relation: https://khub.utp.edu.my/scholars/18586/
title: An Enhanced Multi-Objective Optimizer for Stochastic Generation Optimization in Islanded Renewable Energy Microgrids
creator: Lakhina, U.
creator: Badruddin, N.
creator: Elamvazuthi, I.
creator: Jangra, A.
creator: Huy, T.H.B.
creator: Guerrero, J.M.
description: 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.
date: 2023
type: Article
type: PeerReviewed
identifier:   Lakhina, U. and Badruddin, N. and Elamvazuthi, I. and Jangra, A. and Huy, T.H.B. and Guerrero, J.M.  (2023) An Enhanced Multi-Objective Optimizer for Stochastic Generation Optimization in Islanded Renewable Energy Microgrids.  Mathematics, 11 (9).       
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159212645&doi=10.3390%2fmath11092079&partnerID=40&md5=9f298dbb932d02c04ee03487fdcd188b
relation: 10.3390/math11092079
identifier: 10.3390/math11092079