Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework
Computational Economics
Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity)
An agent-based decision support system for wholesale electricity market
Decision Support Systems
Adapting in agent-based markets: a study from TAC SCM
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Empirical game-theoretic analysis of the TAC Supply Chain game
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Characterizing effective auction mechanisms: insights from the 2007 TAC market design competition
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Forecasting market prices in a supply chain game
Electronic Commerce Research and Applications
Agent-based simulation of electricity markets: a survey of tools
Artificial Intelligence Review
Efficient statistical methods for evaluating trading agent performance
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Detecting and forecasting economic regimes in multi-agent automated exchanges
Decision Support Systems
An agent architecture for multi-attribute negotiation
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Assessing the Impact of Price Forecast Errors on the Economics of Distributed Storage Systems
HICSS '10 Proceedings of the 2010 43rd Hawaii International Conference on System Sciences
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Future sustainable energy systems will need efficient, clean, low-cost, renewable energy sources, as well as market structures that motivate sustainable behaviors on the part of households and businesses. "Smart grid" components can help consumers manage their consumption only if pricing policies are in place that motivate consumers to install and use these new tools in ways that maximize utilization of renewable energy sources while minimizing dependence on non-renewable energy. Serious market breakdowns, such as the California energy crisis in 2000, have made policy makers wary of setting up new retail energy markets. We present the design of an open, competitive simulation approach that will produce robust research results on the structure and operation of retail power markets as well as on automating market interaction by means of competitively tested and bench-marked electronic agents. These results will yield policy guidance that can significantly reduce the risk of instituting competitive energy markets at the retail level, thereby applying economic motivation to the problem of adjusting our energy production and consumption patterns to the requirements of a sustainable future.