基于监测数据相关性分析的用户谐波责任划分方法

针对传统谐波责任划分方法无法实现长时间尺度的动态责任划分,需要专门量测,无法利用现有监测系统数据,以及无法划分同一馈线各用户谐波责任等缺点,提出一种基于监测数据相关性分析的用户谐波责任划分方法。首先,计算电能质量监测系统中谐波电压数据序列与用电信息采集系统中各用户平均有功功率数据序列的典则相关系数,将公共连接点谐波责任划分为背景谐波责任与所关注用户谐波责任;其次,计算谐波电压与各用户有功功率的动态扭曲相关系数,用于反映各用户用电行为与公共连接点谐波电压畸变的关联关系;最后,构造并计算同时考虑关联关系、用户用电容量的长时间尺度谐波责任划分指标。利用实际监测系统中的数据验证了所提方法的有效性和实用性,能基于现有监测数据实现馈线上每个用户的长时间尺度动态谐波责任划分。

Determination Method of User Harmonic Responsibility Based on Correlation Analysis of Monitoring Data

Conventional harmonic responsibility determination methods have shortages such as the inability to achieve long-time scale dynamic responsibility determination, the need for special measurement, the inability to utilize the data of existing monitoring systems, and the inability to determine the harmonic responsibilities of users on the same feeder. Thus, this paper proposes a determination method of user harmonic responsibility based on correlation analysis of monitoring data. Firstly, the monitoring data are collected, including the harmonic voltage data from the power quality monitoring system and the average active power data of each user from the power information collection system. By the canonical correlation coefficients based on these data, the harmonic responsibility at the point of common coupling (PCC) is divided into the background harmonic responsibility and the harmonic responsibility of concerned users. Secondly, the dynamic distortion correlation coefficients of harmonic voltage and active power of each user are calculated, which are used to reflect the relationship between user power consumption behavior and harmonic voltage distortion at PCC. Finally, the long-time scale index for harmonic responsibility determination is developed with consideration of the relationship and user power consumption capacity. The validity and practicability of the proposed method are verified by the data in the actual monitoring system, and the long-time scale dynamic harmonic responsibility determination of each user on the feeder can be realized based on the existing monitoring data.