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Systematic review analyzes optimization in solar and hybrid systems, suggesting pathways for sustainable development.
The rapid growth of renewable energy systems necessitates advanced optimization and intelligent control strategies to enhance efficiency, reliability, and sustainability. This systematic review analyses 23 research and review articles published between 2020 and 2024 focusing on solar photovoltaic (PV) systems, hybrid renewable systems, performance optimization, parameter tuning, multi-objective optimization, and intelligent methodologies. The review categorizes studies based on system configuration, optimization approach, and application objective. Results indicate a clear shift from conventional parameter tuning toward multi-objective evolutionary algorithms, AI-assisted modelling, and hybrid system integration. The study highlights research gaps in real-time adaptive optimization, integrated AI-BMS frameworks, and sustainability-driven design. The findings align with the conference theme by demonstrating how merging computational intelligence with renewable technologies drives sustainable energy development.
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Patil et al. (2026) studied this question.
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