Grey Prediction Model for Forecasting Electricity consumption

Empirical Comparison of Prediction Methods for Electricity Consumption Forecasting

Recent years have seen an increasing interest in providing accurate prediction models for electrical energy consumption. In Smart Grids, energy consumption optimization is critical to enhance power grid reliability, and avoid supply-demand mismatches. Utilities rely on real-time power consumption data from individual customers in their service area to forecast the future demand and initiate ene...

Forecasting Electricity Consumption for Pakistan

Now-a-days, different sectors of the economy are being significantly affected by the electricity variable. In this research, we analyzed the monthly electricity consumption in Pakistan for the period of January 1990 through December 2011, using linear and non linear modeling techniques. They include ARIMA, Seasonal ARIMA (SARIMA) and ARCH/GARCH models. Electricity consumption model reveals a si...

Modeling & Forecasting US Electricity Consumption

Forecasting electricity consumption has often prefered to treat socioeconomic activity and wealth as exogenous. The motivation for this research is to endogenize electricity consumption with economic activity by introducing electricity demand, and the interactions between electricity use and economic activity, into macroeconomic demand equations. In this paper, I create an energy and macroecono...

Forecasting the Consumption for Electricity in Taiwan

This paper use linear regression and non-linear artificial neural network (ANN) model to analyze how the four economic factors: national income (NI), population (POP), gross of domestic production (GDP), and consumer price index (CPI), affect Taiwan’s electricity consumption, furthermore, develop an economic forecasting model. Both models agree with that POP and NI are of the most influence on ...

Ensemble Prediction Model with Expert Selection for Electricity Price Forecasting

Day-ahead forecasting of electricity prices is important in deregulated electricity markets for all the stakeholders: energy wholesalers, traders, retailers, and consumers. Electricity price forecasting is an inherently difficult problem due to its special characteristic of dynamicity and non-stationarity. In this paper, we present a robust price forecasting mechanism that shows resilience towa...

Monash Electricity Forecasting Model