Design and optimization of power grid intelligent operation and maintenance system based on blockchain and industrial IoT: a case study of State Grid Information & Telecommunication Co., Ltd.

This paper presents a Blockchain and Industrial IoT-Enhanced Deep Reinforcement Learning (BI-DRL) algorithm designed to optimize the operation and maintenance (O&M) of power grids. By integrating blockchain with IIoT and deep reinforcement learning, BI-DRL addresses the challenges of data security, decentralized decision-making, and fault prediction in power grid systems. Experiments demonstrate that BI-DRL significantly improves fault detection accuracy, response time, energy efficiency, and computational overhead compared to conventional approaches. A case study with State Grid Information & Telecommunication Co., Ltd. further validates the practical benefits of the proposed method. This research highlights the potential of BI-DRL in advancing power grid management through intelligent, scalable solutions.