Prediction of macro city gas load on BP neural network theory

Gas transmission and distribution system, the gas load is the main parameter to impact the project planning, which determines the capacity of equipments and operation program. Therefore, accurate prediction of gas load is of extremely important significance for gas companies to improve safety and reliability of gas supply. The forecasting method of tradition gas load would not meet the requirement for accurate prediction. It is necessary to find a new method to forecast it. Multi-layer feed forward artificial neural network based on BP algorithm is selected to forecast macro city gas load and a predicted model is established by using MATLAB programming. In order to ensure the accuracy of the prediction model, the article focuses on the simulation error of the text model and judges these errors as the accuracy of the prediction models.