Spatial Load Forecasting Method Based on GIS and Generative Adversarial Network

Spatial Load Forecasting (SLF) can accurately predict the time period, spatial location, and scale of loads in the future. Geography Information System (GIS) is a kind of technology which combines the advantages of computer technology, database and information system. Starting from GIS system, this paper studies how to use GIS and GAN to establish electric power geographic database and implement spatial load forecasting. The machine learning Generative Adversarial Networks (GAN) model is used to enhance the dimension of the load data sets and to complete the spatial load prediction, and an example analysis is made.