Sustainable energy systems of the future will no longer be able to rely on the current paradigm that energy supply fol-lows demand. Many of the renewable energy resources do not produce power on demand, and therefore there is a need for new market structures that motivate sustainable behav-iors by participants. The Power Trading Agent Competition (Power TAC) is a new annual competition that focuses on the design and operation of future retail power markets, specifi-cally in smart grid environments with renewable energy pro-duction, smart metering, and autonomous agents acting on behalf of customers and retailers. It uses a rich, open-source simulation platform that is based on real-world data and state-of-the-art customer models. Its purpose is to help researchers understand the dynamics of customer and retailer decision-making, as well as the robustness of proposed market de-signs. This paper introduces TACTEX’13, the champion agent from the inaugural competition in 2013. TACTEX’13 learns and adapts to the environment in which it operates, by heav-ily relying on reinforcement learning and prediction meth-ods. This paper describes the constituent components of TACTEX’13 and examines its success through analysis of competition results and subsequent controlled experiments. 1
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Urieli et al. (2014) studied this question.