This paper presents seasonal regression models of demand to investigate electricity consumption characteristics. Elec-tricity consumption in commercial areas in Japan is analyzed by using meteorological variables, namely temperature and relative humidity. A dummy variable for holidays is also considered. We have developed models for two levels of period to analyze demand characteristics, that is, half year models and seasonal models. Some options for each model are calculated and validated by statistical tests to obtain better models. As results, half year and seasonal models present explicit information about how the variables affect the demand differently for each period. These specific information help in analyzing characteristics of stu...
This article provides a solution based on statistical methods (ARIMA, ETS, and Prophet) to predict m...
[[abstract]]This paper studies the dynamic demand for residential electricity in Taiwan employing a ...
Electricity demand (or “load”) forecasting has been subject to several time series based studies, mo...
Because of the need to keep balancing between electricity supply and demand continuously, a demand a...
Accurate modeling and forecasting monthly electricity consumption are the keys to optimizing energy ...
The quality of short-term electricity demand forecasting is essential for the energy market players ...
In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with se...
Load forecasting is important in the operation of power systems. The characteristics of the electric...
Load forecasting is important in the operation of power systems. The characteristics of the electric...
Energy data are often reported on an annual basis. To address the climate and health impacts of gree...
Selection of appropriate climatic variables for prediction of electricity demand is critical as it a...
Energy demand forecasting, and specifically electricity demand forecasting, is a fun-damental featur...
Abstract- The forecast of electricity demand in India is of considerable interest since the electric...
We wish to investigate climate change-driven effects on electricity demand and production. We model ...
Residential electricity consumption is an important component of total electricity sales for Nebrask...
This article provides a solution based on statistical methods (ARIMA, ETS, and Prophet) to predict m...
[[abstract]]This paper studies the dynamic demand for residential electricity in Taiwan employing a ...
Electricity demand (or “load”) forecasting has been subject to several time series based studies, mo...
Because of the need to keep balancing between electricity supply and demand continuously, a demand a...
Accurate modeling and forecasting monthly electricity consumption are the keys to optimizing energy ...
The quality of short-term electricity demand forecasting is essential for the energy market players ...
In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with se...
Load forecasting is important in the operation of power systems. The characteristics of the electric...
Load forecasting is important in the operation of power systems. The characteristics of the electric...
Energy data are often reported on an annual basis. To address the climate and health impacts of gree...
Selection of appropriate climatic variables for prediction of electricity demand is critical as it a...
Energy demand forecasting, and specifically electricity demand forecasting, is a fun-damental featur...
Abstract- The forecast of electricity demand in India is of considerable interest since the electric...
We wish to investigate climate change-driven effects on electricity demand and production. We model ...
Residential electricity consumption is an important component of total electricity sales for Nebrask...
This article provides a solution based on statistical methods (ARIMA, ETS, and Prophet) to predict m...
[[abstract]]This paper studies the dynamic demand for residential electricity in Taiwan employing a ...
Electricity demand (or “load”) forecasting has been subject to several time series based studies, mo...