Abstract
This paper surveys the different approaches in use today to ensure grid reliability and incentivize new resources. Market challenges are surveyed, as well as empirical findings that suggest that current market approaches do not provide proper incentives. It is argued that the primary problem is that organized capacity markets today do not consider risks and uncertainty over the proper time frame – decades instead of months or years. Because of this, the analyses ignore risks and other factors that are key to making optimal investment decisions. Solutions are proposed based in part on concepts from traditional resource planning.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Capacity represents the amount of power a resource is capable of delivering at a point in time, or over a period of time. Variations in this term are used in the markets to reflect availability, deliverability and other characteristics important in a particular setting.
- 2.
The Electric Reliability Council of Texas (ERCOT), the electricity market covering most of Texas, uses an energy-only market as a means of incentivizing resource investments.
- 3.
Throughout this chapter, the use of the terms optimize, optimum, or optimal follow the general definitions provided by the Cambridge Dictionary and others to mean “best” or “most effective in a particular situation.” In many cases used herein, it will simply mean “least cost.”
- 4.
Cogeneration is a generating system where a single fuel source is used to simultaneously produce two or more forms of energy output – typically electricity and steam.
- 5.
A power flow model is used to simulate the operation of a high-voltage transmission system. Given assumptions for the topology of the transmission system, the complex impedances of all significant transmission elements, estimates of the real and reactive power loads at each node, and the real and reactive power output of each generator, the model estimates real and reactive power flows through each element of the system modeled and estimates voltage at every bus (magnitude and angle).
- 6.
A production costing program uses assumptions for loads and generation cost characteristics to simulate various operating scenarios (e.g., optimum hourly resource commitment and dispatch over the study period) in order to estimate individual resource and total system operating costs over the study period. Longer-term models also incorporate cost assumptions for resource additions, retirements, and repowering.
- 7.
Rate base represents the total value of facilities on which a public utility is permitted to earn a specified rate of return, in accordance with rules set by a regulatory agency.
- 8.
Useful life is the estimated lifespan of a depreciable fixed asset, during which it can be expected to contribute to utility operations.
- 9.
In this case “optimal” does not necessarily mean absolute “least cost” because other strategic considerations are included in the planning process.
- 10.
Variable O&M refers to nonfuel resource costs that vary with resource operation. While the determination of some components of variable O&M is very subjective, some components are easily quantified. Examples include lubricating oil and make-up water for cooling towers – each of which can be significant for small generators. Utilities can directly tie these costs to operating hours or MWh production. For simplicity, they are often reflected entirely in units of $/MWh.
- 11.
As used here, t represents a period of 5 minutes, 15 minutes, or 1 hour – all commonly used in power system analysis.
- 12.
No-load energy costs represent the fuel and variable O&M costs to operate a resource at 0 MW of output.
- 13.
Any amount added to marginal cost will, in theory and in practice, lead to lower consumption and will therefore not maximize social welfare (producers will have surplus energy at a cost that is less than what customers value).
- 14.
Ramsey-Boiteux pricing is a policy concerning what price a monopolist should set, to maximize social welfare, subject to a constraint on profit.
- 15.
In general, real-time pricing refers to the price for energy over a relatively short period of time – typically between 5 minutes and 1 hour. In the organized RTO markets, real-time pricing refers to the LMPs calculated by the market for energy bought and sold at a specific location and for a set period of time (e.g., 5 minutes).
- 16.
“Short-run” in this context refers to the period from the next five minutes through the next few years (i.e., as limited by the time it takes to install additional generating resources).
- 17.
Bilateral markets for all capacity and energy products continue to operate in the southeast and parts of the western United States. Most of the country continues to utilize bilateral markets for capacity – at least for meeting part of the markets’ needs.
- 18.
While the functions of RTOs are similar to those of ISOs, FERC chose to use a new name in Order 2000 for its desired form of transmission organizations in the United States.
- 19.
All organized markets can be structured as an ISO (and most are), but only multistate organized markets can be structured as an RTO.
- 20.
Note that this day-ahead market activity falls into the “intermediate” optimization problem we describe in Section 3.2. However, it covers only a portion of this time period. Balancing Authorities outside of RTOs typically optimize resource commitment over a rolling, seven-day period.
- 21.
For example, in a typical RTO operation, an LMP posted at 5 mins after the top of the hour reflects the price for all energy consumed or produced during the period from 10 minutes after the hour until 15 minutes after the hour.
- 22.
Market monitors are independent entities hired by the RTOs to monitor market operations.
- 23.
This indicates that one or more resources being dispatched are done so for reasons other than economics.
- 24.
What happens under these circumstances is that more expensive generation is brought online but not allowed to set the market LMP. What is worse is that other generators are then required to reduce output so as to maintain the required instantaneous power balance, thus lowering the overall market’s LMP.
- 25.
Since 2002, FPL has added over 15,000 MW of highly efficient, natural gas-fired generation.
- 26.
SPP serves all of the states of Kansas and Oklahoma and portions of New Mexico, Texas, Arkansas, Louisiana, Missouri, Mississippi, and Nebraska.
- 27.
Physical capacity is capacity provided by an actual operating generating resource. Financial capacity only provides a guarantee to make the purchaser of such capacity financially whole for any market losses. It does not ensure the actual delivery of electricity.
- 28.
The Cost of New Entry is an estimate of the cost to build the least-cost resource in each market.
- 29.
Figure 4 is taken from PJM’s 2014 Triennial Review of their “demand curve,” called the Variable Resource Requirements (VRR) curve in the PJM market.
- 30.
The consequence of nonperformance may require that the defaulting party pay for any energy not provided at up to $5,000/MWh.
- 31.
Typically, the only consequence is that if the unavailability is repeated, future capacity payments will be reduced until capacity availability can be demonstrated.
- 32.
As a point of reference, capacity markets in the United Kingdom cover a term of 15 years.
- 33.
Resources are expected to realize margins from the sale of energy and ancillary services and from Scarcity Pricing in some markets. These margins offset the need to otherwise be fully compensated via the capacity markets.
- 34.
During the last decade (2001–2010), over 265,000 MW of generating capacity was installed in the United States for an estimated cost of $199 billion [14].
- 35.
Current reserve margin requirements in place across most of the United States (12% to 20% of projected annual peak load) ensure that generation is available to serve load 99.97% of the time.
- 36.
Operating reserves represent resource capability above firm system demand required to provide for regulation, load forecasting error, equipment forced and scheduled outages, and local area protection.
- 37.
Planning reserves represent installed capacity above the forecasted peak-hour firm system demand for a defined period in the future.
- 38.
Congestion revenues are revenues realized in the energy markets that are associated with occasional or frequent transmission system congestion.
- 39.
The approach described here is similar to that currently in use by SPP, wherein LSEs have specific reserve requirements, but the RTO operates no formal capacity market [39].
- 40.
SPP is excluded, because it is essentially the laissez-faire approach and not a “formal” capacity market per se.
- 41.
One notable exception is that the traditional energy optimization approach used at least a 7-day optimization period and was therefore not limited to just a day-ahead market.
- 42.
For example, co-optimizing transmission use with generation commitment and dispatch.
- 43.
Jurassic Park, 1993
References
Anderson D (1972) Models for determining least-cost investments in electricity supply. Bell J Econ Manag Sci 3(1):267–299
Baumol WJ, Bradford DF (1970) Optimal departures from marginal cost pricing. Am Econ Rev 60(3):265–283
Bohn RE (1981) A theoretical analysis of customer response to rapidly changing electricity prices. MIT Energy Laboratory, Cambridge
Bohn RE (1982) Spot pricing of public utility services. MIT Energy Laboratory, Cambridge
Bohn RE, Caramanis M, Schweppe F (1980) Optimal spot pricing of electricity. MIT Energy Laboratory, Cambridge
Borenstein S (2009) Electricity pricing that reflects its real-time cost. Technical report, NBER reporter: research summary. http://www.nber.org/reporter/2009number1/borenstein.html
Bowring J (2013) Capacity markets in PJM. Technical report, Monitoring analytics
Bradley RL (2011) Edison to Enron: energy markets and political strategies. Wiley, New York
Cho IK, Meyn SP (2010) Efficiency and marginal cost pricing in dynamic competitive markets with friction. Theor Econ 5(2):215–239
Coase RH (1946) The marginal cost controversy. Econometrica 13(51):169–182
Covarrubias AJ (1979) Expansion planning for electric power systems. IAES Bull 21(2/3):55–64
Dupuit AJEJ (1844) De la mesure de l’utilite des travaux publics. Annales des ponts et chaussees 2(8)
Electricité de France (1965) L’etude a long-terme des investissements a l’aide d’un programme non’lineaire: le modele investissements 85. Technical report, Electricité de France
Energy Information Administration (2011) Form EIA-860 annual electric generator report, and form EIA-860M. Technical report, U.S. Energy Information Administration
Feldstein M (1972) Equity and efficiency in public sector pricing: the optimal two-part tariff. Q J Econ 86:175–187
FERC. Guide to Market Oversight: Glossary. https://www.ferc.gov/market-oversight/guide/glossary.asp
FPL (2016) Florida Power & Light Company’s 2016 Ten Year Power Plant Site Plan. Technical report, Florida Power & Light
Geddes RR (1992) Historical perspective on electric utility regulation. CATO Review of Business and Government
Geuss M (2017) $7.5 billion kemper power plant suspends coal gasification. arsTechnica. www.arstechnica.com/business/2017/06/7-5-billion-kemper-power-plant-suspends-coal-gasification/
Hogan WW (2013) Electricity scarcity pricing through operating reserves. Econ Energy Environ Policy 2(2):65–86
Hotelling H (1937) The general welfare in relation to problems of taxation and of railway and utility rates. Econometric Society, Evanston, IL
Hotelling H (1939) The relation of prices to marginal costs in an optimum system. Econometrica 7(2):151–155
Joskow PL (2013) Symposium on ‘capacity markets’. Econ Energy Environ Policy 2(2):v–vi
Keane D (1995) Outage cost estimation guidebook: EPRI Research Project 2878-04 Final Report. Technical report, EPRI
Lerner AP (1944) The economics of control: principles of welfare economics. Macmillan. www.books.google.com/books?id=2kcNAQAAIAAJ
Marshall A (1890) Principals of economics. Macmillan, New York.
Mas-Colell A (1995) Microeconomic theory. Oxford University Press, Oxford
McCallion K (1995) Shoreham and the rise and fall of the nuclear power industry. Praeger. www.books.google.com/books?id=dHvLpbSYMacC
Meade JE (1944) Price and output policy of state enterprise. Econ J 215:321–339
Negrete-Pincetic M (2012) Intelligence by design in an entropic power grid. PhD thesis, University of Illinois at Urbana Champaign, University of Illinois, Urbana, IL. Meyn S, chair, Sauer PW, de Castro L, Dominguez-Garcia AD, Shanbhag VK
Negrete-Pincetic M, Meyn S (2012) Markets for differentiated electric power products in a Smart Grid environment. In: IEEE power and energy society general meeting, pp. 1–7
Nelson JR (ed) (1964) Marginal cost pricing in practice. Prentice-Hall International, Englewood Cliffs, NJ
Petitet M (2016) Effects of risk aversion on investment decisions in electricity generation: what consequences for market design? In: Proceedings of the 13th international conference on the European energy market
Pinchot G (1945) Long struggle for effective federal water power legislation. George Wash Law Rev 14:9
Pope D (2011) Nuclear implosions - the rise and fall of the Washington public power system. Cambridge University Press, Cambridge
Schroder T, Kuckshinrichs W (2015) Value of lost load: an efficient economic indicator for power supply security? A literature review. Front Energy Res 3:55
Schweppe FC, Caramanis MC, Tabors RD, Bohn RE (1988) Spot pricing of electricity. Kluwer Academic, Dordrecht
Spence DB (2017) Naïve electricity markets. In: IMA volume on the control of energy markets and grids. Springer, Berlin
Staff S (2015) Load responsible entity for reserve margin obligation (presentation). Technical report, Southwest Power Pool
Tabors RD, Kirkley JL (1981) Homeostatic control: the utility/customer marketplace for electric power. MIT Energy Laboratory, Cambridge
Treinen R (2004) Locational marginal pricing (LMP): basics of nodel price calculations www.caiso.com/docs/2004/02/13/200402131607358643.pdf. CAISO market operations presentation
Turvey R (1964) Marginal cost pricing in practice. Econometrica 31(124):426–432
Wang G, Negrete-Pincetic M, Kowli A, Shafieepoorfard E, Meyn S, Shanbhag UV (2012) Dynamic competitive equilibria in electricity markets. In: Chakrabortty A, Ilic M (eds) Control and optimization methods for electric smart grids. Springer, Berlin, pp 35–62
Wolak F (2011) Capturing the benefits of California’s energy infrastructure investments. Technical report, Stanford University. https://web.stanford.edu/group/fwolak/cgi-bin/sites/default/files/files/little_hoover_testimony_wolak_sept_2011.pdf. Accessed June 2017
Acknowledgements
This research was supported by the National Science Foundation under grants CPS-1646229 and EPCN-1609131.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this chapter
Cite this chapter
Moye, R.W., Meyn, S.P. (2018). Redesign of US Electricity Capacity Markets. In: Meyn, S., Samad, T., Hiskens, I., Stoustrup, J. (eds) Energy Markets and Responsive Grids. The IMA Volumes in Mathematics and its Applications, vol 162. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7822-9_4
Download citation
DOI: https://doi.org/10.1007/978-1-4939-7822-9_4
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-7821-2
Online ISBN: 978-1-4939-7822-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)