Chuanwen JIANG
Shanghai Jiaotong University

Abstract: Competition has been introduced in the last decade into the electricity markets and is presently underway in many countries. A centralized approach for the dispatching of the generation units has been substituted by a market approach based on the biddings submitted by the supply side and, eventually, by the demand side. Each producer is a player in the market acting to maximize its utility. The decision making process of the producers and their interactions in the market are a typical complex problem that is difficult to model explicitly, and can be studied with a multi agents approach. This paper proposes a model able to capture the decision making approach of the producers in submitting strategic biddings to the market and simulate the market outcomes resulting from those interactions. The model is based on the Watkins’s Q(λ) Reinforcement Learning and takes into account the network constraints that may pose considerable limitations to the electricity markets. The model can be used to define the optimal bidding strategy for each producer and, as well, to find the market equilibrium and assessing the market performances. The model proposed is applied to a standard IEEE 14-bus test system to illustrate its effectiveness.