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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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 |
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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 |
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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 |
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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. |
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56402940200 |
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56402940200 Wali S.B. Hannan M.A. Ker P.J. Kiong T.S. |
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Conference Paper |
author |
Wali S.B. Hannan M.A. Ker P.J. Kiong T.S. |
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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 |
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13.214268 |