Electricity load demand has grown more than four-fold over the last 20 years period. The purpose of the current study is to evaluate the performance of ARAR model in forecasting electricity load demand in Malaysia. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) will be used as a benchmark model since the model has been proven in many forecasting context. Using Root Mean Square Error (RMSE) as the forecasting performance measure, the study concludes that ARAR is more appropriate model
Forecasting electricity demand requires accurate and sustainable data acquisition systems which rely...
This paper proposes multi-equation linear regression model with autoregressive AR(2) method for mode...
Abstract—Load forecasting forms the basis of demand response planning in energy trading markets wher...
Electricity is among the most crucial needs for every people in this world. It is defined by the set...
Load forecasting is a process of predicting the future load demands. It is important for power syste...
Load demand is a time series data and it is one of the major input factors in economic development e...
Load demand is a time series data and it is one of the major input factors in economic development e...
Forecasting. Plans, power plants ,. Electricity needs are increasingly changing daily, so the State ...
Forecasting. Plans, power plants ,. Electricity needs are increasingly changing daily, so the State ...
This paper discusses a new algorithm of a univariate method, which is vitally important to develop a...
Solar power generation have been gaining ground as a result of improved generating efficiency, reduc...
Accurate load forecasting is become crucial in power system operation and planning; both for deregul...
Customer demand for electrical energy continues to increase, so electrical energy infrastructure mus...
The rapid development of the Internet of Things (IoT) has brought a data explosion and a new set of ...
Time series analysis has been applied intensively and sophisticatedly to model and forecast many pro...
Forecasting electricity demand requires accurate and sustainable data acquisition systems which rely...
This paper proposes multi-equation linear regression model with autoregressive AR(2) method for mode...
Abstract—Load forecasting forms the basis of demand response planning in energy trading markets wher...
Electricity is among the most crucial needs for every people in this world. It is defined by the set...
Load forecasting is a process of predicting the future load demands. It is important for power syste...
Load demand is a time series data and it is one of the major input factors in economic development e...
Load demand is a time series data and it is one of the major input factors in economic development e...
Forecasting. Plans, power plants ,. Electricity needs are increasingly changing daily, so the State ...
Forecasting. Plans, power plants ,. Electricity needs are increasingly changing daily, so the State ...
This paper discusses a new algorithm of a univariate method, which is vitally important to develop a...
Solar power generation have been gaining ground as a result of improved generating efficiency, reduc...
Accurate load forecasting is become crucial in power system operation and planning; both for deregul...
Customer demand for electrical energy continues to increase, so electrical energy infrastructure mus...
The rapid development of the Internet of Things (IoT) has brought a data explosion and a new set of ...
Time series analysis has been applied intensively and sophisticatedly to model and forecast many pro...
Forecasting electricity demand requires accurate and sustainable data acquisition systems which rely...
This paper proposes multi-equation linear regression model with autoregressive AR(2) method for mode...
Abstract—Load forecasting forms the basis of demand response planning in energy trading markets wher...