基于拉丁超立方重点采样的静态电压稳定概率评估法

A Probabilistic Evaluation Method of Static Voltage Stability Based on Latino Hypercube Important Sampling

为描述新型电力系统下大规模风电等不确定因素对系统静态电压稳定的影响,研究系统临界功率概率分布及给定负荷水平下的电压失稳概率,本文构建电压稳定非线性规划模型,采用机会约束引入随机变量,使用拉丁超立方重点采样法构建样本空间,使用内点法计算系统临界功率概率分布,通过与蒙特卡洛法对比验证算法的有效性、收敛性和耗时,最后应用所提算法分析风电出力在不同置信水平和约束上限对系统临界功率的影响,结果表明所提方法快速有效。

In order to describe the influence of large-scale wind power and other uncertain factors on the static voltage stability of power network based on new energy, and to study the system critical power probability distribution and the voltage instability probability under a given load level, this paper constructs a voltage stability nonlinear programming model. The random variables are introduced by chance constraints, the sample space is constructed by the Latin hypercube important sampling method, the probability distribution of the critical power of the system is calculated by the interior point method, and the effectiveness, convergence and time consumption of the algorithm are verified by comparison with the Monte Carlo method. Finally, the proposed algorithm is used to analyze the influence of wind power output on the critical power of the system at different confidence levels and upper bound constraints. The results show that the proposed method is fast and effective.