Synergistic Optimization Scheduling Considering Large-Scale Wind

In order to achieve economic dispatch of the turbines and reduce pollution and the equivalent load fluctuation, combining with the characteristics of two-way flow between EV, Considering the impact of wind power intermittent and the randomness of electric vehicle charging and discharging on the grid, a mathematic model of economic dispatch considering large-scale wind power and electric vehicles integration is built which takes the minimum power generation cost, exhaust emission cost and the equivalent load fluctuation variance as its multi-objective function. Based on the epsilon dominant multi-objective particle swarm optimization algorithm is used to solve the model. This method can guarantee external archive the pare to solutions in convergence and distribution, and overcome the defects of the particle swarm optimization (pso) algorithm in solving multi-objective optimization problems easy to converge to pseudo pare to front and slow convergence speed. Finally, the simulation experiment shows that synergistic optimization scheduling model compared with the single objective optimization scheduling model, can effectively restrain the renewable energy power generation output fluctuations and reduce power generation cost and exhaust emission cost.