Domestic demand predictions considering influence of external environmental parameters

A precise prediction of domestic demand is very important for establishing home energy management system and preventing the damage caused by overloading. In this work, active and reactive power consumption prediction model based on historical power usage data and external environment parameter data (temperature and solar radiation) is presented for a typical Southern Norwegian house. In the presented model, a neural network is adopted as a main prediction technique and historical domestic load data of around 2 years are utilized for training and testing purpose. Temperature and global irradiation (which illustrates the solar radiation level quantitatively) are employed as external parameters. From the results, the efficiency of predictions are evaluated and compared. It can be observed from the numerical results that predictions using historical power data together with external data perform better than the case where only power usage data are adopted.