Revealing Generalized Load Characteristics with Variable Scale User Portrait

With the development of distributed energy technologies, the proportion of generalized load in electric load has greatly increased. Traditional research methods lack variation among different scales and efficiency in big data processing. This paper proposes variable scale user portrait to visually reveal temporal distribution characteristics of generalized load. We adopt it to the data of 3500 customers of Australian Smart Grid, Smart City(SGSC) program. We first set up the label system which is key to user portrait. With Euclidean distance based distributed clustering(EDBDC), the typical users are obtained quickly and efficiently. Then we construct the user portrait with variable time scale load curves for each customer category. The result pattern can provide exploitable information to utilities and retailers for efficient design and implementation of energy service targeted to various customer categories.