基于改进贝叶斯算法的主动配电网状态估计  

Active distribution network state estimation based on improved Bayes algorithm

作　　者：马景岳 胡健[1] 齐晓妹 伊书鑫 MA Jingyue;HU Jian;QI Xiaomei;YI Shuxin(School of Electrical and Electronic Engineering,Shandong University of Technology,Zibo 255000,China)

机构地区：[1]山东理工大学电气与电子工程学院,山东淄博255000

出　　处：《现代电子技术》2022年第7期117-121,共5页Modern Electronics Technique

基　　金：山东省重点研发计划(公益类)(2019GGX104025)。

摘　　要：为解决主动配电网数据量大、多数据源造成的现状,提出一种适用于主动配电网的状态估计方法。利用数据处理技术,以数据校验原则对量测数据预处理,并计算数据质量标签,对节点量测数据初步修正;结合所得数据质量标签结果与贝叶斯算法建立改进贝叶斯数据分类模型,对存在多个不良数据的节点进行不良数据的辨识,实现了状态估计前的不良数据处理,提高了输入到状态估计模型的数据精度;同时针对主动配电网量测困难问题,建立分布式电源的量测模型,补全分布式电源缺省数据,提高了数据质量;最后,基于质量标签改进加权最小二乘算法权重矩阵,建立状态估计模型。算例分析表明,提出的方法能明显减少分布式能源波动和不良数据的影响,提供了较精确的状态估计结果。In view of the current situation caused by large data volume and multiple data sources in active distribution network(ADN),a state estimation method suitable for ADN is proposed.With the data processing technology,the measured data are preprocessed according to the principle of data check,the data quality label is calculated,and the node measured data are corrected preliminarily.In combination with the data quality label results and Bayes algorithm,an improved Bayesian data classification model is established,which identifies bad data for nodes with multiple bad data,realizes the bad data processing before state estimation,and improves the accuracy of data input into state estimation model.In view of the measurement difficulty of ADN,the measurement model of distributed generation is established to complete the default data of distributed generation,so as to improve the data quality.Based on the quality label,the weight matrix of the weighted least squares algorithm is improved to establish a state estimation model.Example analysis shows that the proposed method can significantly reduce the influence of distributed energy fluctuations and bad data,and provide more accurate state estimation results.

关 键 词：主动配电网 状态估计 数据处理技术 分布式电源 质量标签 贝叶斯算法 不良数据 加权最小二乘法 

分 类 号：TN709-34[电子电信—电路与系统] TM734[电气工程—电力系统及自动化]