基于随机优化的割集空间电压稳定域可视化

电压稳定域可视化能够方便调度人员监视电力系统的电压安全裕度，为其决策提供依据。为克服现有算法不能给出概率意义可信度的不足，分别提出了基于理想模型（独立正态分布）的随机优化算法和基于一般模型（非独立正态分布）的数据拟合Monte Carlo算法，以实现割集空间电压稳定域的可视化。其中，基于理想模型的随机优化算法不需要产生大量的随机数，计算过程简洁、高效，且可得到割集空间电压稳定域边界超平面近似的方程。进一步，为了评价利用该超平面方程判断电压稳定的可信度，提出用随机优化的目标函数—正确率作为置信度指标。基于该指标选择割集功率，可显著提高电压稳定评估的正确率。此外，文中将割集空间概念推广到拟割集空间，使电压稳定域的可视化更准确，更易于工程实现。IEEE39节点系统的仿真分析验证了所述算法的有效性。

Visualization of Voltage Stability Region in Cut-set Space Based on Stochastic Programming

The visualization of a voltage stability region can conveniently monitor the voltage security margin of power systems and provide a decision-making basis to the dispatcher.An ideal model(independent normal distribution)random optimization algorithm and a general model(non-independent normal distribution)data fitting algorithm of Monte Carlo are presented to realize visualization of the static voltage stability region in cut-set space to overcome the incapability of providing credibility in the probabilistic sense of the current algorithm.The ideal model random optimization algorithm is simple and effective for solving the hyperplane equation of the voltage stability region boundary in cut-set space.The objective function of random optimization and the accuracy probabilistic index are presented to assess the accuracy of using the solution to estimate voltage stability in cut-set space.The algorithm proposed can be used to select cut-set line power and improve the accuracy probabilistic index.The concept of cut-set space is extended to quasi cut-set space to improve the accuracy probabilistic index and realize static voltage stability region visualization.The algorithm has been validated by an IEEE 39-bus system.