基于负荷模糊聚类的电压稳定概率评估

在对研究时段内多个负荷水平进行模糊C均值聚类的基础上，采用多维正态分布抽样技术，提出了一种同时计及节点负荷相关性和负荷预测不确定性的电压稳定概率评估方法。通过对负荷样本多次抽样后进行连续潮流计算及模态分析，可以获得系统功率极值、母线与支路参与因子的统计信息，以及系统在给定负荷水平下电压失稳的概率，从概率角度指出具有潜在电压稳定问题的区域，实现对系统电压稳定性的概率评估。通过对IEEE57节点系统进行分析计算，验证了算法的可行性和有效性，并就模糊聚类数、负荷预测不确定性和节点负荷相关性对电压稳定评估结果的影响进行了比较和分析。

Probabilistic Evaluation of Voltage Stability Based on Load Fuzzy Clustering

Based on the fuzzy C-means (FCM) clustering algorithm, a new method for probabilistic voltage stability evaluation considering bus load correlation and load forecasting uncertainty is presented in this paper via adopting the multi-dimension correlation sampling technique. The probabilistic voltage stability of power system is evaluated by the statistical information of system maximum loadability and system participations, which are obtained by repeated load level sampling as well as afterward continuation load flow calculation and modal analysis near the voltage collapse point, thus the voltage instability probability at a certain load level and the area prone to voltage instability from the viewpoint of probability are obtained. The proposed method is tested in IEEE 57-bus system to show its feasibility and validity, The effects of the number of fuzzy clustering, bus load correlation and uncertainty on voltage stability are investigated.