Intelligent protection systems for grid-connected renewables: A review of AI techniques and applications

The integration of renewable energy sources (RES) like solar photovoltaics, wind turbines, and hybrid storage into contemporary power systems presents notable challenges for protection, stemming from their intermittent generation, inverter-based interfaces, and bidirectional power flows. Traditional protection schemes, initially developed for predictable and unidirectional grids, are increasingly inadequate for managing complexities and therefore there is urgent requirement for Artificial Intelligence (AI) techniques that provide adaptability, speed, and resilience in dynamic and uncertain operating conditions. This review critically examines the role of AI in enhancing grid protection, focusing on fault detection, isolation, classification, adaptive relay coordination, islanding detection, and the mitigation of cyber-physical threats. This study synthesizes several research works by categorizing AI methodologies such as machine learning, deep learning, fuzzy logic, reinforcement learning, and hybrid models, while also benchmarking their comparative performance and practical applicability. The methodology entails a systematic examination of simulation studies, pilot projects, and restricted real-world implementations, offering a comprehensive assessment of existing capabilities and constraints. Research indicates that AI-driven protection systems can reduce detection time to less than 100 ms, decrease false trips, and enhance resilience to varying grid conditions. However, challenges remain, including data scarcity, insufficient field validation, issues with interpretability, and the absence of standardized evaluation frameworks. The review concludes by outlining future research directions, highlighting field trials, cost-effective deployment strategies, explainable AI, and alignment with IEC/IEEE protection standards. This work provides a synthesis and roadmap for the advancement of intelligent, reliable, and certifiable protection systems within renewable-integrated smart grids.