An effective optimization method for solving the relay coordination problem of the microgrids

Abstract

In this work, an opposition-based learning-aggrandized class topper optimization (OBL-ACTO) algorithm is proposed to optimize the operating time of directional overcurrent relays (DOCRs) for an integrated microgrid power distribution network. The proposed OBL-ACTO algorithm is a hybridized method. In this method, an opposition-based learning (OBL) strategy is employed to tackle the local sticking problem of the traditional ACTO method and ameliorate its exploration and exploitation capability. The effectiveness of OBL-ACTO in solving the optimum coordination problem of (DOCRs) is tested on the IEC microgrid system and the 33kv distribution part of a standard IEEE 30-bus system. The proposed method along with the system is executed on the LabVIEW©2015 platform. The effectiveness of the developed method is shown based on the acquired optimal solution by comparing it with recently developed optimization methods for DOCRs problem. The proposed approach reduces the total operating time by 22.827 to 73.819 % to the compared methods. In addition, a non-parametric statistical hypothesis test is performed to show the proposed method’s significance based on the obtained simulation results.