Bidding Simulation Methods of Multi-input Decision Factors for Power Suppliers based on Intelligent Agent

Abstract

With the development of electric power industry, it has become an urgent problem of deregulation of the industry. From monopoly to free competition, the market participants’ bidding decisions will undergo great change. Because of difference of market participants’ cost, risk preference, relationship of supply and demand, bidding behaviors of market participants show a more perplexing situation. In this paper, a multi-input decision factors algorithm based on intelligent agent is used to simulate the behavior of generators. The influence of subordinate objective of decision and risk preference on the bidding behavior of generators is considered in the model. The case analysis shows that generator's intelligent agent model established in this paper can well simulate generators of different characteristics; through learning the historical experience, generators can improve their bidding behaviors, update the selection probability of each bidding strategy, and finally achieve good returns.