Strategic Behavior in Spot Markets for Electricity when Load is Stochastic
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 4 - Volume 4
Object-Oriented Thought Process, The (2nd Edition)
Object-Oriented Thought Process, The (2nd Edition)
Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Handbook of Computational Economics)
IEEE Transactions on Evolutionary Computation
Modeling Implicit Collusion Using Coevolution
Operations Research
An algorithmic game theory study of wholesale electricity markets based on central auction
Integrated Computer-Aided Engineering - Multi-Agent Systems for Energy Management
Strategic bidding methodology for electricity markets using adaptive learning
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
Integrating power and reserve trade in electricity networks
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Agent-based competitive simulation: exploring future retail energy markets
Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Hi-index | 0.00 |
In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design--the Wholesale Power Market Platform (WPMP)--for common adoption by all US wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration.