Machine Learning-Driven Multi-Objective Energy Management and Optimal Power Flow of Grid-Connected Photovoltaic–Battery Energy Storage Systems for Enhanced Grid Resilience and Renewable Energy Integration
Findings imply that utilities, renewable-energy developers, and grid operators can strengthen resilient renewable-energy integration by coordinating predictive intelligence, multi-objective optimization, intelligent storage control, and network-aware power-flow management as an integrated operational architecture rathe...