Application of Artificial Intelligence in Optimizing the Operation of Pumped Storage Plants

A pumped storage plant (PSP) is an indispensable facility for energy storage and grid regulation in the electrical power system (EPS), and its efficient and safe operation significantly impacts the stability and economy of the power grid. Modern PSP typically features intelligent equipment systems capable of real-time data collection and efficient data analysis, with integrated fault diagnosis, early warning, and efficient communication functions, providing a solid foundation for intelligent power station management and operation. Considering the crucial importance of accurately monitoring equipment status in PSP for safe and economical operation, artificial intelligence (AI) has become a key means to improve monitoring efficiency and accuracy. This article proposes an innovative AI-based monitoring system for PSP equipment status. The system utilizes deep learning (DL) algorithms to achieve autonomous learning and extraction of operating status features, enabling accurate performance evaluation and health status prediction of critical equipment. Experimental results show that the system not only significantly improves the accuracy of fault recognition but also shortens the response time of fault warning, effectively preventing potential safety risks.