Comparative study of optimization methods for optimal coordination of directional overcurrent relays with distributed generators

Q2 Decision Sciences
Zineb El Idrissi, Touria Haidi, Faissal Elmariami, Abdelaziz Belfqih
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引用次数: 0

Abstract

Due to the growing penetration of distributed generators (DGs), that are based on renewable energy, into the distribution network, it is necessary to address the coordination of directional overcurrent relays (DOCR) in the presence of these generators. This problem has been solved by many metaheuristic optimization techniques to obtain the optimal relay parameters and to have an optimal coordination of the protection relays by considering the coordination constraints. In this article, a comparative study of the optimization techniques proposed in the literature addresses the optimal coordination problem using digital DOCRs with standard properties according to IEC60-255. For this purpose, the three most efficient and robust optimization techniques, which are particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution (DE), are considered. Simulations were performed using MATLAB R2021a by applying the optimization methods to an interconnected 9-bus and 15-bus power distribution systems. The obtained simulation results show that, in case of distributed generation, the best optimization method to solve the relay protection coordination problem is the differential evolution DE.
定向过流继电器与分布式发电机最优协调优化方法的比较研究
span lang="EN-US">由于基于可再生能源的分布式发电机(dg)越来越多地渗透到配电网中,有必要解决这些发电机存在的定向过流继电器(DOCR)的协调问题。许多元启发式优化技术已经解决了这一问题,通过考虑协调约束来获得最优的继电器参数和继电器的最优协调。在本文中,对文献中提出的优化技术进行了比较研究,根据IEC60-255,使用具有标准属性的数字docr解决了最优协调问题。为此,考虑了粒子群优化(PSO)、遗传算法(GA)和差分进化(DE)三种最有效、最稳健的优化技术。利用MATLAB R2021a软件,将优化方法应用于9总线和15总线互联配电系统的仿真。仿真结果表明,在分布式发电情况下,解决继电保护协调问题的最佳优化方法是差分演化DE. </span>
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来源期刊
IAES International Journal of Artificial Intelligence
IAES International Journal of Artificial Intelligence Decision Sciences-Information Systems and Management
CiteScore
3.90
自引率
0.00%
发文量
170
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