TITLE:
Low Voltage Daily Energy Demand Temperature Dependent Representation by Using Circular Statistics
AUTHORS:
Pucheta Julián, Salas Carlos, Piumetto Miguel, Herrera Martín, Rodriguez Rivero Cristian
KEYWORDS:
Distribution Transformers, Charge Estimation, Time Series, Dynamic Process, Circular Statistics
JOURNAL NAME:
Applied Mathematics,
Vol.10 No.3,
March
15,
2019
ABSTRACT: In this work, a tool that allows visualizing the probability of the power demand according to the temperature and the hours of the day is presented. This aim contributes to the decision making support for the transformer and its service administration. The objective is to represent the demand accurately as
a color statistical map based on two variables: the time of day and the ambient temperature. Since the daily energy consumption is periodic regarding the hours of the day in terms of several days, its representation with Gaussian models becomes difficult, but it is simplified when working with circular statistics. The circular statistics used here is the Von Mises distribution, which has the parameters mean address and kappa concentration. Results obtained from measurements made over a year in a medium-voltage transformer with intervals of 60 minutes are shown.