Forecasting Electricity Consumption Using Weather Data in an Edge-Fog-Cloud Data Analytics Architecture

Abstract

The forecasting of electricity consumption is a well-study research problem; however, electricity consumption is a complex model because it depends on many factors, and its accuracy is not always accurate. The accuracy of this forecasting impact; for example, in the utilities in the bulk generation of electricity and in the end-user at economical prices. This work shows the implementation of a forecasting model considering weather data across the smart metering system infrastructure using and edge-fog-cloud architecture for data analytics. The results show that using weather data across edge-fog-cloud architecture is an excellent alternative to forecast electricity consumption.