Research On Distributed Optimization Of Energy Management In Smart Grid Based On Game Theory

With the aging of the electrical equipment,the increasing demand for electricity and the development of the new energy technology,the power system technology is required for its better reliability,stability and efficiency.Smart grid is aimed as to optimize the quality and stability of the power itself provided,and then to decrease the operating risk.In the trend of researches on smart grid,optimization of energy management is seen as key technology.Moreover,it includes amending users' strategy as well as optimizing the system for its supply and distribution.Based on the study of relative works of literature,the main contributions of this paper are listed as follows:Firstly,based on evolutionary game theory,a dynamic interactive algorithm model to analyze the user engagement is proposed.Specifically,the general users' pay-off function is constructed at the beginning.Then,users are classified due to their power consumption.The strategy space is constructed whether the user choose to participate in the intelligent electricity allocation and relatively,the different evolutionary game model is established.Finally,simulation cases are conducted as to validate the convergence and effectiveness of the algorithm.Secondly,via liberating the limitation of the one-supply-side,a three-level network system is constructed based on game theory.Simulation cases are conducted and calculated as to validate the convergence and effectiveness of the three-level model.Lastly,as to enhance the absorptive capability for the new energy source power generation,a mixed control constructure is proposed based on the MAS theory.A distributed optimization algorithm is conducted as to fulfill the global object of the muli-microgrids system.A kind of consensus simulation is conducted to validate the efficiency of the algorithm.