any historical load data

a gated recurrent unitIn view of the difficulty of new community without（GRU）load predictionalgorithm based on data transfer of similar community characteristicsis proposed to realize the load prediction of new community. Firstly

the idea of transfer learning is used to transfer the data informationwhich is highly similar to the features of the new community and predict the model parameters；Secondly

the feature data set is used asthe training set to complete the training of extreme gradient boosting（XGBoost）regression model；Then

GRU neural network is used tomodel the training sample set. When the prediction accuracy of themodel is reached

the medium and long term load prediction of thenew community with time series relationship is completed. Finally

taking a community in Lianyungang as an example

the load prediction results of the residential area form January 2020 to November2022 are obtained

so as to verify the validity of the established medium and long term load prediction model with time series relationship.