| Title |
Development of the Series of Probabilistic Statistical Models?for Electricity Demand Prediction in Residential Communities |
| Authors |
김철호(Kim, Chulho) ; 변지욱(Byun, Jiwook) ; 고재현(Go, Jaehyun) ; 허연숙(Heo, Yeonsook) |
| DOI |
https://doi.org/10.5659/JAIK.2021.37.7.157 |
| Keywords |
Probabilistic model; Electricity load profile; Residential community; Uncertainty |
| Abstract |
This study developed a series of probabilistic statistical models for electricity demand prediction of residential communities. The series of
probabilistic models were developed to reflect individual variations in the electricity demand depending on household characteristics and
temporal variability in the pattern of hourly electricity use. We used the hourly electricity data, including plug-in and lighting energy use,
from 23 households selected from the public data of the Korea Energy Agency. The prediction model consists of four models to capture
variability in the electiricity demand at different indiviual and time scales. Models 1 and 2 are blinear regression models that predict the
annual average electricity load depending on the household characteristics and variation in the daily electricity load, respectively. Models 3
and 4 are multivariate normal distribution probability density functions that generate average hourly electricity load profile and temporal
variations from the average profile, respectively. The results demonstrarate that the series of probabilistic models sufficiently reflect actual
individual and temporal variations. |