基于贝叶斯网络的10kV线路时钟超差计量点负荷类型识别方法

Load type identification method of 10 kV transmission line clock‑inaccuracy metering point based on bayesian network

10 kV线路上负荷计量点处出现时钟超差将导致线损率异常,而现有人工排查方法存在效率低、智能化程度不高的问题。为此,提出一种基于线损率曲线波动特征识别时钟超差计量点负荷类型的新方法,通过贝叶斯网络(BN)拟合负荷类型与时钟超差线损率的映射关系。为解决时钟超差样本缺乏的问题,在基于线路实际运行数据的仿真模型中对负荷计量点分别设置计量时钟偏差模块,生成时钟超差线损率样本集;引入模糊C均值聚类,根据负荷曲线形状相似度对负荷进行归类,在负荷较多的场景中实现数据降维。依托于同期线损系统的研究数据,算例分析验证了该方法的可行性和准确性,说明其可实现时钟超差计量点负荷类型辨识,为快速定位时钟超差异常电能表提供参考。

The clock‑inaccuracy at the load measuring point on the 10 kV line leads to an abnormal line loss rate,while the existing manual methods have the problems of low efficiency and low intelligence.Therefore,based on the fluctuation characteristics of line loss rate curve,a new method for identifying the load types of clock‑inaccuracy metering points is proposed to fit the mapping relationship between load type and the clock‑inaccuracy line loss rate by Bayesian network(BN).In order to solve the problem of lack of clock‑inaccuracy samples,the metering clock deviation modules are respectively set for the load metering points to generate a sample set of clock‑inaccuracy line loss rate in the simulation model based on the actual operation data of the line.The fuzzy C‑means clustering is then introduced to classify the load according to the shape similarity of the load curve,and the data dimensionality reduction is realized in scenarios with heavy load.Relying on research data from the synchronous line loss management system,the calculation example verifies the feasibility and accuracy of the proposed method.It is shown that the method can realize load type identification of clock‑inaccuracy,and provide a reference for quickly locating the abnormal energy meters.