基于仿真与实测数据融合的电压暂降风险评估

Voltage Sag Risk Assessment Based on Fusion of Simulated and Measured Data

电压暂降风险评估有助于电压暂降防治与敏感用户选址。仿真模拟方法数据多但难以反映实际环境影响,数据驱动方法样本少且分布不均,导致全网各节点电压暂降风险难以得知。因此,文中提出一种基于仿真与实测数据融合的电压暂降风险评估方法。首先,从仿真与实测数据中筛选电压暂降风险影响因素,并构建表征暂降传播特性的影响域综合量化指标;其次,采用尾部类过采样与头部类欠采样构建仿真源域数据集,基于知识迁移与Armijo-Goldstein准则改进梯度下降法,构建无监测数据节点的残余电压多元回归预测模型;最后,结合预测结果与暂降耐受特性划分电压暂降风险级别。通过实际电网算例分析表明,所提方法的准确率与收敛性能相较于现有常用方法有所提高,能快速准确地评估全网电压暂降风险。

Voltage sag risk assessment is helpful for voltage sag prevention and sensitive user siting.The simulation-based methods have a large amount of data which cannot reflect the influence of actual environment,and the data-driven methods have few samples with uneven distribution.So it is difficult to know the voltage sag risk of each bus in the whole network.Therefore,a voltage sag risk assessment method based on the fusion of simulated and measured data is proposed.First,the influencing factors of voltage sag risk are selected from simulated and measured data,and then the comprehensive quantitative index of the influence domain characterizing the voltage sag propagation characteristics is constructed.Second,the tail class oversampling and the head class undersampling are used to construct the simulation source domain dataset,and the gradient descent method is improved by knowledge transfer andArmijo-Goldstein criterion to construct the residual voltage multiple regression prediction model for the buses without measured data.Finally,the voltage sag risk level is classified by combining the predicted results with the voltage sag tolerance characteristics.The analysis of an actual power grid case shows that the accuracy and convergence performance of the proposed method are improved compared with the existing commonly used methods,and the voltage sag risk in the whole network can be evaluated quickly and accurately.