Review demonstrates the efficacy of IoT and machine learning in managing distributed renewable energy storage and generation, highlighting enhanced predictive maintenance and fault detection.
Renewable energy generation and storage have become increasingly important in recent years, in line with the transition to cleaner and more sustainable energy. Efficient management of renewable energy systems is vital for their reliable operation, and this entails gathering and analysing data from sensors to detect and address potential system faults. The combination of the Internet of Things (IoT) and Machine Learning (ML) has emerged as a promising solution to improve the management of renewable energy generation and storage systems. IoT facilitates the integration of numerous sensors and devices, while ML provides advanced data analytics for predictive maintenance and fault detection. In this comprehensive article, we review the current state of renewable energy generation and storage management systems, including many important studies not present in existing surveys. This review emphasises the importance of reliable management in securing a greener future.
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Naha et al. (2026) studied this question.
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