Short-term power load forecasting based on BP neural network

Inhalt:
In order to improve the stability of grid load forecasting. Aiming at short-term microgrid load forecasting, this paper proposes a method based on BP neural network to forecast the source side of the power grid. This method is based on the user’s historical electricity consumption data. Through the training sample data, the influence of various influencing factors on the electricity load of the microgrid is analyzed, and the load forecasting model is established through the BP neural network topology, and then the short-term electricity is simulated by MATLAB. Load forecasting, for a 24-hour a day power load forecasting of a microgrid, the forecast result shows that it is consistent with the actual value, which proves the stability of the model.