Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions

• 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
• Subjects: 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.