An Artificial Intelligent Load Forecast Method Using Image Based LSTM

Artificial intelligence method is used more and more widely in load forecasting, but the inputs of these methods are usually the raw time series. This paper presents a new artificial intelligence forecasting method using long short term memory (LSTM) and load image. Firstly, the raw time series load data is converted into load images. Then the load images are used as the input of LSTM forecasting model. Finally, the output image of the model is converted to load value as the final forecasting result. Experiments show that the method proposed has significantly improved the forecasting accuracy compared with the simple LSTM algorithm using the raw load time series as the input, and has certain engineering application value.