Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System

Recent advances in electric grid technology have led to sustainable, modern, decentralized, bidirectional microgrids (MGs). The MGs can support energy storage, renewable energy sources (RESs), power electronics converters, and energy management systems. The MG system is less costly and creates less...

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Main Authors: Ali M. Jasim, Basil H. Jasim, Florin-Constantin Baiceanu, Bogdan-Constantin Neagu
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/11/5/1248
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author Ali M. Jasim
Basil H. Jasim
Florin-Constantin Baiceanu
Bogdan-Constantin Neagu
author_facet Ali M. Jasim
Basil H. Jasim
Florin-Constantin Baiceanu
Bogdan-Constantin Neagu
author_sort Ali M. Jasim
collection DOAJ
description Recent advances in electric grid technology have led to sustainable, modern, decentralized, bidirectional microgrids (MGs). The MGs can support energy storage, renewable energy sources (RESs), power electronics converters, and energy management systems. The MG system is less costly and creates less CO<sub>2</sub> than traditional power systems, which have significant operational and fuel expenses. In this paper, the proposed hybrid MG adopts renewable energies, including solar photovoltaic (PV), wind turbines (WT), biomass gasifiers (biogasifier), batteries’ storage energies, and a backup diesel generator. The energy management system of the adopted MG resources is intended to satisfy the load demand of Basra, a city in southern Iraq, considering the city’s real climate and demand data. For optimal sizing of the proposed MG components, a meta-heuristic optimization algorithm (Hybrid Grey Wolf with Cuckoo Search Optimization (GWCSO)) is applied. The simulation results are compared with those achieved using Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Grey Wolf Optimization (GWO), Cuckoo Search Optimization (CSO), and Antlion Optimization (ALO) to evaluate the optimal sizing results with minimum costs. Since the adopted GWCSO has the lowest deviation, it is more robust than the other algorithms, and their optimal number of component units, annual cost, and Levelized Cost Of Energy (LCOE) are superior to the other ones. According to the optimal annual analysis, LCOE is 0.1192 and the overall system will cost about USD 2.6918 billion.
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spelling doaj.art-d33ed21aee7042a2b0d1277570707fc52023-11-17T08:10:15ZengMDPI AGMathematics2227-73902023-03-01115124810.3390/math11051248Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid SystemAli M. Jasim0Basil H. Jasim1Florin-Constantin Baiceanu2Bogdan-Constantin Neagu3Electrical Engineering Department, University of Basra, Basra 61001, IraqElectrical Engineering Department, University of Basra, Basra 61001, IraqPower Engineering Department, Gheorghe Asachi Technical University of Iasi, 700050 Iasi, RomaniaPower Engineering Department, Gheorghe Asachi Technical University of Iasi, 700050 Iasi, RomaniaRecent advances in electric grid technology have led to sustainable, modern, decentralized, bidirectional microgrids (MGs). The MGs can support energy storage, renewable energy sources (RESs), power electronics converters, and energy management systems. The MG system is less costly and creates less CO<sub>2</sub> than traditional power systems, which have significant operational and fuel expenses. In this paper, the proposed hybrid MG adopts renewable energies, including solar photovoltaic (PV), wind turbines (WT), biomass gasifiers (biogasifier), batteries’ storage energies, and a backup diesel generator. The energy management system of the adopted MG resources is intended to satisfy the load demand of Basra, a city in southern Iraq, considering the city’s real climate and demand data. For optimal sizing of the proposed MG components, a meta-heuristic optimization algorithm (Hybrid Grey Wolf with Cuckoo Search Optimization (GWCSO)) is applied. The simulation results are compared with those achieved using Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Grey Wolf Optimization (GWO), Cuckoo Search Optimization (CSO), and Antlion Optimization (ALO) to evaluate the optimal sizing results with minimum costs. Since the adopted GWCSO has the lowest deviation, it is more robust than the other algorithms, and their optimal number of component units, annual cost, and Levelized Cost Of Energy (LCOE) are superior to the other ones. According to the optimal annual analysis, LCOE is 0.1192 and the overall system will cost about USD 2.6918 billion.https://www.mdpi.com/2227-7390/11/5/1248islanded microgridenergy management systemrenewable energy sourcesgrey wolf optimizationcuckoo searchoptimal sizing
spellingShingle Ali M. Jasim
Basil H. Jasim
Florin-Constantin Baiceanu
Bogdan-Constantin Neagu
Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System
Mathematics
islanded microgrid
energy management system
renewable energy sources
grey wolf optimization
cuckoo search
optimal sizing
title Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System
title_full Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System
title_fullStr Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System
title_full_unstemmed Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System
title_short Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System
title_sort optimized sizing of energy management system for off grid hybrid solar wind battery biogasifier diesel microgrid system
topic islanded microgrid
energy management system
renewable energy sources
grey wolf optimization
cuckoo search
optimal sizing
url https://www.mdpi.com/2227-7390/11/5/1248
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