The invention provides a power grid service classification method based on a neural network. The power grid service classification method comprises the steps of: I, carrying out data set pre-processing and classification; II, using an individual network training set to train and generate a specified number of individual neural networks; III, determining weight coefficients of the individual neural networks by using a network selection training set; IV, judging whether to preserve the individual neural networks according to the weight coefficients, and generating neural network ensemble models; V, testing the models by using a testing sample set, and adjusting a neural network ensemble with the combination of a threshold value; VI, and outputting an optimal neural network ensemble model and classification results. The power grid service classification method is used for selecting the individual neural networks based on an improved CS algorithm, generating the neural network ensemble models with the combination of neural network features, and improving selection efficiency and accuracy, thereby being more accurate and efficient in processing power grid service data and recognizing service types.