Correlating analysis and optimization between hydropower system parameters and multi-frequency oscillation characteristics

Xueding Lu, Chaoshun Li, Dong Liu, He Wang, Zhiwei Zhu, Xiaoqiang Ta and Rongli Xu

Energy, 2024, vol. 304, issue C

Abstract: This paper aims to study the relationship between multi-frequency oscillation characteristics and parameters of hydro-turbine governing systems (HTGS), as well as improve the system oscillation quantification accuracy and primary frequency regulation performance. Firstly, an HTGS model with multi-frequency oscillation characteristics is established using an actual hydropower system as the object. Then, system oscillation components and the sources of each oscillating link are identified using eigenvalue and correlation analysis. To address the issue that sub-wave interference with dominant oscillation quantization, we innovatively incorporate correlation and frequency indexes into quantification process, and the dominant oscillations of complex HTGS are accurately quantified. On this basis, the detailed partitioning of control parameters is established to obtain the guide graph quickly reflecting the relationship between control parameters and system oscillations. Finally, an integrated optimization strategy with ultra-low frequency oscillation (ULFO) safety and regulation performance constraints is constructed, and control parameters are further optimized under two typical parameter setting methods. The results indicate over 90 % of the stable parameters enable the system to enter ULFO mode, and optimized control parameters utilizing proposed strategy increase regulation speed by 46 % while effectively suppressing ULFO. This paper provides a powerful tool and novel ideas for complex HTGS oscillation analysis and parameter optimization.

Keywords: Multi-frequency oscillation; Oscillation accuracy quantification; Parameter correlation; ULFO security boundary; Parameter optimization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:304:y:2024:i:c:s0360544224015627

DOI: 10.1016/j.energy.2024.131789

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