AUTHOR=Yao Kun , Wang Ying , Fan Shuangshuang , Wan Jie , Wu Henggang , Cao Yong TITLE=Fault mechanisms and diagnosis methods for typical load mutation problems of turbo-generator sets JOURNAL=Frontiers in Energy Research VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.981598 DOI=10.3389/fenrg.2022.981598 ISSN=2296-598X ABSTRACT=

Since flexible peak shaving has been implemented in a growing number of high-power turbo-generator sets in the power grid owing to increasing demand, the load control performance of steam turbines directly affects the safety and efficiency of the unit operation. Load-following issues, especially load mutation, weaken the frequency control performance of the unit and cause load fluctuation faults, threatening power grid safety and stability. However, the definition, classification, characterization, generation mechanism, and diagnostic methods for load mutation problems have not been systematically researched. Based on the operational data of various turbo-generator set cases, this study systematically assessed three typical load mutation problems; namely, the common fault of unreasonable parameter settings of the control system as well as new-found faults in the actuator hardware and electrical interference. Subsequently, the fault mechanisms and characterization parameters of the different set capacities were analyzed and extracted. Furthermore, a diagnosis method was designed according to the actual problem, based on which fault type was identified. Case analysis of typical sets demonstrated that this method can quickly test and diagnose faults when in actual real-world scenarios and effectively determine the cause of the fault. This method can also detect the initial fault features, which is convenient for daily maintenance and avoids fault aggravation.