An intelligent broker agent for energy trading: an MDP approach

  • Authors:
  • Rodrigue T. Kuate;Minghua He;Maria Chli;Hai H. Wang

  • Affiliations:
  • School of Engineering and Applied Sciences, Aston University, Birmingham, United Kingdom;School of Engineering and Applied Sciences, Aston University, Birmingham, United Kingdom;School of Engineering and Applied Sciences, Aston University, Birmingham, United Kingdom;School of Engineering and Applied Sciences, Aston University, Birmingham, United Kingdom

  • Venue:
  • IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
  • Year:
  • 2013

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Abstract

This paper details the development and evaluation of AstonTAC, an energy broker that successfully participated in the 2012 Power Trading Agent Competition (Power TAC). AstonTAC buys electrical energy from the wholesale market and sells it in the retail market. The main focus of the paper is on the broker's bidding strategy in the wholesale market. In particular, it employs Markov Decision Processes (MDP) to purchase energy at low prices in a day-ahead power wholesale market, and keeps energy supply and demand balanced. Moreover, we explain how the agent uses Non-Homogeneous Hidden Markov Model (NHHMM) to forecast energy demand and price. An evaluation and analysis of the 2012 Power TAC finals show that AstonTAC is the only agent that can buy energy at low price in the wholesale market and keep energy imbalance low.