Research on Load Forecasting Technology of Power System Based on Artificial Intelligence

With the development of new type power systems, artificial intelligence plays an increasingly important role in the stability and security of power grids. And Power load forecasting is one of the main applications of artificial intelligence. The power load of a city usually includes three types of industrial and commercial people, because the commercial load is relatively fixed, so the forecast of industrial electricity and civil electricity is more important. This paper focuses on the first step of load forecasting: load classification. A convolution neural network coincidence classification method based on data enhancement is proposed based on the comparison of the characteristics of different types of power curves. The results show that the data enhancement can effectively improve the classification accuracy, and the use of convolutional neural network for power load classification can have a better classification effect.