Power load prediction method based on Kalman filter and convolutional neural network

The invention discloses a power load prediction method based on a Kalman filter and a convolutional neural network. The power load prediction method comprises the following steps: acquiring historicalload data of a power system in a certain region, and processing abnormal data of the historical load data; analyzing and quantifying factors influencing the power load, wehrein the corrected data arenormalized; determining input and output data of a neural network, determining the number of neurons of an optimal hidden layer, and establishing a convolutional neural network; carrying out prediction by using the trained convolutional neural network, and carrying out inverse normalization on predicted data to obtain a load prediction value; determining a Kalman equation according to the time sequence model and the predicted value of the convolutional neural network, taking the predicted value of the time sequence model as a real value of Kalman filtering, taking the predicted value of the convolutional neural networ