Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions
This study explores the integration of photovoltaic (PV) systems with battery storage for sustainable energy solutions. Employing the Backtracking Search Algorithm (BSA), the research optimizes PI controller parameters to enhance system efficiency and reliability. Real-world energy demand and weathe...
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my.uniten.dspace-344322024-10-14T11:19:45Z Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions Abdolrasol M.G.M. Jern Ker P. Hannan M.A. Tiong S.K. Ayob A. Almadani J.F.S. 35796848700 57220589801 7103014445 15128307800 26666566900 58902945600 Backtracking Search Algorithm (BSA) modulation index control optimization algorithms photovoltaic-Battery System Sustainable Energy Solutions Benchmarking Digital storage Electric batteries Energy conservation Learning algorithms Particle swarm optimization (PSO) Backtracking search algorithm Backtracking search algorithms Battery storage Modulation index control Modulation indexes Optimization algorithms Photovoltaic systems Photovoltaic/battery systems PI controller parameters Sustainable energy solutions MATLAB This study explores the integration of photovoltaic (PV) systems with battery storage for sustainable energy solutions. Employing the Backtracking Search Algorithm (BSA), the research optimizes PI controller parameters to enhance system efficiency and reliability. Real-world energy demand and weather data are integrated for practical relevance. Rigorous simulations within MATLAB/Simulink establish a robust analytical framework, evaluating optimization algorithms and identifying optimal configurations. By analysing objectives and simulation outcomes, the study provides insights for system refinement. The research strategically applies advanced algorithms to elevate PV-battery system performance and compares outcomes with Particle Swarm Optimization (PSO) and other studies, offering a comprehensive benchmark for evaluation. � 2023 IEEE. Final 2024-10-14T03:19:44Z 2024-10-14T03:19:44Z 2023 Conference Paper 10.1109/ETFG55873.2023.10408655 2-s2.0-85185766773 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185766773&doi=10.1109%2fETFG55873.2023.10408655&partnerID=40&md5=c173942367db3feaffb77f1f68526136 https://irepository.uniten.edu.my/handle/123456789/34432 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Backtracking Search Algorithm (BSA) modulation index control optimization algorithms photovoltaic-Battery System Sustainable Energy Solutions Benchmarking Digital storage Electric batteries Energy conservation Learning algorithms Particle swarm optimization (PSO) Backtracking search algorithm Backtracking search algorithms Battery storage Modulation index control Modulation indexes Optimization algorithms Photovoltaic systems Photovoltaic/battery systems PI controller parameters Sustainable energy solutions MATLAB |
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Backtracking Search Algorithm (BSA) modulation index control optimization algorithms photovoltaic-Battery System Sustainable Energy Solutions Benchmarking Digital storage Electric batteries Energy conservation Learning algorithms Particle swarm optimization (PSO) Backtracking search algorithm Backtracking search algorithms Battery storage Modulation index control Modulation indexes Optimization algorithms Photovoltaic systems Photovoltaic/battery systems PI controller parameters Sustainable energy solutions MATLAB Abdolrasol M.G.M. Jern Ker P. Hannan M.A. Tiong S.K. Ayob A. Almadani J.F.S. Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions |
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This study explores the integration of photovoltaic (PV) systems with battery storage for sustainable energy solutions. Employing the Backtracking Search Algorithm (BSA), the research optimizes PI controller parameters to enhance system efficiency and reliability. Real-world energy demand and weather data are integrated for practical relevance. Rigorous simulations within MATLAB/Simulink establish a robust analytical framework, evaluating optimization algorithms and identifying optimal configurations. By analysing objectives and simulation outcomes, the study provides insights for system refinement. The research strategically applies advanced algorithms to elevate PV-battery system performance and compares outcomes with Particle Swarm Optimization (PSO) and other studies, offering a comprehensive benchmark for evaluation. � 2023 IEEE. |
author2 |
35796848700 |
author_facet |
35796848700 Abdolrasol M.G.M. Jern Ker P. Hannan M.A. Tiong S.K. Ayob A. Almadani J.F.S. |
format |
Conference Paper |
author |
Abdolrasol M.G.M. Jern Ker P. Hannan M.A. Tiong S.K. Ayob A. Almadani J.F.S. |
author_sort |
Abdolrasol M.G.M. |
title |
Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions |
title_short |
Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions |
title_full |
Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions |
title_fullStr |
Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions |
title_full_unstemmed |
Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions |
title_sort |
optimized pv-battery systems using backtracking search algorithm for sustainable energy solutions |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2024 |
_version_ |
1814061180525740032 |