| Wind power generation,as one of the renewable energy generation,has several advantages such as clean and easily accessible.With the penetration of wind power rising up,the uncertainty brought by the volatility of the wind power generation has become more and more prominent.Moreover,the randomness of the load in demand side also makes such uncertainty more intense.An effective way to stabilize the wind power output fluctuation and eliminate the uncertainty which brought by the load randomness in the transmission system is to configure battery energy storage system(BESS).Thus,the optimal configuration of battery energy storage system is studied,which aims at improving the economic and security performance of the transmission network by considering the uncertainties.The main work of this thesis is as follows:A multi-objective particle swarm optimization affine method considering both randomness of wind power and load is proposed to allocate energy storage system.Firstly,the location and capacity of BESS are randomly generated and affine algorithm is used to solve the uncertainty power flow to get superior solutions.Secondly,a method is proposed to compare the dominance relations between two affine numbers and eliminate inferior solutions.Thirdly,a congestion value sorting method based on affine arithmetic is also proposed to choose the best particle in PSO and tailor the solution set and finally obtain the Pareto optimal solution set.The IEEE-14 node transmission system and IEEE-30 node transmission system are studied for the optimal configuration of BESS under the circumstances where wind farms are fixed and the optimal configuration of both BESS and wind farms where wind farms are not fixed,respectively.The results illustrate the effectiveness and efficiency of the method.It shows that the Pareto optimal solution set achieved by the method can effectively solve the deficiency of the lack of diversity and comprehensiveness of the results in the existing methods. |
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