The 2020 Power Trading Agent Competition

47 Pages Posted: 30 Mar 2020

See all articles by Wolfgang Ketter

Wolfgang Ketter

University of Cologne - Institute of Energy Economics; Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management; Erasmus Research Institute of Management (ERIM)

John Collins

University of Minnesota - Twin Cities

Mathijs de Weerdt

Delft University of Technology

Date Written: March 30, 2020

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 positions, 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.

Keywords: Autonomous Agents, Electronic Commerce, Energy, Preferences, Portfolio Management, Power, Policy Guidance, Sustainability, Trading Agent Competition

Suggested Citation

Ketter, Wolfgang and Collins, John and Weerdt, Mathijs de, The 2020 Power Trading Agent Competition (March 30, 2020). ERIM Report Series Reference No. 2020-002, Available at SSRN: https://ssrn.com/abstract=3564107 or http://dx.doi.org/10.2139/ssrn.3564107

Wolfgang Ketter (Contact Author)

University of Cologne - Institute of Energy Economics ( email )

Alte Wagenfabrik
Vogelsanger Strasse 321a
Cologne, 50827
Germany

HOME PAGE: http://ewi.uni-koeln.de/en/

Erasmus University Rotterdam (EUR) - Department of Technology and Operations Management ( email )

RSM Erasmus University
PO Box 1738
3000 DR Rotterdam
Netherlands

Erasmus Research Institute of Management (ERIM) ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

HOME PAGE: http://www.rsm.nl/energy

John Collins

University of Minnesota - Twin Cities ( email )

420 Delaware St. SE
Minneapolis, MN 55455
United States

Mathijs de Weerdt

Delft University of Technology ( email )

Stevinweg 1
Delft, 2628 CN
Netherlands

HOME PAGE: http://www.alg.ewi.tudelft.nl/weerdt/

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
106
Abstract Views
487
rank
286,315
PlumX Metrics