In this paper, the optimum coordination of over current relay in distribution system has been performed. The time dial setting (TDS) of over current relay is optimized by minimizing total operating time of relays. As the power system is a complex and highly interconnected, the complexity may be occurred in calculating optimum relay coordination time (TDS, phase setting etc.) by conventional or analytical methods. Therefore, an opposition learning-based gravitational search algorithm (OLGSA) is proposed for relay coordination optimization problem. The proposed optimization method can search the optimum solution for relay coordination problem from both the direction (initial populations and their opposite direction populations) in search space to reach global solution as early as possible. Three different distribution power systems are considered to verify the performance of the proposed algorithm for optimum relay coordination problem. The simulation results for all three cases have been compared with existing results. The outcome of the proposed method for relay coordination problem shows that the total relay operating time is minimized (20–40 % improvement in relay total operating time for different cases) comparably than available results for all three cases by maintaining coordinations among relays and satisfying different constraints.

本文对配电系统中的过电流继电器进行了优化协调。通过最小化继电器的总运行时间，可以优化过电流继电器的时间刻度设置（TDS）。由于电力系统是复杂且高度互连的，因此在通过常规或分析方法计算最佳继电器协调时间（TDS，相位设置等）时可能会出现复杂性。因此，针对中继协调优化问题，提出了一种基于对立学习的重力搜索算法。所提出的优化方法可以从搜索空间中的两个方向（初始种群及其相反的种群）中寻找中继协调问题的最优解，以尽早达到全局解。考虑了三种不同的配电系统，以验证所提出算法的最优继电器协调问题的性能。将这三种情况的仿真结果与现有结果进行了比较。所提出的继电器协调问题方法的结果表明，通过保持继电器之间的协调并满足不同的要求，与三种情况下的可用结果相比，总继电器工作时间得以最小化（不同情况下继电器总工作时间缩短了20％至40％）。约束。