Short-term Forecasting of Multivariate Loads and Photovoltaic Power Based on MTL-SA-LSTM
It is crucial to accurately predict the multivariate loads and photovoltaic power for the development of load demand re-sponse plan,energy equipment scheduling,and renewable energy consumption in an integrated energy system that includes photo-voltaic power generation.To this end,a novel short-term forecasting model is proposed for the simultaneous forecasting of elec-tric,cooling and thermal multivariate loads as well as photovoltaic power.The model adopts the multi-task learning and long short-term memory network architecture based on hard parameter sharing,with the self-attention mechanism incorporated to pre-vent performance degradation,thus giving significantly higher accuracy in prediction results compared with other models.
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