基于概率预测与谐波潮流的配电网谐波源识别方法

为解决配电网中谐波源的位置和数量的信息不明确的问题，提出了一种谐波源识别方法。该方法首先采用灵敏度指数对谐波测量装置的选址进行优化，然后采用基于遗传算法优化的支持向量机概率预测算法对母线含有谐波源的概率进行计算，最后使用谐波潮流对识别结果进行验证和进一步的分析。为评估该方法的可靠性和有效性，该方法在IEEE-13节点系统上进行了仿真分析。仿真结果说明了算法的有效性。

Harmonic sources identification method in distribution network based on probability forecasting and harmonic power flow

Harmonic sources identification is needed when the information about the positions and number of harmonic sources in the network is insufficient. To solve this problem, a harmonic sources identification method is proposed. Sensitivity index is used firstly for the optimal placement of harmonic measurement devices. Then a method based on genetic algorithm (GA) and support vector machine (SVM) is used to classify the buses as suspected and non-suspected ones. GA is used for parameters optimization for SVM models. At last, harmonic power flow is performed to examine the accuracy of the predicted locations. To evaluate its reliability and effectiveness, the proposed method is applied to the modified IEEE 13-bus system. The evaluation results are very promising. This work is supported by Science and Technology Program of State Grid Shandong Electric Power Company (No. 520625150002).