Multi-Objective Optimization Based Approach for Optimal Allocation of Distributed Generation Considering Techno-Economic and Environmental Indices /

Abstract

This paper presents efficient, nature inspired ant lion optimization (ALO) and multiverse optimization (MVO) techniques for the optimal allocation of DGs in Active distribution networks (ADNs). The main objective is to improve techno-economic and environmental attributes while satisfying system’s constraints. In comparison to the ALO method, the MVO algorithm has the drawback of requiring a large number of iterations to reach an optimal solution. Various MCDM approaches are used in this study to determine the optimal trade-off among the available solutions. The effectiveness of the suggested ALO approach has been confirmed on the IEEE-33 and 69 bus ADNs, the obtained results were validated by comparing them to other methods in the literature. The test system results indicate that the developed algorithms produces the highest Loss reduction in the IEEE-33 and 69 bus systems as 94.43% and 97.16%, respectively, and the maximum VSI is 0.9805 p.u and 0.9937 p.u, respectively; however, the minimum VD and annual energy loss cost for the given test systems is 0.00019 p.u and $3353.3 which shows that the suggested method can produce higher quality results as compared to other methods presented in literature. As a result, the proposed ALO could be very effective, efficient and appealing solution to the OADG problem.