Abstract
We use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices. The research contributions of this paper are both in the areas of market power and market design policy issues for electricity markets, and in the methodological use of large industry-wide evolutionary simulation models.
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References
B. Allaz and J.-L. Vila, Cournot competition, tifutures markets and efficiency, Journal of Economic Theory 59(1) (1993) 1–16.
E.J. Anderson and A.B. Philpott, Using supply functions for offering generation into an electricity market, Operations Research 50(3) (2002) 477–489.
E.J. Anderson and A.B. Philpott, Optimal offer construction in electricity markets, Mathematics of Operations Research 27(1) (2002) 82–100.
S. Borenstein, J. Bushnell and C.R. Knittel, Market power in electricity markets: beyond concentration measures, The Energy Journal 20(4) (1999) 65–88.
S. Borenstein and J. Bushnell, An empirical analysis of the potential for market power in California's electricity industry, The Journal of Industrial Economics 47(3) (1999) 285–323.
J. Bower and D.W. Bunn, A model-based comparison of pool and bilateral market mechanisms for electricity trading, The Energy Journal 21(3) (2000) 1–29.
D.W. Bunn and F.S. Oliveira, Agent-based simulation: an application to the new electricity trading arrangements of England and Wales, IEEE Transactions on Evolutionary Computation 5(5) (2001) 493–503.
T.N. Cason and D. Friedman, Price formation in single call markets, Econometrica 65(2) (1997) 311–345.
R. Cooper, D.V. DeJong, R. Forsythe and T.W. Ross, Selection criteria in coordination games: some experimental results, The American Economic Review 80(1) (1990) 218–233.
C. Crampes and A. Creti, Price bids and capacity choice in electricity markets, Working paper (2001), available at http://www.idei.asso.fr/English/ECv/CvChercheurs/PageEcvCreti.html
C.J. Day and D.W. Bunn, Divestiture of generation assets in the England andWales electricity market: a computational approach to analysing market power, Journal of Regulatory Economics 19(2) (2001) 123–141.
Electricity Association, The UK electricity system (1999), www.electricity.org.uk.
Electricity Association, Electricity companies in the United Kingdom – a brief chronology (2000), www.electricity.org.uk.
Electricity Association, List of power stations (2000), www.electricity.org.uk.
Electricity Association, Who owns whom in the UK electricity industry (2000), www.electricity.org.uk.
N. Feltovitch, Reinforcement-based vs. belief-based learning models in experimental asymmetricinformation games, Econometrica 68(3) (2000) 605–641.
R.G. Green and D. Newbery, Competition in the British electricity spot market, Journal of Political Economy 100(5) (1992) 929–953.
B.F. Hobbs, Network models of spatial oligopoly with an application to deregulation of electricity generation, Operations Research 34(3) (1986) 395–409.
L.P. Kaelbling, M.L. Littman and A.W.Moore, Reinforcement learning: a survey, Journal of Artificial Intelligence Research 4 (1996) 237–285.
P.D. Klemperer and M.A. Meyer, Supply function equilibria in oligopoly under uncertainty, Econometrica 57(6) (1989) 1243–1277.
D.M. Kreps and J.A. Scheinkman, Quantitative precommitment and Bertrand competition yield cournot outcomes, The Bell Journal of Economics 14(2) (1983) 326–337.
J. Nicolaisen, V. Petrov and L. Tesfatsion, Market power and efficiency in a computational electricity market with discriminatory double-auction pricing, IEEE Transactions on Evolutionary Computation 5(5) (2001) 504–523.
Ofgem, The new electricity trading arrangements (July 1999), available at http://www.ofgem.gov.uk/.
Ofgem, Settlement administration agent user requirements specification (March 2000), available at http://www.ofgem.gov.uk/.
Ofgem, NGC incentives under Neta (April 2000), available at http://www.ofgem. gov.uk/.
Ofgem and DTI, The New Electricity Trading Arrangements, Ofgem/DTI Conclusions Document (October 1999), available at http://www.ofgem.gov.uk/.
A.E. Roth and I. Erev, Learning in extensive-form games: experimental data and simple dynamic models in the intermediate term, Games and Economic Behavior 8 (1995) 164–212.
M.H. Rothkopf, Daily repetition: a neglected factor in the analysis of electricity auctions, The Electricity Journal (1999) 61–70.
A. Salama, Privatization and culture change: British nuclear fuels case study, Energy Policy 25(3) (1997) 293–304.
R. Sarin and F. Vahid, Predicting how people play games: a simple dynamic model of choice, Games and Economic Behavior 34 (2001) 104–122.
R.W. Staiger and F.A. Wolak, Collusive pricing with capacity constraints in the presence of demand uncertainty, The RAND Journal of Economics 23(2) (1992) 203–220.
R.S. Sutton and A.G. Barto, Reinforcement Learning: An Introduction (MIT Press, Cambridge, MA, 1998).
A. Sweetser, Measuring a dominant firm's market power in a restructured electricity market, a case study of Colorado, Utilities Policy 7 (1998) 243–257.
J.B. Van Huyck, R.C. Battalio and R.O. Beil, Tacit coordination games, strategic uncertainty, and coordination failure, The American Economic Review 80(1) (1990) 234–248.
N.-H.M. Von der Fehr and D. Harbord, Spot market competition in the UK electricity industry, The Economic Journal 103(418) (1993) 531–546.
J. von Neumann and O. Morgenstern, Theory of Games and Economic Behavior (Princeton University Press, Princeton, NJ, 1972).
J.-Y. Wei and Y. Smeers, Spatial oligopolistic electricity models with Cournot generators and regulated transmission prices, Operations Research 47(1) (1999) 102–112.
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Bunn, D.W., Oliveira, F.S. Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation. Annals of Operations Research 121, 57–77 (2003). https://doi.org/10.1023/A:1023399017816
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DOI: https://doi.org/10.1023/A:1023399017816