Power distribution network load prediction method and system based on deep learning

The invention discloses a power distribution network load prediction method based on deep learning, and the method comprises the steps: obtaining regional load data and renewable energy power generation data, forming a data set, carrying out the preprocessing of the data set, and obtaining a first data set; extracting time sequence features in the first data set by using a convolutional neural network, converting the time sequence features into a data form of a deep learning model through an embedded layer, obtaining one-dimensional time sequence data, performing fast Fourier transform to obtain a frequency curve, extracting an amplitude value on the frequency curve, and calculating to obtain a corresponding period; selecting a corresponding period to slice and divide the one-dimensional time sequence data into a two-dimensional matrix; according to the method, a two-dimensional convolutional network is used for feature extraction, a two-dimensional matrix subjected to feature extraction is restored into a on