative capacity resources would be in operation). It identifies the total MWh of generation from power system assets, the marginal generating unit operating on the system in each hour, the marginal energy market price, and emissions of carbon dioxide (CO2), nitrogen oxides (NOx), sulfur dioxide (SO2), and mercury (Hg). Modeling data and assumptions included in the Base Case are the following: Peak load forecasts for the PJM system: based on actual hourly load profiles in PJM and adjusted for future load expectations as forecasted by PJM.
Existing capacity resources: based on supply curve data for PJM, including costs, heat rates, fuel and technology types, and other information.15 Existing resources assumed in the Base Case include approximately 15,000 MW of DR, consistent with the amount cleared in the most recent BRA. Outages and deratings for generating units are
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based on NERC Generation Availability Data System (GADS) data for PJM, and emissions information is based on Environmental Protection Agency (EPA) Continuous Emissions Monitoring Systems (CEMS) data16 and Hg emissions collected in EPA’s Mercury and Air Toxics Standards rulemaking docket.17 Resource additions and retirements: based on data from SNL Financial, and supplemented by calculating reserve margin thresholds and adding generic capacity units to maintain resource adequacy. Fuel prices: natural gas price forecasts are derived from NYMEX futures contracts for Henry Hub and a historical basis
differential between Henry Hub and the PJM region. Coal and oil forecasts are from the EIA’s Annual Energy Outlook, and reflect delivered prices to electricity producers.18 ith these inputs, dispatch is simulated for the Base Case for the modeling period, and for scenarios that only differ from the Base Case in the assumed level of DR. Specifically, the results presented below are for two scenarios: Scenario 1 removes 50 percent of DR resources and replaces them with generating resources representative of those in PJM’s interconnection queue (which is roughly two-thirds NGCC, and one-third wind (derated)). Scenario 2 replaces 10 percent of DR resources with an equivalent quantity of capacity resources (using the same queue-based resource mix). It is not possible to estimate precisely the portion of DR associated with on-site diesel generators in PJM; consequently, for modeling purposes we chose to bracket the potential impacts of diesel-backed DR by assuming the range of 10 percent to 50 percent of existing DR as a proxy for the portion associated with onsite generation. In effect, we model the dispatch of generationbacked DR as being at the top of the supply curve, since it is by definition only dispatched in rare circumstances. In its place, the scenarios add queue-based resources (NGCC and wind generators) which, by virtue of their low variable costs, would be lower in the supply curve than the
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Minimum hourly load
Peak hourly load
capacity market resources, the system-wide emissions of all pollutants are lower than the Base Case emissions.
Marginal Cost ($/ MWh )
Emergency generationbacked DR resources
Original supply curve
New supply curve with added wind/NGCC capacity
Additional wind/NGCC capacity
Cumulative Capacity (MW)
Fig. 2: Simplified Illustration of Supply Curve
DR resources. A simplified representation of this difference is presented in Figure 2. B. Results. The results, shown in Table 2, are surprising at first glance. Knowing that the generation which backs the DR
would rarely run, one would expect that replacing it with – in part – NGCC capacity would in fact increase emissions. We find the opposite effect: that is, in both scenarios in which potential future DR capacity resources (in the Base Case) are replaced with alternative
Table 2: Total Emissions by Pollutant; Base Case vs. Scenarios, 2016–2025 Emissions Type
Scenario 1
Scenario 2
5.436 billion 5.165 billion
5.436 billion 5.354 billion
CO2 (tons) Base case Scenario Difference SO2 (tons)
272 million
82 million
Base case
10.6 million
10.6 million
Scenario Difference
10.2 million 451,982
10.5 million 135,740
NOx (tons) Base case
5.0 million
5.0 million
Scenario Difference
4.7 million 240,080
4.9 million 78,779
Base case Scenario
36.86 35.30
36.86 36.40
Difference
1.56
0.46
Hg (tons)
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The reduction in emissions is driven primarily by a displacement of energy production at older, less-efficient fossil-fuel resources with the combination of output from new, efficient, and inframarginal natural-gas-fired and windpowered generation. We also modeled the results assuming other levels of replacement of generation-backed DR between 10 and 50 percent, and assuming that the resources selected in place of DR included no wind resources (that is, they were all NGCC). While the results changed quantitatively, they were the same qualitatively – namely, a reduction in emissions across the board.19 Figure 3 presents the changes in generation from existing resource types, revealing how the dispatch of new, efficient resources reduces emissions through the displacement of older, less efficient fossil-fuel resources higher on the supply curve. dditionally, we find that when the replacement resources that would be added (but for the generation-backed DR) are dispatched, the impact is not only a reduction of emissions, but also a reduction in marginal energy prices across the PJM market, since the more efficient and lower-cost NGCC and wind are displacing more expensive generation further up the supply
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Scenario 1 Renewables
Scenario 2
Fossil Fuels
More generation
Less generation
Natural Gas
Oil
Coal
-400
-300
-200
-100
0
100
200
300
400
Difference in Net Generation (millions of MWh) Notes: [1] Values shown represent the difference between scenario case and base case. [2] Renewables include biomass, solar and wind. [3] Only significant changes are shown. Changes in other fuels are either zero (e.g., nuclear, hydro) or small (e.g., other non-renewable).
Fig. 3: Differences in Net Generation by Fuel Type, 2016–2025
curve. These lower prices are paid by all purchasers of power within PJM, meaning another effect of replacing generation-backed DR with alternative capacity is to reduce energy market costs for all consumers. In fact, our analysis reveals that annual energy cost savings range from $0.65 billion to $2.56 billion in 2016, depending on the scenario, and from $1.45 billion to $5.67 billion by 2025, again depending on the scenario. Importantly, these cost data reflect only changes in energy market prices, and should not be interpreted as representing the overall net impact on costs to consumers. DR is selected in capacity markets because, in part, it is less expensive than competing resources on a 10
capacity basis. Whether the net impact on consumers is positive or negative would depend on the direction and magnitude of the price impact in capacity markets of clearing the NGCC and wind resources relative to the DR resources, compared with the energy market pricing impact. The capacity market impact could be large enough to more than offset the energy market savings. We did not evaluate this net price impact in our analysis.
IV. Conclusions Despite their relative newness, demand response resources play an increasingly important role in electricity markets, contributing
to wholesale market efficiency, power system operations, and clear benefits to participating end users. As capacity markets evolve and DR matures, it can and should continue to play a growing role and help improve wholesale market outcomes. In this article, however, we take a critical look at the potential challenges that DR integration faces, particularly those associated with DR resources that are backed by onsite or backup generation. Based on a review of capacity market characteristics and dynamics, we find that while generation-backed DR provides an important contribution, its contribution is no more – and in some senses less – than the impact on reliability of supply-side resources against
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which it competes in capacity markets. Further, given the performance/operating attributes of such resources relative to capacity market alternatives, the value of DR may diminish as regions seek to differentiate among competing capacity resources in light of the need to manage the growing integration of variable renewable resources. We also find, based upon a simulated dispatch analysis of resources that compete to meet forward capacity obligations, that differences between DR and supply-side capacity resources may lead to important differences in energy prices and emissions of several key pollutants. From the perspective of environmental policy, the selection of generation-backed DR instead of competing supply-side resources (which is dominated by NGCC and wind facilities in RTO interconnection queues) leads to significantly higher levels of system emissions on an annual basis, across all pollutants.& Endnotes: 1. Assessment of Demand Response & Advanced Metering, FERC Staff Report, Nov. 2011, at 9–10. 2. For example, in PJM, beginning with the auction for capacity in the 2014/2015 delivery year, DR must be categorized as one of the following: Limited Demand Resources, Extended Summer Demand Resources, or Annual Demand Resources. Limited Demand Resources must agree to up to 10 interruptions for at least 6 hours between June and September during any weekday between the hours of 12 pm and 8 pm. Extended Summer Demand Resources must agree to unlimited interruptions for at least 10
November 2012, Vol. 25, Issue 9
hours between June and October between the hours of 10 am to 10 pm. Annual Demand Resource must agree to unlimited interruptions for at most least 10 hours between October and April between the hours of 10 am 10 pm in months May-October and between the hours of 6 am-9 pm for November to April. See Monitoring Analytics, LLC, 2011 State of the Market Report for PJM, Vol. 2: Detailed Analysis, Mar. 15, 2012, at 99. 3. See, for example, ISO New England, ISO Discussion Paper – Aligning Markets and Planning, June 13, 2012, at http://www.iso-ne.com/ committees/comm_wkgrps/ strategic_planning_discussion/ materials/mra_discussion_paper_ 06132012_vtransmit.pdf. 4. See, for example, California Public Utilities Commission, Order Instituting Rulemaking to Oversee the Resource Adequacy Program, Consider Program Refinements, and Establish Annual Local Procurement Obligations, Rulemaking 09-10-032, Oct. 10, 2011, at 26. 5. The analysis and results described in this article – in particular the modeling of relative environmental impacts – derive from analysis originally conducted on behalf of Calpine Corporation for submittal to the U.S. Environmental Protection Agency in connection with Docket No. EPA-HQ-OAR-2008-0708. See Paul J. Hibbard, Reliability and Emission Impacts of Stationary Engine-Backed Demand Response in Regional Power Markets, Aug. 2012 (‘‘Hibbard report’’) (at: http://www.analysisgroup.com/ demand_response_report.aspx). 6. In this article we focus on those regions that have organized wholesale markets with forward capacity auctions, since these are the regions where DR is emerging as a significant capacity resource. While these regions’ new resource development interest (as represented in new generation interconnection queues) is dominated by wind and NGCC resources, other regions may have greater contributions from peaking and other resource types. 7. Notable but limited exceptions to this rule include unit location where
capacity markets have a locational element, and the specific capacity derating of certain resource types (such as wind and solar). 8. FERC, supra note 1, at 9–10. The RTOs counted include ISO-NE, NYISO, PJM, MISO, ERCOT, CAISO, and SPP. 9. A further distinction that is relevant to the generation profile of DR is whether the DR is based on technologies to moderate or curtail actual customer loads or based on the availability of backup, supplemental, or emergency generation that is on site. In the latter case, the system load reduction is not tied to absolute reductions in energy use; instead it relies on the use of behind-the-meter generation that displaces electricity that otherwise would be provided by the grid. 10. See, e.g., ISO-NE, Using the Forward Capacity Market to Meet Strategic Challenges, May 2012, at http:// www.iso-ne.com/committees/ comm_wkgrps/strategic_ planning_discussion/materials/ fcm_whitepaper_final_may_11_ 2012.pdf. 11. See, e.g., Northeast States for Coordinated Air Use Management (NESCAUM), Air Quality, Electricity, and Back-up Stationary Diesel Engines in the Northeast, Aug. 1, 2012. 12. NESCAUM. 13. We chose PJM because of the rapidly expanding contribution from DR in that region. 14. For a more detailed description of model approach and results, see Hibbard report. 15. Supply curve data are from SNL Financial. 16. EPA CEMS data used are those reported in SNL Financial. 17. See http://www.epa.gov/ airquality/powerplanttoxics/ actions.html for more details. 18. More detail on SDM structure, data and assumptions may be found in the Hibbard report. 19. See Hibbard report for details on the results of the additional scenarios.
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Please cite this article in press as: Hibbard PJ, et al. Demand Response in Capacity Markets: Reliability, Dispatch and Emission Outcomes, Electr. J. (2012), http://dx.doi.org/10.1016/j.tej.2012.10.010
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