Author(s)

Pucheta Julián¹, Salas Carlos², Piumetto Miguel¹, Herrera Martín², Rodriguez Rivero Cristian³

¹Departamento de Electrónica-FCEFyN-Universidad Nacional de Córdoba, Córdoba, Argentina.
²FTyCA-Universidad Nacional de Catamarca, San Fernando del Valle de Catamarca, Argentina.
³Center for Neuroscience, University of California at Davis-EEUU, Davis, Argentina.

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.

Distribution Transformers, Charge Estimation, Time Series, Dynamic Process, Circular Statistics

Julián, P. , Carlos, S. , Miguel, P. , Martín, H. and Cristian, R. (2019) Low Voltage Daily Energy Demand Temperature Dependent Representation by Using Circular Statistics. Applied Mathematics, 10, 61-74. doi: 10.4236/am.2019.103006.