%0 Journal Article
%A Lakhina, U.
%A Badruddin, N.
%A Elamvazuthi, I.
%A Jangra, A.
%A Huy, T.H.B.
%A Guerrero, J.M.
%D 2023
%F scholars:18586
%J Mathematics
%N 9
%R 10.3390/math11092079
%T An Enhanced Multi-Objective Optimizer for Stochastic Generation Optimization in Islanded Renewable Energy Microgrids
%U https://khub.utp.edu.my/scholars/18586/
%V 11
%X A microgrid is an autonomous electrical system that consists of renewable energy and efficiently achieves power balance in a network. The complexity in the distribution network arises due to the intermittent nature of renewable generation units and varying power. One of the important objectives of a microgrid is to perform energy management based on situational awareness and solve an optimization problem. This paper proposes an enhanced multi-objective multi-verse optimizer algorithm (MOMVO) for stochastic generation power optimization in a renewable energy-based islanded microgrid framework. The proposed algorithm is utilized for optimum power scheduling among various available generation sources to minimize the microgrid�s generation costs and power losses. The performance of MOMVO is assessed on a 6-unit and 10-unit test system. Simulation results show that the proposed algorithm outperforms other metaheuristic algorithms for multi-objective optimization. © 2023 by the authors.
%Z cited By 2