The Imperative of Holistic Optimization in Solar-PoweredSystems
Keywords:
Solar Energy, Integrated Optimization, Hybrid, Microgrid, AI-DrivenAbstract
Solar energy is considered to be the safest technology as regard green energy generation. This study assessed several techniques adopted for distributed iterative algorithm and intelligent control of distributed solar-hybrid microgrids. The study reviews the hybrid renewable system and multi-objective optimization, it also analyses machine learning and AI-driven forecasting by examining the complexity in energy system optimization. This paper explains the integration into existing Infrastructure and dual-use approaches as it integrate solar energy into building envelopes like windows. Solar energy storage and integration were explained alongside with hybridization and System Compatibility. This study further narrates how smart technologies are used for optimization especially with AI-driven forecasting and demand response. Findings reveal that microgrids provide communities or industries with a reliable energy source by combining battery storage. The study concludes that artificial intelligence (AI) is highly efficient in advancing basic development in contemporary microgrid technology.
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