Local forecasting for predictive smart home/object control
Local forecasts will become a system component of intelligent houses and objects. This work examines the local forecast of three expected loads or generation of electrical energy, which are to be integrated into an intelligent energy management. These are the household load, photovoltaic feed and the charging load of electric vehicles. Forecasts were performed using linear stochastic signal models, neural networks and deep learning networks.