
1.国网电力科学研究院有限公司(南瑞集团有限公司),江苏省南京市 211106
2.电网运行风险防御技术与装备全国重点实验室,江苏省南京市 211106
3.河海大学电气与动力工程学院,江苏省南京市 211100
Received:23 January 2025,
Revised:2026-03-03,
Online First:06 July 2026,
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吴小康,徐伟,薛峰.基于节点注入功率空间降维和几何驱动的高维静态安全域构建[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250123001.
WU Xiaokang,XU Wei,XUE Feng.Geometry-driven Construction of High-dimensional Static Security Region Based on Dimension Reduction of Node Injection Power Space[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250123001.
吴小康,徐伟,薛峰.基于节点注入功率空间降维和几何驱动的高维静态安全域构建[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250123001. DOI:
WU Xiaokang,XU Wei,XUE Feng.Geometry-driven Construction of High-dimensional Static Security Region Based on Dimension Reduction of Node Injection Power Space[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250123001. DOI:
电力系统静态安全域(SSR)是分析强不确定性高比例新能源电网静态安全性的重要工具。随着远距离跨区输电规模和新能源接入比例持续增长,节点注入功率空间维数急剧增加,SSR边界的非线性特征凸显。在高维空间中构建SSR,存在维数灾难和精度不高的问题。为此,提出基于注入功率空间降维和几何驱动的高维SSR构建方法。首先,采用球面
K
-means聚类算法将越限模式划分为不同的簇,并识别关键越限模式,计算不同节点注入功率对关键越限模式灵敏度向量的相关系数。通过对灵敏度接近的节点注入功率进行聚合,实现高维空间降维。然后,根据关键越限模式对应的超平面,构建包含SSR的初始多面体,并计算临界安全运行点及其对应的超平面,采用顶点削平算法确定精确的SSR边界。最后,基于包含新能源的改进IEEE 39节点算例和某省级电网进行验证,结果表明,所提的方法能够大幅提升凸SSR的计算效率和精度。
The static security region (SSR) is a critical tool for analyzing the static security of power systems with high penetration of renewable energy sources characterized by strong uncertainties. As the long-distance inter-regional transmission scale and the integration proportion of renewable energy continue to grow
the dimension of the node injection power space increases sharply
and the nonlinear characteristics of the SSR boundary becomes more pronounced. Constructing the SSR in high-dimensional space faces challenges of the dimension curse and limited accuracy. To address these issues
this paper proposes a geometry-driven construction method of high-dimensional SSR based on dimension reduction of node injection power space. First
the spherical
K
-means clustering algorithm is employed to classify the violation patterns into distinct clusters and identify critical violation patterns. The correlation coefficients of sensitivity vectors of the critical violation patterns to different node injection powers are calculated
enabling dimension reduction in the high-dimensional space by aggregating node injection powers with similar sensitivity. Subsequently
an initial polyhedron containing the SSR is constructed based on the hyperplanes corresponding to the key violation patterns. The critical secure operating points
along with their corresponding hyperplanes
are computed. A vertex clipping algorithm is then applied to determine the exact SSR boundary. Finally
verification is carried out based on a modified IEEE 39-bs system integrated with renewable energy and a specific provincial power grid. The results demonstrate that the proposed method can significantly improve the computational efficiency and accuracy of the convex SSR .
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