New energy consumption method based on depth learning

Abstract

The invention belongs to the technical field of new energy power generation consumption and discloses a new energy consumption method based on depth learning. The method is characterized in that a back propagation algorithm of the multi-layered perceptual neural network is utilized for realization, and training is performed through utilizing the improved dynamic recurrent neural network method; the optimization process includes the offline training process of a deep learning model, and the other part is the online optimization process of a deep learning optimization controller. The method is advantaged in that the depth learning-based consumption optimization algorithm can determine optimization controller parameters online according to the content and the quantity of different optimization targets and the content and the quantity of different constraints without the need of artificial adjustment, the method is universally adaptable for application scenes, the dynamic recurrent neuralnetwork model training method based on an adaptive update coefficient can overcome disadvantages that the conventional dynamic recurrent neural network has the slow convergence speed and is easy to fall into a local minimum value, and the training time of an optimization controller model is shortened under the premise of ensuring accuracy.

Description

technical field [0001] The invention belongs to the technical field of new energy power generation and consumption, and in particular relates to a new energy consumption method based on deep learning. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: With the increasingly serious problems of energy security, ecological environment, and climate change, accelerating the development of new energy has become a consensus method to promote energy transformation and development and cope with global climate change. Among them, wind power generation and photovoltaic power generation have become the clean energy development methods with the fastest development, the most mature technology and the best commercialization prospects. However, the randomness, intermittency, and volatility of wind power and photovoltaic power generation have caused a series of problems in the large-scale development of new energy, such as access...

AI Technical Summary

Problems solved by technology

[0003] To sum up, the current large-scale new energy is concentrated in the "Three North" region, and the local consumption capacity in this region is low, the power transmission distance is long, the capacity is large, and the flexible power supply is lacking. The safe operation of new energy power generation and effective consumpt

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