The invention discloses a short-term
power load prediction method based on
deep learning, and the method comprises the steps: S1, collecting historical
power load data and corresponding weather and holiday and festival information, S2, carrying out the preprocessing of the historical data based on the historical
power load data and the change of a power
utilization behavior mode of a user, reducing the data inconsistency, and carrying out the prediction of a short-term power load. The method comprises the following steps: S1,
processing historical power load data, weather information and holiday and festival information, S3, constructing a
deep learning model which inputs processed historical power load data, weather information and holiday and festival information, S4, training the constructed
deep learning model by using a training
data set and optimizing
model parameters, and S5, carrying out short-term power load prediction by using the trained deep learning model and generating a prediction result. According to the short-term power load prediction method based on deep learning, the problem of inconsistency of historical data caused by frequent change of power utilization habits of users in a changeable user behavior mode in the prior art is solved.