Analyzing Temperature-Sensitive Loads of Medium Voltage Classified Users

Abstract

With the development of new energy sources, the operation of power system needs controllable power loads to balance the fluctuation of the sources. This paper focuses on temperature sensitive load, which has gained many attentions in recent years. Specifically, a method to extract and analyze the summer temperature-sensitive loads of medium voltage classified users is proposed, which uses K-means clustering method to obtain MV classified users and correlation coefficient method to analyze temperature sensitivities of the classified users at different times of the year. The method is applied to field data of a whole year, and the temperature-sensitive loads of MV classified users in July and August are extracted. Their characteristics, including the share of temperature-sensitive load, the maximum daily temperature-sensitive load growth rate and the peak distribution of daily temperature-sensitive load, are analyzed, which are helpful for operation and control of power system.