Piecewise Causality Study between Power Load and Vibration in Hydro-Turbine Generator Unit for a Low-Carbon Era

Lianda Duan, Dekuan Wang, Guiping Wang, Changlin Han, Weijun Zhang, Xiaobo Liu, Cong Wang, Zheng Che and Chang Chen
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Lianda Duan: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Dekuan Wang: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Guiping Wang: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Changlin Han: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Weijun Zhang: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Xiaobo Liu: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Cong Wang: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Zheng Che: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Chang Chen: China Institute of Water Resources and Hydropower Research, Beijing 100038, China

Energies, 2022, vol. 15, issue 3, 1-13

Abstract: With the rapid development of wind and photovoltaic power generation, hydro-turbine generator units have to operate in a challenging way, resulting in obvious vibration problems. Because of the significant impact of vibration on safety and economical operation, it is of great significance to study the causal relationship between vibration and other variables. The complexity of the hydro-turbine generator unit makes it difficult to analyze the causality of the mechanism. This paper studied the correlation based on a data-driven method, then transformed the correlation into causality based on the mechanism. In terms of correlation, traditional research only judges whether there is a correlation between all data. When the data with correlation are interfered with by the data without correlation, the traditional methods cannot accurately identify the correlation. A piecewise correlation method based on change point detection was proposed to fill this research gap. The proposed method segmented time series pairs, then analyzed the correlation between subsequences. The causality between power load and vibration of a hydro-turbine generator unit was further analyzed. It indicated that when the power load is less than 200 MW, the causality is weak, and when the power load is greater than 375 MW, the causality is strong. The results show that the causality between vibration and power load is not fixed but piecewise. Furthermore, the piecewise correlation method compensated for the limitation of high variance of the maximum information coefficient.

Keywords: high proportional renewable power system; active power; change point detection; maximum information coefficient; cosine similarity; anomaly detection (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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