Comprehensive energy load prediction method based on multi-task learning strategy and deep learning

Abstract

The invention relates to a comprehensive energy load prediction method based on a multi-task learning strategy and deep learning. The method comprises the following steps: S1, forming a historical cooling, heating and power load feature library and an influence factor feature library; S2, constructing an MMoE multi-task learning model; S3, constructing three LSTM neural network models, training the three LSTM neural network models by utilizing feature sharing and extraction results output by a plurality of expert sub-networks in the MMoE model in the step S2 and cold, hot and electric load tags, and finally obtaining an MMoE-LSTM model; and S4, obtaining a cooling, heating and electric load prediction result. According to the method, interference of weak correlation information on the subtasks can be avoided, and a better prediction effect is achieved.

Description

technical field [0001] The invention belongs to the technical field of comprehensive energy, and relates to a comprehensive energy load forecasting method, in particular to a comprehensive energy load forecasting method based on multi-task learning strategies and deep learning. Background technique [0002] With the development of my country's economy and society, the demand for energy continues to grow, and energy issues have become an important issue related to national security strategies and sustainable development capabilities. In the traditional energy supply system, functional systems such as cooling, heating, and electricity operate independently of each other, lack of coordination, low energy utilization rate, and poor reliability of energy supply. Therefore, the energy supply and consumption link is gradually developing towards an integrated energy system. The integrated energy system makes full use of the complementary effects of various energy forms, significantl...

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Problems solved by technology

[0007] After searching, no publications of the prior art identical or similar to the present invention were found

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