Research on the Health Evaluation of a Pump Turbine in Smoothing Output Volatility of the Hybrid System Under a High Proportion of Wind and Photovoltaic Power Connection

Yan Ren (), Haonan Zhang, Lile Wu (), Kai Zhang, Zutian Cheng, Ketao Sun, Yuan Sun and Leiming Hu
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Yan Ren: School of Electrical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Haonan Zhang: School of Energy and Power Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Lile Wu: School of Electrical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Kai Zhang: Henan Rural Industry Development Service Center, Zhengzhou 450002, China
Zutian Cheng: Power China Henan Electric Power Survey & Design Institute Co., Ltd., Zhengzhou 450007, China
Ketao Sun: School of Energy and Power Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Yuan Sun: Hunan Heimifeng Pumped Storage Co., Ltd., Changsha 410219, China
Leiming Hu: Jiangxi Hongping Pumped Storage Co., Ltd., Yichun 330603, China

Energies, 2025, vol. 18, issue 5, 1-30

Abstract: With the high proportion of wind and photovoltaic (PV) power connection in the new electricity system, the system output power volatility is enhanced. When the output fluctuation of the system is suppressed, the pumped storage condition is changed frequently, which leads to the vibration enhancement of the unit and a decrease in the system safety. This paper proposes a pump turbine health evaluation model based on the combination of a weighting method and cloud model in a high proportion wind and PV power connection scenario. The wind–PV output characteristics of the complementary system in a year (8760 h) and a typical week in four seasons (168 h) are analyzed, and the characteristics of frequent working condition transitions of pumped storage units are studied against this background. A five-level health classification system including multi-dimensional evaluation indicators is established, and a multi-level health evaluation based on cloud membership quantification is realized by combining the weighting method and cloud model method. The case analysis of a pumped storage power station within a new electricity system shows that the system as a whole presents typical cloud characteristics (Ex = 76.411, En = 12.071, He = 4.014), and the membership degree in the “good” state reaches 0.772. However, the draft tube index (Ex = 62.476) and the water guide index (Ex = 50.333) have shown a deterioration trend. The results verify the applicability and reliability of the evaluation model. This study provides strong support for the safe and stable operation of pumped storage units in the context of the high-proportion wind and PV power connection, which is of great significance for the smooth operation of the new electricity system.

Keywords: new electricity system; pump turbine; health evaluation; cloud model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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