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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Main Authors: Abdolrasol M.G.M., Jern Ker P., Hannan M.A., Tiong S.K., Ayob A., Almadani J.F.S.
Other Authors: 35796848700
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2024
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spelling 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
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 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
spellingShingle 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
description 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
score 13.209306