Intelligent Micro-Cogeneration Systems for Residential Grids: A Sustainable Solution for Efficient Energy Management

This paper presents an optimization approach for Micro-cogeneration systems with internal combustion engines integrated into residential grids, addressing power demand failures caused by intermittent renewable energy sources. The proposed method leverages machine learning techniques, control strategies, and grid data to improve system flexibility efficiency in meeting electricity domestic hot water demands. Historical were analysed develop a learning-based prediction model water. Thermal storage was the enhance flexibility. An created, considering efficiency, emissions, cost while adapting real-time changes. A strategy designed flexible operation of system, excess thermal resource allocation. solution’s effectiveness validated through simulations, results demonstrating system’s ability efficiently address high periods mitigating from research novel potential significantly resilience, integration contributing more sustainable reliable systems.