| The overall pattern of "separating power plants from power networks and generation bidding mechanism" on generation-side has become the established fact in China as the revolution of electric power market going on. Based on this fact, the discussion and research of electric power market bidding mechanism and power plants’bidding strategy has become more and more popular because these studies will directly benefit lots of people. As each power plants’ bidding strategy are influenced by other power plants, the most common methods for studying these problems are using gaming theory or evolutionary gaming theory. But these methods are limited by the lots of assumption and will extremely hard for solving this kind of problems if they have many power plants or many strategies. Inspired by the theory which was presented by some researchers that every simple, one population, economic genetic algorithm is an evolutionary game, in this paper, A method has proposed based on the improved Genetic Algorithm to simulate the bidding behaviors of power plants in electric power market. The author firstly stated the basic theory and result of Genetic Algorithm, and then improved the reproduction operator and the crossover operator with some testing experiments followed for verifying the validity of the new mechanism. Then the market model which is much realistic in electric power market is presented and many simulations have been done on this new model. Based on the analysis of the simulation, MCP mechanism is better than PAB mechanism on the rapidity to get equilibrium status and the ultimate stability, as it differs little on the final equilibrium price. So, MCP mechanism is more suitable for the electric power market in China. |
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