Research on the Reliability Improvement Technology of Important Auxiliary Machines of Thermal Power Units Based on Deep Peaking

During the deep peaking, the important auxiliary machines of thermal power units operate in unconventional zones, and which seriously lack operational stability. This paper designs a reliability enhancement system for important auxiliary machines through data mining, artificial intelligence algorithms and adaptive control technology. The system can realize fault warning and fault self-healing under low load, and maintain the stability of main parameters of units. After testing and application verification, this technology can effectively improve the reliability of important auxiliary machines under deep peaking and reduce the invisible power generation loss. It can improve the economic efficiency of thermal power units and provide a reference for similar projects.