A bidding method of power market based on immune genetic algorithm

With the merging of the power market in China, power plants were faced with a serious challenge. The power market on generation-side of separating power plants from power networks and generation bidding will become the main operating model in our hometown. It is necessary to improve social benefits and reduce the purchasing price with the mature power technology. This thesis researches on bidding method of power market, according to the development direction of power market in our country. One immune genetic algorithm has been explored for bidding of power market in this thesis, which opens up one new kind of approach to solve the problem of bidding. The typical computational example shows that presented algorithm is a new effective optimal method, as it can obtain better result and has faster convergence speed.