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Optimum coordination of directional overcurrent relay in presence of distributed generation using genetic algorithm

机译:遗传算法在分布式发电情况下定向过流继电器的最优协调

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Distributed generation (DG) is commonly used to supply the local loads. The penetration of distributed generation leads to violating the relay coordination in the distribution network. The interconnection of DG affects miscoordination of distribution system protection, because of the generator ability to contribute large fault currents to the fault point. The impact of DG on relay coordination affect the operating time of relay. The CTI associated with primary and backup relay pairs is getting violated due to changes in fault current level. Thus, coordination between primary and backup relays fails in the presence of distributed Generation. Hence, the interconnection of DG in the distribution system causes an adverse impact on protection coordination. Relay coordination problem has many constraints due to coordination criteria. Heuristic based optimization techniques are used to solve the optimization problems. These techniques have a drawback of converging to the values that may not be optimum due to the wide range of design variables and difficulty in getting an initial feasible solution with a short range of design variables. This paper presents a new algorithm to overcome the problem of the initial feasible solution in determining the optimum settings of OCRs. In this context, the optimization problem is formulated as constrained non-linear optimization problem and is determining using Genetic Algorithm (GA). This algorithm is tested on two different networks that found suitable to give satisfactory results.
机译:分布式发电(DG)通常用于提供本地负载。分布式发电的渗透导致违反配电网络中的中继协调。 DG的互连会影响配电系统保护的不协调性,因为发电机能够将较大的故障电流贡献给故障点。 DG对继电器协调的影响会影响继电器的工作时间。由于故障电流水平的变化,与主要和备用继电器对相关联的CTI被违反。因此,在存在分布式发电时,主中继和备用中继之间的协调会失败。因此,配电系统中DG的互连会对保护协调产生不利影响。中继协调问题由于协调标准而具有许多约束。基于启发式的优化技术用于解决优化问题。这些技术的缺点是,由于设计变量的范围广,收敛到可能不是最佳值,并且难以获得设计变量范围短的初始可行解决方案。本文提出了一种新的算法来克服在确定OCR的最佳设置时最初可行的解决方案的问题。在这种情况下,将优化问题表述为约束非线性优化问题,并使用遗传算法(GA)进行确定。该算法已在两个合适的网络上进行了测试,可以得出令人满意的结果。

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