Optimization Allocation Of Microgrid Generation Considering The Infruence Of V2G

Microgrid plays an important role in realizating that distributed generation connects to the power system safely and friendly. The capacity of electric vehicles accessing to microgrid is larger and larger and larger. Compared with wind power and photovoltaic, V2 G technology can realize the the controllable scheduling fro electric, and it will smooth renewable energy power generation unit. Distributed generation and electric vehicles of distributed power supply will have an impact on the economic and safe operation. Unreasonable configuration of distributed power supply may reduce the utilization efficiency of renewable energy and reliability of power supply for load.All of the existing studies donot consider the influence of elcectric vehicles when configure distributed power supply. According to the shortage of present research, and considering total cost of power generation, environmental benefits, and powe supply reliability assurance in islanded conditions, this paper introduces V2 G control technology into microgrid power allocation optimization, and constructs the mathematic model of microgrid optimization allocation considering the effects of V2 G.According to the advantage of optimization algorithm in processing multi-objective problem, this paper overcomes the disadvantages of pareto method and multi group method and combines the advantages of them. VEPSO-BP(Vector evaluated particle swarm optimization algorithm based on Pareto) is proposed to solve the model. An elite set is set up in the outside, and Pareto non dominated solutions are extracted from the elite concentrated by the roulette method before each iteration, and they are used to guide the particles to the Pareto frontier.Through the SIMULINK simulation model and parameter setting, the simulation experiment is carried out. The optimized allocation results show that the total power generation cost will increase with the reduction of the maximum outage probability, but the environmental benefit cost will be decreased gradually. By comparing vector evaluated particle swarm optimization algorithm based on Pareto, genetic algorithm, and colony algorithm, it proves that vector evaluated particle swarm optimization algorithm has more fast convergence speed and higher precision in dealing with multiobjective optimization.Through the analysis of optimization results, it can be seen that renewable energy, such as wind power and photovoltaic, still has a disadvantage in generation cost, but has better environment benefit. Therefore, in order to promote the development of renewable energy generation, there is a need to formulate market incentive mechanism such as levying carbon trading tax and improve the renewable energy power generation price for sale.