张认, 王健, 商洁, 海晨, 刘皓明. 基于复合高斯混合模型的主动配电网全局概率电压灵敏度分析[J]. 电网技术, 2025, 49(1): 295-305. DOI: 10.13335/j.1000-3673.pst.2023.2078
引用本文: 张认, 王健, 商洁, 海晨, 刘皓明. 基于复合高斯混合模型的主动配电网全局概率电压灵敏度分析[J]. 电网技术, 2025, 49(1): 295-305. DOI: 10.13335/j.1000-3673.pst.2023.2078
ZHANG Ren, WANG Jian, SHANG Jie, HAI Chen, LIU Haoming. Global Probabilistic Voltage Sensitivity Analysis of Active Distribution Networks Based on the Compound Gaussian Mixture Model[J]. Power System Technology, 2025, 49(1): 295-305. DOI: 10.13335/j.1000-3673.pst.2023.2078
Citation: ZHANG Ren, WANG Jian, SHANG Jie, HAI Chen, LIU Haoming. Global Probabilistic Voltage Sensitivity Analysis of Active Distribution Networks Based on the Compound Gaussian Mixture Model[J]. Power System Technology, 2025, 49(1): 295-305. DOI: 10.13335/j.1000-3673.pst.2023.2078

基于复合高斯混合模型的主动配电网全局概率电压灵敏度分析

Global Probabilistic Voltage Sensitivity Analysis of Active Distribution Networks Based on the Compound Gaussian Mixture Model

  • 摘要: 高比例分布式电源(distributed generation,DG)的随机性加剧了主动配电网(active distribution network,ADN)电压波动,并使ADN电压安全分析愈加复杂,故提出了一种基于复合高斯混合模型(Gaussian mixture model,GMM)的全局概率电压灵敏度分析方法。首先推导基于节点道路交集阻抗的ADN全局电压灵敏度解析模型,量化所有节点功率波动对节点电压的影响。考虑到多个节点注入功率不确定性的叠加影响下,电压波动呈现非高斯分布特征,采用高斯混合模型刻画DG和负荷预测误差的概率特征。然后,基于全局灵敏度矩阵对DG和负荷预测误差GMM的仿射变换,构建源荷功率波动与电压波动的概率解析式。最后,推导DG和负荷不确定性对电压波动综合影响的复合GMM特征函数,建立基于复合GMM的全局概率电压灵敏度分析模型。算例结果表明,所提方法能够反映所有节点注入功率波动对节点电压波动影响的概率特征,可快速准确计算出ADN电压运行的越限概率。

     

    Abstract: The stochasticity of the high penetration of distributed generations (DGs) exacerbates the voltage fluctuation of the active distribution networks (ADNs) and complicates its voltage safety analysis. Therefore, this paper proposes a global probability voltage sensitivity analysis method based on the compound Gaussian mixture model (GMM). Firstly, a shared node path impedance-based global voltage sensitivity analytical model of ADN is derived to quantify the impact of global power fluctuations on node voltage. Considering that the voltage fluctuation has the non-Gaussian characteristic under the superposition influence of power uncertainty injected by multiple nodes, the GMM is used to characterize the probability characteristics of DG and load forecasting errors. Then, based on the affine transformation of the global sensitivity matrix to the GMM of DG and load forecasting error, the probability analytic expression of the voltage fluctuation is constructed, which is caused by the uncertainty of DG and load. Finally, based on the GMM characteristic function, the compound GMM characteristic function of the combined influence of the uncertainty of DG and load on voltage fluctuation is derived, and the global probabilistic voltage sensitivity analysis model based on the compound GMM is established. The case study results show that the proposed method can reflect the probability characteristics of the impact of all node power fluctuations on node voltage, and can quickly and accurately calculate the probability of over-voltage in ADNs.

     

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