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Fuzzy Multi-objective Optimization Model about Wind Pow-er-Photovoltaic Power-Concentrating Solar Power Hybrid Power Genera-tion System
Received:February 19, 2019  Revised:March 19, 2019
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Keywords:The concentrating solar power plant with thermal storage  Fuzzy Multi-objective Optimization  Peaking shaving  Maximum satisfaction index  DE-PSO algorithm.
Fund Project:Science and Technology Project of State Grid Corporation of China
zhanghong Power System and Automation zhanghong1802@163.com
Chen Zhao 2906232965@qq.com
Huang Rong 2833507286@qq.com
donghaiying School of New Energy & Power Engineering, Lanzhou Jiaotong University;School of Automation and Electrical Engineering, Lanzhou JiaoTong University hydong@mail.lzjtu.cn
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      In order to realize the friendly integration of high proportion of new energy represented by scenery in power system, this paper integrates wind farm, photovoltaic power station and concentrating solar power station as a multi-power hybrid system, a fuzzy multi-objective optimization model about wind power-photovoltaic- concentrating solar power combined power generation system is proposed. The concentrating solar power plant with thermal storage has good schedulability and controllability, which provides rotating standby and climbing support, reducing the randomness and uncertainty of the wind output, thus realizing its peak-shaving function. A multi-objective optimization model is built,which considers maximum benefit and the minimum fluctuation variance of combined operation. The deterministic model is fuzzified by defin-ing the target membership function, and the multi-objective optimization model is transformed into a single-objective optimization model by using the maximum satisfaction index method. Particle Swarm Optimization Based on Differential Evolution is used to solve it. The simulation results of the example system show that the fuzzy multi-objective optimization can make full use of the advantages of the concentrating solar power plant to achieve the overall optimal operation effect, the DE-PSO algorithm has better convergence accuracy and higher computational efficiency when solving nonlinear programming problems, thereby the feasibility and effectiveness of the proposed optimal operation model and algorithm are verified.