Optimal Sizing of PV-Battery based Hybrid Renewable System using Particle Swarm Optimization for Economic Sustainability

Integrating energy storage (ES) such as batteries with renewable sources like photovoltaic (PV) systems offers eco-friendly power generation, but optimizing the scale of hybrid renewable systems (HRSs) is complex due to PV intermittency, discharge uncertainty, and economic factors. The article has p...

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Main Authors: Wali S.B., Hannan M.A., Ker P.J., Kiong T.S.
Other Authors: 56402940200
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2024
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spelling my.uniten.dspace-344182024-10-14T11:19:39Z Optimal Sizing of PV-Battery based Hybrid Renewable System using Particle Swarm Optimization for Economic Sustainability Wali S.B. Hannan M.A. Ker P.J. Kiong T.S. 56402940200 7103014445 37461740800 57216824752 Energy storage hybrid renewable system levelized cost of energy particle swarm optimization Renewable energy sources Cost effectiveness Digital storage Energy storage Iterative methods Particle size analysis Particle swarm optimization (PSO) Renewable energy Secondary batteries Sustainable development Cost of energies Economic sustainability Hybrid renewable system Levelized cost of energy Levelized costs Particle swarm Particle swarm optimization Photovoltaics Renewable energy source Swarm optimization MATLAB Integrating energy storage (ES) such as batteries with renewable sources like photovoltaic (PV) systems offers eco-friendly power generation, but optimizing the scale of hybrid renewable systems (HRSs) is complex due to PV intermittency, discharge uncertainty, and economic factors. The article has proposed an optimal solution for a small-scale PV-battery-based hybrid renewable system aimed at improving economic sustainability using particle swarm optimization (PSO). The main objective is to minimize the levelized cost of energy (LCOE) while finding the optimal PV and battery sizes. By conducting simulations and analyses using MATLAB, the findings vividly illustrate the significant influence of PSO in reducing the overall LOCE of 80.36%. Through iterative exploration and optimization of PV capacity, battery capacity, and power rating, the PSO algorithm achieves an optimal configuration, minimizing costs while meeting energy demands. The optimal configuration includes a 3.3kW of PV and a one kWh battery with an NPC of $24,974.29 and an LCOE of 0.011 $/kWh. The system has a renewable fraction (RF) of 100% with no CO2 emission. The PSO-driven method, based on real-world data on power demand, PV generation, and EV charging, demonstrates its novel impact on renewable energy system design, accelerating the transition to greener and more cost-effective energy solutions � 2023 IEEE. Final 2024-10-14T03:19:38Z 2024-10-14T03:19:38Z 2023 Conference Paper 10.1109/ETFG55873.2023.10408314 2-s2.0-85185787323 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185787323&doi=10.1109%2fETFG55873.2023.10408314&partnerID=40&md5=cbe1e74ef5916867dcc98714403992dd https://irepository.uniten.edu.my/handle/123456789/34418 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Energy storage
hybrid renewable system
levelized cost of energy
particle swarm optimization
Renewable energy sources
Cost effectiveness
Digital storage
Energy storage
Iterative methods
Particle size analysis
Particle swarm optimization (PSO)
Renewable energy
Secondary batteries
Sustainable development
Cost of energies
Economic sustainability
Hybrid renewable system
Levelized cost of energy
Levelized costs
Particle swarm
Particle swarm optimization
Photovoltaics
Renewable energy source
Swarm optimization
MATLAB
spellingShingle Energy storage
hybrid renewable system
levelized cost of energy
particle swarm optimization
Renewable energy sources
Cost effectiveness
Digital storage
Energy storage
Iterative methods
Particle size analysis
Particle swarm optimization (PSO)
Renewable energy
Secondary batteries
Sustainable development
Cost of energies
Economic sustainability
Hybrid renewable system
Levelized cost of energy
Levelized costs
Particle swarm
Particle swarm optimization
Photovoltaics
Renewable energy source
Swarm optimization
MATLAB
Wali S.B.
Hannan M.A.
Ker P.J.
Kiong T.S.
Optimal Sizing of PV-Battery based Hybrid Renewable System using Particle Swarm Optimization for Economic Sustainability
description Integrating energy storage (ES) such as batteries with renewable sources like photovoltaic (PV) systems offers eco-friendly power generation, but optimizing the scale of hybrid renewable systems (HRSs) is complex due to PV intermittency, discharge uncertainty, and economic factors. The article has proposed an optimal solution for a small-scale PV-battery-based hybrid renewable system aimed at improving economic sustainability using particle swarm optimization (PSO). The main objective is to minimize the levelized cost of energy (LCOE) while finding the optimal PV and battery sizes. By conducting simulations and analyses using MATLAB, the findings vividly illustrate the significant influence of PSO in reducing the overall LOCE of 80.36%. Through iterative exploration and optimization of PV capacity, battery capacity, and power rating, the PSO algorithm achieves an optimal configuration, minimizing costs while meeting energy demands. The optimal configuration includes a 3.3kW of PV and a one kWh battery with an NPC of $24,974.29 and an LCOE of 0.011 $/kWh. The system has a renewable fraction (RF) of 100% with no CO2 emission. The PSO-driven method, based on real-world data on power demand, PV generation, and EV charging, demonstrates its novel impact on renewable energy system design, accelerating the transition to greener and more cost-effective energy solutions � 2023 IEEE.
author2 56402940200
author_facet 56402940200
Wali S.B.
Hannan M.A.
Ker P.J.
Kiong T.S.
format Conference Paper
author Wali S.B.
Hannan M.A.
Ker P.J.
Kiong T.S.
author_sort Wali S.B.
title Optimal Sizing of PV-Battery based Hybrid Renewable System using Particle Swarm Optimization for Economic Sustainability
title_short Optimal Sizing of PV-Battery based Hybrid Renewable System using Particle Swarm Optimization for Economic Sustainability
title_full Optimal Sizing of PV-Battery based Hybrid Renewable System using Particle Swarm Optimization for Economic Sustainability
title_fullStr Optimal Sizing of PV-Battery based Hybrid Renewable System using Particle Swarm Optimization for Economic Sustainability
title_full_unstemmed Optimal Sizing of PV-Battery based Hybrid Renewable System using Particle Swarm Optimization for Economic Sustainability
title_sort optimal sizing of pv-battery based hybrid renewable system using particle swarm optimization for economic sustainability
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2024
_version_ 1814061179736162304
score 13.214268