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The 2020 Power Trading Agent Competition

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  • Ketter, W.
  • Collins, J.
  • de Weerdt, M.M.

Abstract

This is the specification for the Power Trading Agent Competition for 2020 (Power TAC 2020). Power TAC is a competitive simulation that models a “liberalized” retail electrical energy market, where competing business entities or “brokers” offer energy services to customers through tariff contracts, and must then serve those customers by trading in a wholesale market. Brokers are challenged to maximize their profits by buying and selling energy in the wholesale and retail markets, subject to fixed costs and constraints; the winner of an individual “game” is the broker with the highest bank balance at the end of a simulation run. Costs include fees for publication and withdrawal of tariffs, for rectifying supply-demand imbalances, for contributions to peak demand, and for customer connections. The simulation environment models a wholesale market, a regulated distribution utility, and a population of energy customers, situated in a real location on Earth during a specific period for which weather data is available. The wholesale market is a relatively simple call market, similar to many existing wholesale electric power markets, such as Nord Pool in Scandinavia or FERC markets in North America, but unlike the FERC markets we are modeling a single region, and therefore we approximate the effects of locational-marginal pricing through manipulation of the wholesale supply curve. Customer models include households, electric vehicles, and a variety of commercial and industrial entities, many of whom have production capacity such as solar panels or wind turbines. All have “real-time” metering to support allocation of their hourly supply and demand to their subscribed brokers, and all are approximate utility maximizers with respect to tariff selection, although the factors making up their utility functions may include aversion to change and complexity that can retard uptake of marginally better tariff offers. A distribution utility models the regulated natural monopoly that owns the regional distribution network, and is responsible for maintenance of its infrastructure. Real-time balancing of supply and demand is managed by a market-based mechanism that uses economic incentives to encourage brokers to achieve balance within their portfolios of tariff subscribers and wholesale market posi- tions, in the face of stochastic customer behaviors and weather-dependent renewable energy sources. Changes for 2020 are focused on stability and on making customer evaluation of regulation rates more realistic, and are highlighted by change bars in the margins. See Section 4.1.1 for details.

Suggested Citation

  • Ketter, W. & Collins, J. & de Weerdt, M.M., 2020. "The 2020 Power Trading Agent Competition," ERIM Report Series Research in Management ERS-2020-002-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:125794
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    References listed on IDEAS

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    1. Martin Bichler & Alok Gupta & Wolfgang Ketter, 2010. "Research Commentary ---Designing Smart Markets," Information Systems Research, INFORMS, vol. 21(4), pages 688-699, December.
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    Cited by:

    1. Sanjay Chandlekar & Easwar Subramanian & Sanjay Bhat & Praveen Paruchuri & Sujit Gujar, 2022. "Multi-unit Double Auctions: Equilibrium Analysis and Bidding Strategy using DDPG in Smart-grids," Papers 2201.10127, arXiv.org, revised Feb 2022.

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    Keywords

    Autonomous Agents; Electronic Commerce; Energy; Preferences; Portfolio Management; Power; Policy Guidance; Sustainability; Trading Agent Competition;
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