Application And Analysis Of Stochastic Evolutionary Model In Power Generation Market

Random evolutionary game dynamics involving such disciplines as mathematics, physics, biology and game theory, an active multidisciplinary research field, provides a powerful theoretical framework for the choice of dynamic, experienced30years of development has been formedmature scientific theoretical system. Replication dynamic equation of infinite groups is relatively mature, and the evolutionary dynamics of finite groups is lagging behind, until the recent introduction of the random way that makes its evolutionary dynamic gradually mature.Knowledge of game theory in the second chapter introduces the ESS. The third chapter describes the asynchronous update Comparison process, the frequency-dependent Moran process, as well as the sync frequency dependent Wright-Fisher process. In view of the evolution of static equilibrium in evolutionary game theory (ESS) the importance of this paper discusses the adjustments under the evolutionary dynamics equations in the three stochastic processes, and then study the fixation probability of strategy in the selection criteria of the weak, the whole structure evolution dynamic complexity, in order to get accurate results, only discuss the dynamic evolution of the simplest symmetric game, the fixation probability of strategy update mechanism.Reform of the electricity market, generation companies to participate in the market bidding to become more and more intense. In the current electricity market competition, the bidding strategies of generators are used to some extent, determine their income. Generators most mainstay of the market, however, have the characteristics of bounded rationality, and the strategies they used each other to contain the entire bidding process can be regarded as generators to adjust strategy, to making to achieve a balanced game process by using the method combined with the PX market model based Comparison Stochastic evolutionary Game BIDDING policy guidance in the application section, simulation results show that the method can dynamically adjust the strategy to help generators and ultimately seek the maximum benefit.