The load of power network is influenced by weather

holidays and life style

which is random in short term and regular in long term. Choosing a suitable short-term load forecasting model will help to improve the accuracy of short-term load forecasting and greatly facilitate the short-term load forecasting work.In this paper

short-term load forecasting tool based on BP algorithm of neural network is used to acquire a large number of arrays by collecting data samples from local power network.The non-linear relationship between each factor and load is obtained by the neural network BP algorithm self-adaptive learning.The changing trend of load in local power network is predicted

the mode of power grid is regulated in advance

the risks of main transformer and line operation are reduced

and the safe operation of power grid is ensured.