Review of AI-Based Modelling and Control Methods for Wind-PV-Battery Distributed Generation

PV and wind electricity are used in distributed generation (DG) systems for sustainability and decentralisation. Wind, solar, and battery systems can provide energy storage and complementary generating profiles. Renewable resources are unpredictable, making modelling and controlling difficult and limiting performance. Traditional prediction, optimisation, and control methods are inferior to AI. This critical analysis examines AI-based modelling and control methods for small scale wind-photovoltaic battery distributed generating systems. This paper objectively evaluates AI approaches strengths and weaknesses and discusses their practical applications in energy flow optimisation and renewable resource variability. Oversight is necessary for those implementing AI solutions and researchers making breakthroughs. The evidence presented here demonstrates that artificial intelligence can potentially improve distributed energy systems' efficiency, dependability, and sustainability.