Assessing Market Power in Deregulated Electricity Markets
By Subhonmesh Bose, Chenye Wu, Adam Wierman, and Hamed Mohsenian-Rad
Examples of market manipulation in deregulated power systems abound, and so we need to be able to identify market power and prevent its exercise. Market power analysis needs to be put on a firmer foundation, one that connects short-term and long-term perspectives and takes into account both economic fundamentals and the physical characteristics of transmission systems.
Electricity traditionally has been supplied in the United States by regulated utilities, each with a franchise service area in which it has the right to sell and is allowed a mandated level of profit. Since the 1990s, however, electricity markets in many regions have moved to a more deregulated structure, where the prices are set through mechanisms such as bidding.
The intention, as policymakers and regulators have created electricity markets, has been to encourage innovation and competition in technology but also to bring power prices down. Yet in some deregulated and restructured power systems, prices have instead spiked sharply higher. In some notorious cases, market manipulation was found to be at the root of the spikes.
The California electricity crisis that ushered in the new century remains the most notable case in point: It involved frequent blackouts and an 800 percent increase in wholesale prices from April to December 2000. Investigations led by the Federal Energy Regulatory Commission (FERC) revealed that on multiple occasions, though installed generation capacity was significantly greater than total load demand, some energy companies managed to rig markets to create artificial shortages.
Because of that ability on the part of energy companies to manipulate markets to their advantage—because of their market power —California ratepayers ended up spending about $5. 5 billion more for electricity from 1998 to 2000 than they otherwise would have. The practical importance of identifying such market power and preventing its exercise is obvious.
The U.S. Department of Justice defines market power as the ability of a supply firm to profitably alter prices away from competitive levels, as Steven Soft has spelled out in an IEEE-Wiley book. Market power is connected with a form of market dominance, where a supplier has the ability to behave independently of competitors and consumers in a manner that increases its profitability.
In practice, defining market power in electricity markets is challenging and requires more clearly specifying two of the terms in the previous paragraph: “alter prices” and “competitive levels.” Typically, the notion of “altering prices” has a component of both magnitude and duration, such as altering the price of electricity by 15 percent over ten days during a year. As for "competitive levels," it can be hard to distinguish naturally high competitive prices from prices that are the result of market power.
Furthermore, identification of market power requires ensuring that the manipulation was profitable and especially intentional. Verifying these two components can be delicate; determining profitability requires knowledge of the complete portfolio position of a company, and intentional withholding of electricity to generate shortages can be hard to distinguish from real breakdowns that just happen to be profitable.
Further complications arise from the geographic scale in which market power might be exercised. Such dominance can be gained throughout a wholesale power pool, for example, by a power supplier with a large enough generation capacity; or in just one segment of a power pool, say by a power supplier in a region that has limited ability to import less expensive electricity.
So, detecting market power in the electricity market is not easy. If tools and measures to identify and prevent exercise of market power are not designed properly, they may over-compensate (drive prices below competitive levels), which leads to inadequate investment in generation, or under-compensate (allow prices above competitive levels).
The measures used in practice today are mostly ad hoc and derived largely from economic measures for generic (non-electricity) markets. In recent years, however, systematic design of market power measures has begun to emerge based on both long term and short term analysis. Long term approaches most often study the potential for market power, that is to say, they are usually ex-ante. They are useful for tasks such as market design evaluation, merger analysis, operation planning, as well as for identifying “must-run” generators in advance.
Short term approaches, in contrast, study the exploitation of market power, ±that is, they are usually ex-post. They are typically applied close to the spot market and focus on things such as immediately mitigating market misconduct via penalties for withholding generation. While short-term and long-term market power analyses are clearly related, their relationship is not well understood. With regards to market power, this creates a divide between the planning stage and the enforcement stage; careful investigation will be required to bridge this gap.
Given the fractured nature of the literature on market power, there is currently a great need to put market power analysis on a firmer foundation, one that connects short-term and long-term perspectives and takes into account both economic fundamentals and the physical characteristics of transmission systems. The need for such new market power measures will become even more pronounced in the coming years as we move towards a smart grid that includes high penetration of renewable energy, distributed generation, energy storage and increased use of demand-response programs. While offering more flexibility, each of these emerging components of the smart grid paradigm mentioned above are expected to have impact on both long term and short term market power analysis.
As part of a project that is recently funded by the National Science Foundation, researchers at the California Institute of Technology and the University of California at Riverside have started addressing some of the challenges in developing a unified approach to quantifying market power in the future smart grid. Some preliminary results were recently presented in the IEEE PES General Meeting in Vancouver, Canada in July 2013.
Subhonmesh Bose is a Ph.D. candidate in the Department of Electrical Engineering at the California Institute of Technology, where he has been since graduating from the India Institute of Technology, Kanpur. His research interests are in the intersection of engineering and economics, primarily in modeling and analyzing problems in the evolving smart grid and its associated markets.
Chenye Wu, an IEEE member, is a postdoctoral researcher at Carnegie Mellon University, where he works on the design, optimization, distributed control and game-theoretic analysis of smart power systems and electricity market. He received his doctoral degree in computer science from the Institute for Interdisciplinary Information Sciences, Tsinghua University, in 2013, and he has been a visiting scholar at the Chinese University of Hong Kong, Texas Tech University, Missouri University of Science and Technology, Carnegie Mellon University and California Institute of Technology. He was the best paper recipient of IEEE SmartGridComm 2012 and IEEE PES General Meeting 2013.
Adam Wierman, an IEEE member, is a professor in the Department of Computing and Mathematical Sciences at the California Institute of Technology, where he is a founding member of the Rigorous Systems Research Group (RSRG). He received his Ph.D., M.Sc. and B.Sc. in Computer Science from Carnegie Mellon University in 2007, 2004 and 2001. His research interests center around resource allocation and scheduling decisions in computer systems and services, specifically, analytic techniques in stochastic modeling, queueing theory, scheduling theory and game theory, and application of those techniques in areas like energy-efficient computing, data centers, social networks and electricity markets. He has served on the board of directors of ACM Sigmetrics and on the editorial boards of Performance Evaluation, Operations Research, Queueing Systems, and the IEEE Transactions on Cloud Computing.
Hamed Mohsenian-Rad, an IEEE member, is an assistant professor of electrical engineering at the University of California at Riverside. He received his doctoral degree in electrical engineering from the University of British Columbia in Vancouver, Canada in 2008 and his M.Sc. and B.Sc. degrees from Sharif University of Technology and Amir-Kabir University of Technology in Tehran, Iran in 2004 and 2002, respectively. His main research interests are in optimization and game-theoretic analysis of power systems and electricity markets, and he currently serves as editor for the IEEE Transactions on Smart Grid and the IEEE Communications Letters. He has been honored with the National Science Foundation’s CAREER Award 2012, the Best Paper Award from the IEEE International Conference on Smart Grid Communication 2012 and the Best Paper Award from the IEEE Power and Energy Society General Meeting 2013.