Central air conditioner energy-saving control method and system based on neural network

Abstract

The invention discloses a central air conditioner energy-saving control method based on a neural network. The method comprises the following steps that first, the working condition parameter data of a started air conditioner system are acquired; second, analog signals in the working condition parameter data are converted into digital signals and sent to a data processing module; third, a current total system power is obtained through calculation according to the working condition parameter data, whether the current total system power is larger than a minimum total system power or not is judged, and an energy-saving strategy is obtained through matching; fourth, a device control module controls the corresponding device to run according to the energy-saving strategy. The invention further discloses a central air conditioner energy-saving control system and device based on the neural network. According to the central air conditioner energy-saving control method, system and device, the energy-saving strategy is obtained through matching according to the processing advantages of the artificial neural network on non-linear complex data, on the premise that application performance requirements are certainly met, an air conditioner system runs with the best efficiency all the time, and the purpose of reducing total system energy consumption is achieved.

Description

technical field [0001] The invention relates to the technical field of central air-conditioning energy saving, in particular to a neural network-based central air-conditioning energy-saving control method and system. Background technique [0002] As an important part of the building system, the central air-conditioning system accounts for a large proportion of the energy consumption and electricity of the entire building system. According to statistics, the energy consumption of the construction industry accounts for 30% of the country's total energy consumption, and the power consumption of the air-conditioning system accounts for 30% of the country's total energy consumption. 70% of the energy consumption of the entire building accounts for about 18% of the company's total electricity consumption. With the demand for building humanized services, this number will continue to grow. Therefore, the energy saving of the air conditioning system is of great significance and effec...

AI Technical Summary

Problems solved by technology

During the operation of the central air conditioner, the host, water pump, cooling tower, etc. do not have any load follow-up capability, which leads to the long-term operation of the central air conditioner under high working conditions, resulting in a lot of energy waste

Especially in the case of weather changes, such as when the temperature is not high when it rains in summer, the demand for cooling capacity decreases, but the central air conditioner operates near the rated working condition, resulting in waste of electric energy

[0004] According to relevant statistics, 90% of the running time of the central air-conditioning unit is in the non-full-load running state, while the chilled water pump, cooling water pump and water tower fan are still in the 100% full-load running state during this 90% of the time. According to the change of the actual cooling load, the output power is increased or decreased correspondingly, which leads to the phenomenon that "large flow rate and small temperature difference" and the temperature difference between frozen water and cooling water cannot be effectively controlled.

At the same time, the chilled water outlet temperature of common chillers is set at about 7.0°C, and the chiller’s chilled water outlet temperature setting cannot be changed in real time according to changes in outdoor temperature and humidity, resulting in a large amount of wasted power.

[0005] The energy consumption management of central air-conditioning is mainly based on the data center system management methods and strategies to achieve the purpose of energy saving, but the traditional data management mode is to control the system equipment by pre-defining the parameters of each equipment of the air-conditioning system to achieve the overall energy-saving purpose. Due to the structure of the air-conditioning system Complex, the operating conditions are changing in real time, and the method of customizing the system energy-saving strategy by relying on fixed parameters cannot make the system always run in the best energy-saving state, and the continuous availability of fixed parameters is poor

[0006] It can be seen from the above that the existing central air-conditioning system cannot change correspondingly with the increase or decrease of the cooling load during the operation process, which makes the actual operating condition of the system far deviate from the optimal operating condition of the system, resulting in the failure of the entire central air-conditioning system. Reduced efficiency

This has always been a major problem that cannot be solved by the traditional central air-conditioning operation mode

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