A novel approach for power load forecast based on GAN data augmentation

Abstract At present, the concept of Smart Grid is intimately related to huge volumes of data generation, known as Big Data. These play a key role as far as the improvement of the network operation is concerned and, above all, when it comes to energy consumption. Hence the load forecast based on Big Data processing represents a reliable alternative in carrying out an accurate load prediction. As such, a new approach for the power load forecast, based on GAN data augmentation, for a hospital, within a Smart Grid, will be presented in this work.