【摘要】 目前配电网低压台区相位关系存在记录不准确或更新不及时的问题,不利于低压台区的运行与管理。提出一种基于筛选电压数据的配电台区低压用户相别自动辨识和校验方法。首先,获取最近一段时间内配电变压器三相电压及该台区所有用户电压的历史数据,计算变压器电压在不同时刻的三相不平衡率,筛选出不平衡率最大的时刻,并由这些时刻对应的电压值构成变压器三相电压及用户电压的新时间序列;然后,计算各电压新序列之间的动态时间弯曲距离,采用改进的K均值聚类算法实现用户相别的自动辨识;最后,采用变压器各相总电能与用户智能电表数据对用户相别辨识结果进行校验。仿真结果和工程实例验证了所提方法的有效性。更多还原

【Abstract】 The current low-voltage station phase relationship records of the distribution network are inaccurate or untimely updating,which has a negative impact on the operation and management of the low-voltage station area. An automatic phase identification and verification method for low-voltage users in the distribution station area based on filtered voltage data is proposed. Firstly, obtain the historical data of the three-phase voltage on the low-voltage side of the distribution transformer and the voltage of all single-phase users in the station in the recent period, calculate the three-phase unbalance rate of the voltage on the low-voltage side of the transformer at different times, among them select the multiple moments with the largest unbalance rate, and the voltage values corresponding to these moments constitute a new time series of the three-phase voltage of the transformer and the voltage of each user. Then, the DTW distance between the new time series of each voltage is calculated, and the K-means clustering algorithm are used to realize the automatic identification of the user phase. Finally, the total power of each phase of the transformer and the powers of the user’s meters are used to check the user phase identification result. The effectiveness of the proposed method is verified by both the simulation results and the engineering example.更多还原