A tail end space energy consumption prediction method based on building total energy consumption, a medium and equipment

Abstract

The invention discloses a tail end space energy consumption prediction method based on building total energy consumption, a medium and equipment, and the method comprises the steps of sequentially transmitting preprocessed sample data of N tail end spaces at a moment t and first tau time steps into a tail end space energy consumption prediction model in each step of model training; enabling the model to obtain N tail end space energy consumption prediction values at the t moment through N times of forward calculation, adding the N tail end space energy consumption prediction values to the actual total energy consumption of the building to calculate a loss function, and adjusting parameters of the tail end space energy consumption prediction model through back propagation of a gradient descent method; repeating the training process on the sample data at all moments until the model converges to the prediction precision, and completing the training of the end space energy consumption prediction model; and predicting the energy consumption generated by the tail end space by using the obtained tail end space energy consumption prediction model through the controller parameters of the tail end devices, the temperature and humidity sensors, the Internet weather information, the people flow density, the power of the electric appliances and the lighting devices and the house structure parameters in the operation process of the building heating and ventilation system. According to the invention, the training of the tail end space energy consumption prediction model is realized underthe condition that the tail end space energy consumption historical data is missing.

Description

technical field [0001] The invention belongs to the technical field of HVAC and artificial intelligence, and in particular relates to a method, medium and equipment for predicting energy consumption of terminal spaces based on total energy consumption of buildings. Background technique [0002] At present, my country's construction stock market is very huge, and the smart city and urban construction in the new era also focus on the intelligent upgrade of large public buildings such as office buildings, hotels, and schools. Fully realize the popularization and application of advanced technology in buildings, comprehensively improve the level of building intelligence, and realize an important aspect of energy saving in intelligent buildings is to establish and improve building energy consumption management systems, the basis of which is to realize energy consumption monitoring and energy consumption prediction. Statistics show that the energy consumption of electromechanical s...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a terminal space energy consumption prediction method, medium and equipment based on the total energy consumption of buildings in view of the deficiencies in the above-mentioned prior art, and utilize the relationship that building energy consumption is equal to the sum of terminal space energy consumption , train the end space energy consumption prediction model through the total building energy consumption data, end space equipment parameters and environmental data, and abstract the end space into quantifiable variables in the model, so that the model can be applied to different end spaces and overcome the end space It is difficult to train the defect of energy consumption prediction model when energy consumption cannot be directly measured, and make the energy consumption prediction model applicable to different end spaces

Images