Hybrid renewable systems, which combine two or more sources with energy storage, offer promising solutions to enhance reliability, cost-efficiency, and environmental sustainability. Hybrid Solar Energy Systems, Energy Management Optimization, Reinforcement Learning (RL), Fuzzy Logic Control, Smart Grid Integration This paper presents a comprehensive energy management mechanism for hybrid solar systems from different aspects of solar energy generation, battery storage, and grid. This research proposes a novel AI-enhanced hybrid solar energy framework integrating spatio-temporal forecasting, adaptive control, and decentralized energy trading. The core objective is to improve the efficiency, responsiveness, and scalability of solar power generation using a unified. Hybrid Renewable Energy Systems (HRES), which blend solar, wind, and battery storage, present an effective alternative. However, achieving optimal performance requires intelligent management. Additionally, emerging technologies such as AI for forecasting and optimization, smart EMS, and new policy models are.
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