Control method of VAV (variable air volume) air-conditioning system

Abstract

The invention provides a control scheme of a VAV (variable air volume) air-conditioning system. A neural network predictive control method is used for a tail end VAV-BOX and an air-conditioning unit, thus the hysteresis characteristic of a VAV system can be overcome, the control accuracy is improved, the resonance phenomena of an actuating mechanism can be greatly reduced, the energy-saving effect is improved by above 13%, and the control parameter tuning problem in the project is solved. A pressure independent cascade stage predictive control method is used for the tail end VAV-BOX, thus thecontrol accuracy can also be improved. The air-conditioning unit is provided with four control loops and can automatically select a static pressure control or total air volume control policy with adjustable setting static pressure by using an all-condition integrated control technology, thus the predictive control on a fan can be realized; the primary air volume of all the tail end VAV-BOXes can be detected and the air supply temperature can be adjusted according to the operation condition, thus the problem of too low temperature in partial air-conditioning area in the lowest fresh air operation is solved; the cascade stage predictive control method is adopted for a fresh air ratio control loop, thus the accurate control on the fresh air ratio can be realized and the energy-saving level can be further improved.

Description

technical field [0001] The invention relates to a control method of a VAV variable air volume air conditioner system, belonging to the technical field of VAV variable air volume air conditioner control in civil buildings. Background technique [0002] At present, the VAV variable air volume air conditioning control system is mainly based on the separate design of multiple loops, and is basically adjusted by the PID control method. Its automatic control system needs the commissioning engineer to set the PID parameters on site according to his own experience, and does not have self-learning ability. . Since the time constant of each automatic control system is different, it is very easy to cause poor adaptability of the automatic control system, resulting in large temperature fluctuations or "resonance" phenomenon of the actuator. At the same time, due to the certain coupling relationship among multiple loops in the VAV air-conditioning system, even if the debugging and opera...

AI Technical Summary

Problems solved by technology

[0006] The present invention aims at the difficulty in control of the existing VAV variable air volume air conditioner, which is a multi-input multi-output nonlinear system with large hysteresis characteristics, and integrates the advantages of neural network, optimal control and predictive control, and proposes an intelligent control method

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