Tao Luo, Xudong Cao, Jin Li, Kun Dong, Rui Zhang, Xueliang Wei
Abstract:The energy load data in the micro-energy network are a time series with sequential and nonlinear characteristics. This paper proposes a model based on the encode-decode architecture and ConvLSTM for multi-scale prediction of multi-energy loads in the micro-energy network. We apply ConvLSTM, LSTM, attention mechanism and multi-task learning concepts to construct a model specifically for processing the energy load forecasting of the micro-energy network. In this paper, ConvLSTM is used to encode the input time s…
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