An agent-based approach equipped with game theory: Strategic collaboration among learning agents during a dynamic market change in the California electricity crisis

Energy Economics

Volumn 32, Issue 5, 2010, Pages 1009-1024

  Sueyoshi, Toshiyuki ^a,b  

^a NEW MEXICO INSTITUTE OF MINING AND TECHNOLOGY   (United States)

^b NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Agent based approach; Electricity market; Partial reinforcement learning

Indexed keywords

AGENT-BASED APPROACH; CALIFORNIA ELECTRICITY CRISIS; COMPLEX CHARACTERISTICS; DEGREE OF COLLABORATION; DYNAMIC MARKET; ELECTRICITY MARKET; LEARNING AGENTS; LEARNING CAPABILITIES; LEARNING SPEED; MARKET CHANGES; PARTIAL REINFORCEMENT LEARNING; POWER-EXCHANGE MARKET; STRATEGIC COLLABORATION; TRADING AGENT;

ECONOMICS; ELECTRIC INDUSTRY; ELECTRICITY; GAME THEORY; INTELLIGENT AGENTS; MULTI AGENT SYSTEMS; REINFORCEMENT LEARNING; SPEED;

COMMERCE;

ELECTRICITY; ENERGY MARKET; GAME THEORY; LEARNING; NUMERICAL MODEL;

EID: 77956733322     PISSN: 01409883     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eneco.2009.12.004     Document Type: Article

References (28)

1. Bagnall A.J. A multi-adaptive agent model of generator bidding in the UK market in electricity. Proceeding of Genetic and Evolutionary Computation Conference, Las Vegas, Nevada 2000, 605-612.
2. Bereby-Meyer Y., Roth A.E. The speed of learning in noisy games: partial reinforcement and the sustainability of cooperation. American Economic Review 2006, 96:1029-1042.
3. Borenstein S., Bushnell J.B., Wolak F.A. Measuring market inefficiencies in California's restructured wholesale electricity market. American Economic Review 2002, 92:1376-1405.
4. Bunn D.W., Oliveira F.S. Agent-based simulation: an application to the new electricity trading arrangements of England and Wales. IEEE Transaction on Evolutional Computation 2001, 5:493-503.
5. Camerer C.F. Progress in behavioral game theory. Journal of Economic Perspective 1997, 11:167-188.
6. Chevillon G., Rifflart C. Physical market determinants of the price of crude oil and the market premium. Energy Economics 2009, 31:537-549.
7. Chialvo D.P., Bak P. Learning from mistakes. Neuroscience 1999, 90:1137-1148.
8. Erev I., Roth A.E. Predicting how people play games: reinforcement learning in experimental games with unique, mixed strategy equilibria. American Economic Review 1998, 88:848-881.
9. Ghaffari A., Zare S. A novel algorithm for prediction of crude oil price variation based on soft computing. Energy Economics 2009, 31:531-536.
10. Jacobs J.M. Artificial power markets and unintended consequences. IEEE Transactions on Power Systems 1997, 12:968-972.
11. Joskow P.L., Kahn E.A. Quantitative analysis of pricing behavior in California's wholesale electricity market during summer 2000. The Energy Journal 2002, 23:1-35.
12. Knittel C.R., Roberts M.R. An empirical examination of restructured electricity prices. Energy Economics 2005, 27:791-817.
13. Makowski M., Nakamori Y., Sebastain H.J. Advances in complex system modeling. European Journal of Operational Research 2005, 166:593-858.
14. Mohammadi H. Electricity prices and fuel costs: long-run relations and short-run dynamics. Energy Economics 2009, 31:503-509.
15. Morikiyo T., Goto M. Artificial trading for US wholesale electric power market. Asia Pacific Management Review 2004, 9:751-782.
16. Redl C., Haas R., Huber C., Böhm B. Price formation in electricity forward markets and the relevance of systematic forecast errors. Energy Economics 2009, 31:356-364.
17. Roth A.E., Erev I. Learning in extensive-form games: experimental data and simple dynamic models in the intermediate term. Games and Economic Behavior 1995, 8:164-212.
18. Samuelson D. Agents of change. OR/MS Today 2005, 32:26-31.
19. Shahidehpour M., Yamin H., Li Z. Market Operations in Electric Power System 2002, John Wiley & Sons, NY.
20. Si J., Wang Y.-T. On-line learning control by association and reinforcement. IEEE Transactions on Neural Networks 2001, 12:264-276.
21. Stoft S. Power System Economics 2002, IEEE Press, Piscataway, NJ.
22. Sueyoshi T. Beyond economics for guiding large public policy issue: Lessons from the Bell System Divestiture and the California electricity crisis. Decision Support Systems 2010, 43:457-469.
23. Sueyoshi T., Tadiparthi G.R. A wholesale power trading simulator with learning capabilities. IEEE Transactions on Power Systems 2005, 20:1330-1340.
24. Sueyoshi T., Tadiparthi G.R. An agent-based approach to handle business complexity in US wholesale power trading. IEEE Transactions on Power System 2007, 22:532-543.
25. Sueyoshi T., Tadiparthi G.R. Wholesale power price dynamics under a capacity limit in transmission. IEEE Transactions on Systems, Man and Cybernetics: Part C 2008, 38:229-241.
26. Sueyoshi T., Tadiparthi G.R. An agent-based decision support system for wholesale electricity market. Decision Support Systems 2008, 44:425-446.
27. Sueyoshi T., Tadiparthi G.R. Why did California electricity crisis occur? A numerical analysis using multi-agent intelligent simulator. IEEE Transactions on Systems, Man and Cybernetics: Part C 2008, 38:779-790.
28. Wilson R. Architecture of power markets. Econometrica 2002, 70:1299-1340.