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Optimal Configuration Method of Photovoltaic Intelligent Edge Terminal Based on Improved Coyote Optimization Algorithm |
Liu Jiaheng1, Zhang Ming2, Ge Leijiao1, Ji Wenlu2, Wang Bo3, Fang Lei2, Zhang Weiya2 |
1. Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin 300072 China; 2. Nanjing Power Supply Company State Grid Jiangsu Electric Power Co. Ltd Nanjing 210005 China; 3. School of Electrical and Engineering Wuhan University Wuhan 430072 China |
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Abstract Photovoltaic intelligent edge terminal (PV IET) is one of the important devices to achieve efficient and intelligent operation and maintenance of distributed PV large-scale access to distribution network. In this paper, a mathematical model for optimizing the configuration of PV IETs is presented, and an improved coyote optimization algorithm (ICOA) is proposed to achieve an accurate solution of the model. In order to solve the problems of insufficient precision of the coyote optimization algorithm and slow convergence speed, a new social mutual assistance coyote growth strategy and the optimal coyote single-dimensional disturbance strategy in group are proposed, and simulated annealing and adaptive elite retention strategies are introduced to make the algorithm more suitable the engineering issues raised in this article. Realize the three aspects of the number, location and connection mode of PVIET to the PV power station. Finally, the validity of the model is verified by the improved IEEE69 cases, and the superiority of the ICOA in accuracy, stability and convergence is verified by the comparison of algorithms.
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Received: 14 May 2020
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