The invention relates to the technical field of power
system load prediction, and discloses a
power load prediction method based on a multi-
scale space-time diagram
attention network, which comprises a space-time load information diagram construction unit, a diagram attention modeling unit and a gating
feature fusion unit. According to the
power load prediction method based on the multi-
scale space-time diagram
attention network, the regional space is divided by using cells, a
topological graph considering cellular
spatial correlation is constructed, a prediction architecture of three-dimensional
feature fusion is constructed, spatial topological correlation is analyzed through the diagram
attention network, a load feature deep mode is mined through a one-dimensional convolutional network, and the
power load prediction method based on the multi-
scale space-time diagram attention network is realized. The bidirectional gating cycle unit captures dynamic characteristics of a
time sequence, and a gating mechanism performs multi-scale feature weighted fusion, so that complex space-time dependence can be better modeled, the generalization ability of the model is improved, the method adapts to a high-frequency fluctuation and multi-source heterogeneous data environment, the accuracy of power load prediction is improved, and the power load prediction efficiency is improved. And powerful support is provided for building a clean, low-carbon, safe and efficient modernized
electric power system.