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Study On Capacity Allocation Optimization of Independent Wind/PV/Storage Generation System

A reasonable capacity allocation and optimization for the wind/PV/storage independent system could reduce the initial investment of the system and improve the security of power system. In this paper, a capacity optimization method is introduced based on quantum genetic algorithm, the life cycle cost (LCC) and the loss of power supply probability(LPSP)are taken as the system evaluation index, economic and other conditions are taken as the constraints, the number of the wind turbines, solar cells and batteries as the variable. Quantum genetic algorithm(QGA) can promote population evolution through quantum bit coding and quantum rotating gate, which can effectively overcome the precocious and slow convergence of traditional genetic algorithm(GA) and easy to get out of local optimal, so can quickly get the optimal capacity of the system. The simulation results show that the reasonable and superior of the above algorithm are compared with the traditional genetic algorithm.