Abstract
As electricity markets evolve, there is a need for new modelling approaches that simulate how electric power markets could evolve over time and how participants in these markets may act and react to the changing economic, financial and regulatory environment in which they operate. To study electricity markets behaviour and evolution we propose a multi-agent simulator where agents represent several entities that can be found in electricity markets, such as generators, consumers, market operators and network operators, but also entities that are emerging with the advent of liberalization, such as traders. The simulator probes the possible effects of market rules and conditions by simulating the strategic behaviour of participants. In this paper a special attention is devoted to the behaviour and characteristics of Seller, Buyer and Trader agents, highlighting their strategies and decision processes in order to gain advantage facing the new emerging competitive market.
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
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
PowerWeb - http://stealth.ee.cornell.edu/powerweb/
Electric Power Research Institute - http://www.agentbuilder.com/Documentation/EPRI/
Harp, S., Brignone, S., Wollenberg, B.: SEPIA: Simulator for Electric Power Industry Agents. IEEE Control Systems 20(4), 53–69 (2000)
Bower, J., Bunn, D.: Agent-based Simulation - An Application to the New Electricity Trading Arrangements of England and Wales. IEEE Transactions on Evolutionary Computation 5(5), 493–503 (2001)
Monclar, F.R., Quatrain, R.: Simulation of Electricity Markets: A Multi-Agent Approach. In: Proc. of the 2001 International Conference on Intelligent Systems Application to Power Systems, pp. 207–212 (2001)
Nicolaisen, J., Petrov, V., Tesfatsion, L.: Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing. IEEE Transactions on Evolutionary Computation 5(5), 504–523 (2001)
Villar, J., Rudnick, F.: Hydrothermal Market Simulator Using Game Theory: Assessment of Market Power. IEEE Transactions on Power Systems 18(1), 91–98 (2003)
Contreras, J., Conejo, A.J., Torre, S., Munoz, M.G.: Power Engineering Lab: Electricity Market Simulator. IEEE Transactions on Power Systems 17(2), 223–228 (2002)
Praça, I., Ramos, C., Vale, Z., Cordeiro, M.: A Multi-Agent Simulation Prototype for Decision Support in Electricity Markets. In: Proc. of the 2002 AI, Simulation and Planning in High Autonomy Systems, pp. 247–252 (2002)
Praça, I., Ramos, C., Vale, Z., Cordeiro, M.: Intelligent Agents for Negotiation and Game-based Decision Support in Electricity Markets. In: Proc. of the 12th Intelligent Systems Applications to Power Systems Conference (2003) (to appear)
Sheble, G.: Computational Auction Mechanisms for Restructured Power Industry Operation. Kluwer Academic Publishers, Dordrecht (1999)
Shahidehpour, M., Yamin, H., Li, Z.: Market Operations in Electric Power Systems: Forecasting, Scheduling and Risk Management. John Wiley & Sons, Chichester (2002)
Greenwald, A., Kephart, J., Tesauro, G.: Strategic Pricebots Dynamics. In: Proc. of the First ACM Conference on Electronic Commerce, pp. 58–67 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Praça, I., Ramos, C., Vale, Z., Cordeiro, M. (2003). An Agent-Based Simulator for Electricity Markets: Seller, Buyer, and Trader Players. In: Mařík, V., McFarlane, D., Valckenaers, P. (eds) Holonic and Multi-Agent Systems for Manufacturing. HoloMAS 2003. Lecture Notes in Computer Science(), vol 2744. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45185-3_27
Download citation
DOI: https://doi.org/10.1007/978-3-540-45185-3_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40751-5
Online ISBN: 978-3-540-45185-3
eBook Packages: Springer Book Archive