Strategic Bidding Of Electricity Supplier In Competitive Market Based On Improved Q-Learning

The innovation of electric power industry is being gradually deepening in the world. At present, our country is constructing the region power market positively, and had carried on generation unbundling and the competition bidding. The generation field market implements competition mechanism. As a hot topic researched in power market, to research and to discuss generation bidding strategy have the important theory and the practical value.Currently the strategic bidding behaviors in the long term trading are difficult to be mathematic modeled. For the complexity of the strategic interaction among the multi market participants, the multi agents system has an inspiring outlook in such research area. This thesis developed a model basing on the Reinforcement Learning to simulating the long term trading in an oligopoly electricity market .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.Fuzzy reasoning and reinforcement learning are the commonly used...