基于半不变量及最大熵的概率谐波潮流算法

Probabilistic Harmonic Power Flow Algorithm Based on Cumulant and Maximum Entropy

针对电力系统中谐波分布的不确定性,提出了一种结合半不变量、线性化谐波潮流方程以及最大熵模型的概率谐波潮流算法。首先,根据谐波电流的样本获取高阶矩和半不变量等数字特征,根据电网基础数据构建谐波潮流方程并在基准运行点处线性化,计算谐波电压数字特征,进而建立最大熵模型拟合其概率分布。所提方法具有计算量小、编程简单、结果客观准确等优点。最后,使用所提方法在4节点系统上与卷积法比较,以及在IEEE 57节点系统上与蒙特卡洛法比较,均验证了该方法的有效性。

In view of the uncertainty of harmonic distribution in the power system, this paper proposes a probabilistic harmonic power flow algorithm based on cumulant, linear harmonic power flow equation and maximum entropy model. Firstly, the numerical characleristies, such as higher moments and cumulant, are obtained according to the samples of harmonic current. Secondly, the harmonic power flow equation is constructed according to the basic data of the grid and linearized at the reference operating point. The numerical characteristics of the harmonic voltage are calculated. Then the maximum entropy model is developed to fit the probability distribution of the harmonic voltage. The proposed method has the advantages of low computational complexity, simple programming and objective and accurate resuhs. Finally, the probabilistic harmonic power flow is calculated on a 4-bus system and the IEEE 57-bus power system. The results are compared with the convolution method and the Monte Carlo method to verify the effectiveness of the method.