Building air conditioner model prediction control method and device for realizing demand side response

Abstract

The invention provides a building air conditioner model prediction control method and device for realizing demand side response, and relates to the field of indoor environment control. The method comprises the following steps: historical heat environment data of control areas of a controlled building is collected, wherein the controlled building comprises one or more control areas; heat environments of the control areas in a preset prediction period are predicted according to the historical heat environment data of the control areas and prediction variables; building air conditioner terminal equipment is controlled to input the power to the control areas to meet first preset conditions in the preset prediction period according to prediction results of the control areas and comfort requirements; or the building air conditioner terminal equipment is controlled to input the total power to the controlled building to meet second preset conditions in the preset prediction period according tothe prediction results of all the control areas of the controlled building and the comfort requirements of each control area.

Description

technical field [0001] The invention relates to the field of indoor environment control, in particular to a building air-conditioning model predictive control method and device for realizing demand-side response. Background technique [0002] my country is a big energy consumer, in which building energy consumption accounts for as high as 25% of the total energy consumption of the whole society, and this proportion is still increasing year by year, while the energy consumption of air conditioning systems has always accounted for a large part of building energy consumption. As people's requirements for building comfort and energy saving are increasing, how to control the terminal equipment of the air conditioning system to achieve energy saving as much as possible while meeting people's comfort requirements has attracted more and more attention. [0003] At present, the traditional HVAC control strategy is relatively extensive, ignoring the influence of time and space on the ...

AI Technical Summary

Problems solved by technology

However, due to the constraints of the model, the effect of this control technology is greatly affected.

Overly complex mechanism modeling, due to the difficulty of implementation and low implementability, is difficult to implement in the actual control system of the project

However, an oversimplified abstract model will affect the optimization accuracy and application scenarios of the control system, and restrict the optimization and energy saving effect of the control system.

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