数据驱动下基于方差核分解的电压稳定裕度全局灵敏度在线计算

doi:10.19595/j.cnki.1000-6753.tces.260369

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摘要

随着新能源电网负荷以及电力电子设备规模增加,电力系统受端电压稳定性面临严峻挑战,快速、准确评估影响电压稳定裕度的关键因素,对于保障互联系统安全稳定运行至关重要。本文从理论上证明了联络线传输功率分配对系统电压稳定裕度的影响,并揭示了不同联络线功率调整对电压稳定裕度的灵敏度差异。在此基础上,提出了一种数据驱动的新能源电力系统联络线功率-电压稳定裕度全局灵敏度在线计算方法。所提方法利用前期研究在线评估系统电压稳定裕度,并结合负荷及新能源随机出力下实时采集的联络线有功功率量测数据,构建基于方差核分解（variance-based kernel decomposition,VKD）的全局灵敏度计算模型,解析联络线功率与电压稳定裕度间的非线性关系。该方法在系统正常运行工况下,通过获取少量的量测数据,便可快速、准确地辨识影响系统电压稳定裕度的关键联络线功率。通过北欧测试系统、中国电科院标准算例以及实际系统的仿真分析,验证了所提方法的准确性、鲁棒性及在线应用能力。

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	高晗
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关键词 ：电压稳定裕度, 联络线传输功率, 方差核分解, 全局灵敏度, 新能源电力系统

Abstract：

As the load and the scale of power electronic devices increase in renewable energy power systems, the voltage stability of the receiving-end system faces significant challenges. Rapid and accurate assessment of key factors influencing voltage stability margin (VSM) is crucial for ensuring the safe and stable operation of interconnected systems. This paper theoretically demonstrates the impact of tie-line power distribution on the system’s VSM and reveals the sensitivity differences of VSM under different tie-line power adjustment schemes. Based on this demonstration, a data-driven online global sensitivity calculation method for tie-line power and VSM in renewable power systems is proposed. The proposed method leverages prior research for online evaluation of system VSM and combines real-time measurements of tie-line active power under stochastic load and renewable generation to construct a Variance-based Kernel Decomposition (VKD) model for global sensitivity analysis, thereby capturing the nonlinear relationship between tie-line power and VSM. Under normal operating conditions, the method can quickly and accurately identify the key tie-line powers affecting system VSM with only a small amount of measurement data. Simulation studies on the Nordic 32 test system, the China Electric Power Research Institute voltage stability standard case (CSEE-VS), and a real-world power system validate the accuracy, robustness, and online applicability of the proposed approach.
Firstly, the explicit analytical linkage between tie-line active power variations and the VSM of the system is rigorously derived, elucidating the underlying physical mechanisms and uncovering diverse sensitivity characteristics across different tie-line active power adjustments. Then, a global sensitivity calculation method for VSM based on variance-based kernel decomposition (VKD) is developed, enabling accurate and efficient quantification of the nonlinear influence of tie-line active power on the VSM. To mitigate the stochastic fluctuations introduced by simultaneous load and renewable disturbances, a sliding window-based online analysis framework is introduced, which effectively suppresses randomness-induced errors and ensures reliable sensitivity assessment.
Simulation results demonstrate that compared to traditional methods, the proposed VKD-based global sensitivity calculation method calculates sensitivity directly through kernel function expansion. This approach significantly improves the computational efficiency of global sensitivity while ensuring accurate identification of the critical tie-lines affecting VSM. Specifically, the proposed method completes the entire online sensitivity calculation within 0.7 seconds on average (including 0.37 s for VSM estimation). Furthermore, compared with the Monte Carlo-based Sobol’ method (maximum error 0.57) and the traditional linear sensitivity analysis (maximum error 0.85), the proposed method achieves a maximum error of only 0.14 under varying renewable penetration levels.
The following conclusions can be drawn from the simulation analysis: (1) Under a fixed inter-area transmission power, the system VSM is significantly influenced by the distribution of tie-line power, and the degree of influence varies distinctly among different tie-lines, offering a new perspective for the safe and stable operation of power systems. (2) The proposed ambient data-driven global sensitivity calculation method accurately reflects the relationship between system tie-line active power and VSM by comprehensively considering the interactions between system uncertainties and stochastic fluctuation characteristics, thereby effectively identifying the critical tie-line powers that influence system VSM. (3) The accuracy, robustness, and online computational capability of the proposed online analysis method for VSM global sensitivity have been validated using the Nordic test system, CSEE-VS standard case and real-world power system, demonstrating considerable practical engineering utility.

Key words： Voltage stability margin transmission power of tie-line variance-based kernel decomposition global sensitivity power system with high renewables

收稿日期: 2026-03-12

PACS:

TM712

基金资助:

现代电力系统仿真控制与绿色电能新技术教育部重点实验室（东北电力大学）开放课题资助项目（MPSS2025-03）

通讯作者: 高晗女,1995年生,副教授,研究方向规模化新能源并网系统稳定性分析与控制研究。E-mail：hannahgh@hrbust.edu.cn

作者简介: 杨德友男,1983年生,教授,博士生导师,研究方向为随机数据驱动的电力系统小干扰稳定分析与阻尼调控等。E-mail：dyyang@hrbust.edu.cn

引用本文:

高晗, 杨德友, 王丽馨. 数据驱动下基于方差核分解的电压稳定裕度全局灵敏度在线计算[J]. 电工技术学报, 0, (): 369-. Gao Han, Yang Deyou, Wang Lixin. Online Calculation of Data-Driven Global Sensitivity for Voltage Stability Margin Based on Variance-Based Kernel Decomposition. Transactions of China Electrotechnical Society, 0, (): 369-.

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