Energy-saving optimization control method, device, equipment and storage medium for central air-conditioning system

Abstract

The present application relates to a method, device, equipment and storage medium for optimizing the control of a central air-conditioning system. The method includes: determining multiple operating state combinations of each device in the central air-conditioning system according to the performance characteristic models of each device in the central air-conditioning system and the demand information of the cold load of the central air-conditioning system on the user side; determining a target operating state combination from the multiple operating state combinations according to a preset screening condition; controlling the central air-conditioning system to operate according to the target operating state combination, and determining the actual value of the system refrigeration efficiency of the central air-conditioning system in the target operating state combination; when the actual value of the system refrigeration efficiency does not meet the preset requirements, obtaining the target value of the return water temperature of the chilled water main pipe of the central air-conditioning system and the target value of the system refrigeration efficiency of the central air-conditioning system; further controlling each device in the central air-conditioning system through a pre-established model predictive controller according to the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of central air conditioning systems, and in particular, to an energy-saving optimization control method, device, equipment, and storage medium for a central air conditioning system. Background Art

[0002] At present, central air conditioning systems are widely used in various buildings, and their energy consumption accounts for a very high proportion in the whole building, generally 40%-50%. Therefore, the problem of energy conservation and consumption reduction has attracted more and more attention. Moreover, there are many devices involved in the central air conditioning system, and the efficiency models of each device are different. There are many input and output variables for energy-saving optimization control, which have the characteristics of non-linearity, time-variation, and coupling. As a result, it is difficult for each device in the central air conditioning system to operate under relatively optimal working conditions. Then, for those skilled in the art, how to make each device in the central air conditioning system operate under relatively optimal working conditions so as to reduce the energy consumption of the central air conditioning system has become an important research topic. Summary of the Invention

[0003] Based on this, the embodiments of the present application provide an energy-saving optimization control method, device, equipment, and storage medium for a central air conditioning system, which can make each device in the central air conditioning system operate under relatively optimal working conditions, thereby reducing the energy consumption of the central air conditioning system and achieving the purpose of energy-saving optimization.

[0004] In a first aspect, the embodiments of the present application provide an energy-saving optimization control method for a central air conditioning system, including:

[0005] Determine various operating state combinations of each device in the central air conditioning system according to the performance characteristic models of each device in the central air conditioning system and the demand information of the cooling load of the central air conditioning system on the user side;

[0006] Determine the target operating state combination from various operating state combinations according to the preset screening conditions;

[0007] Control the central air conditioning system to operate according to the target operating state combination, and determine the actual value of the system refrigeration efficiency of the central air conditioning system under the target operating state combination;

[0008] When the actual value of the system refrigeration efficiency does not meet the preset requirements, obtain the target value of the return water temperature of the chilled water main pipe of the central air conditioning system and the target value of the system refrigeration efficiency of the central air conditioning system;

[0009] According to the return water temperature target value of the chilled water main pipe and the system refrigeration efficiency target value, the various devices of the central air-conditioning system are further controlled by a pre-established model prediction controller, so that the actual value of the system refrigeration efficiency of the central air-conditioning system reaches the system refrigeration efficiency target value, and the actual value of the return water temperature of the chilled water main pipe of the central air-conditioning system reaches the return water temperature target value of the chilled water main pipe.

[0010] In a second aspect, an energy-saving optimization control device for a central air-conditioning system provided by an embodiment of the present application includes:

[0011] A determination module, configured to determine multiple operating state combinations of the various devices of the central air-conditioning system according to the performance characteristic models of the various devices of the central air-conditioning system and the demand information of the user side for the cooling load of the central air-conditioning system;

[0012] The determination module is further configured to determine a target operating state combination from the multiple operating state combinations according to a preset screening condition;

[0013] A control module, configured to control the central air-conditioning system to operate according to the target operating state combination;

[0014] The determination module is further configured to determine the actual value of the system refrigeration efficiency of the central air-conditioning system in the target operating state combination;

[0015] An acquisition module, configured to acquire the return water temperature target value of the chilled water main pipe of the central air-conditioning system and the system refrigeration efficiency target value of the central air-conditioning system when the actual value of the system refrigeration efficiency does not meet the preset requirements;

[0016] The control module is further configured to further control the various devices of the central air-conditioning system by a pre-established model prediction controller according to the return water temperature target value of the chilled water main pipe and the system refrigeration efficiency target value, so that the actual value of the system refrigeration efficiency of the central air-conditioning system reaches the system refrigeration efficiency target value, and the actual value of the return water temperature of the chilled water main pipe of the central air-conditioning system reaches the return water temperature target value of the chilled water main pipe.

[0017] In a third aspect, an electronic device provided by an embodiment of the present application includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps of the energy-saving optimization control method for a central air-conditioning system provided in the first aspect of the embodiment of the present application are implemented.

[0018] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the energy-saving optimization control method for a central air-conditioning system provided in the first aspect of the embodiment of the present application are implemented.

[0019] The technical solution provided by the embodiments of the present application can determine the target operating state combination of each device in the central air-conditioning system based on the performance characteristic models of each device in the central air-conditioning system and the demand information of the cooling load on the user side of the central air-conditioning system. By the determined target operating state combination, it can initially control the turning on or off of the corresponding devices in the central air-conditioning system, as well as the operating temperature and frequency. Under the condition of fully meeting the cooling load demand on the user side, the energy consumption of the central air-conditioning system is initially reduced. Moreover, when the actual value of the system refrigeration efficiency does not meet the preset requirements, based on the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency as tracking values, on the basis of the aforementioned adjustment, the temperature and frequency of the corresponding devices in the central air-conditioning system can be further adjusted through the pre-established model predictive controller, so that each device in the central air-conditioning system operates under relatively optimal working conditions, thereby further reducing the energy consumption of the central air-conditioning system and achieving the purpose of energy-saving optimization. Description of the Drawings

[0020] Figure 1 It is a schematic flow chart of a method for energy-saving optimization control of a central air-conditioning system provided by an embodiment of the present application;

[0021] Figure 2 It is a schematic principle diagram of a method for energy-saving optimization control of a central air-conditioning system provided by an embodiment of the present application;

[0022] Figure 3 It is a schematic structural diagram of a device for energy-saving optimization control of a central air-conditioning system provided by an embodiment of the present application;

[0023] Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0024] The present application will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. Additionally, it should be noted that for the sake of description, only the parts related to the present application are shown in the drawings, rather than all the structures.

[0025] In order to make the purpose, technical solution and advantages of the present application clearer, through the following embodiments and in combination with the drawings, the technical solutions in the embodiments of the present application will be further described in detail. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0026] It should be noted that the execution subject of the following method embodiments can be an energy-saving optimization control device for a central air-conditioning system, and this device can be implemented as part or all of an electronic device through software, hardware, or a combination of software and hardware. Optionally, the electronic device can be a computer, a mobile phone, a tablet, or a portable device, etc., or it can be an independent server or a server cluster, etc. The specific type of the electronic device is not limited in the embodiments of the present application.

[0027] Generally, there are many devices involved in a central air-conditioning system. For example, a central air-conditioning system can include a chiller, a cooling water circulation system, a chilled water circulation system, a fan coil system, and a cooling tower, etc. When some local devices in the central air-conditioning system are optimized and controlled, it may cause the energy consumption of other devices to increase, resulting in limited global energy-saving effects of the entire central air-conditioning system. For this reason, the technical solution provided in the embodiments of the present application can determine various operating state combinations of each device in the central air-conditioning system based on the performance characteristic models of each device in the central air-conditioning system and the demand information of the user side for the cooling load of the central air-conditioning system, and select a target operating state combination that meets the preset screening conditions from the various operating state combinations, control the corresponding devices to be turned on or off according to the target operating state combination, and control the temperature or frequency of the corresponding devices, so as to achieve the preliminary control of the central air-conditioning system and achieve the purpose of preliminary energy-saving and consumption reduction; further, determine the actual value of the system refrigeration efficiency of the central air-conditioning system under the target operating state combination. When the actual value of the system refrigeration efficiency does not meet the preset requirements, further control the temperature or frequency of each device in the central air-conditioning system in combination with the target return water temperature value of the chilled water main pipe and the target value of the system refrigeration efficiency, so as to achieve further energy-saving and consumption reduction of the central air-conditioning system.

[0028] Next, the technical solution provided in the embodiments of the present application will be specifically introduced:

[0029] Figure 1 It is a schematic flowchart of a method for energy-saving optimization control of a central air-conditioning system provided in an embodiment of the present application. As Figure 1 shown, the method may include:

[0030] S101. Determine various operating state combinations of each device in the central air-conditioning system based on the performance characteristic models of each device in the central air-conditioning system and the demand information of the user side for the cooling load of the central air-conditioning system.

[0031] Specifically, the performance characteristic model is used to reflect the operating characteristics of the equipment. Different equipment has different performance characteristic models. The equipment in the central air-conditioning system involves chillers, chilled water systems, cooling water systems, cooling towers, etc. Therefore, the above performance characteristic model can include the refrigeration efficiency model of the chiller (this model specifically includes the relationship between the chilled water supply temperature, the cooling water return temperature, the chilled water outlet and return temperature difference, the cooling water outlet and return temperature difference, the refrigeration power and the refrigeration efficiency), the head characteristic models of the chilled water pump and the cooling water pump (this model specifically includes the water flow rate of the corresponding pump, the relationship between the pump frequency and the pump head), the power consumption characteristic models of the chilled water pump and the cooling water pump (this model specifically includes the water flow rate of the corresponding pump, the relationship between the pump frequency and the pump power consumption), the approach characteristic model of the cooling tower (this model specifically includes the relationship between the outdoor ambient wet-bulb temperature, the cooling water flow rate ratio, the cooling tower fan frequency ratio, the cooling water supply and return temperature difference and the cooling water approach, where the cooling water approach is equal to the difference between the cooling water return temperature and the outdoor ambient wet-bulb temperature), and the power consumption characteristic model of the cooling tower fan (this model specifically includes the relationship between the cooling tower fan frequency and the power consumption).

[0032] Optionally, before the above S101, a performance characteristic model of each device in the central air-conditioning system can be established based on the attribute information of each device in the central air-conditioning system.

[0033] Among them, the attribute information of the device includes the device type, the device quantity, and the device parameter information. The device type can include: chillers, chilled water pumps, cooling water pumps, cooling towers, chilled water valves, cooling water valves, and indoor terminal fan coils, etc. The device parameter information can include: for a chiller, the device parameter information can include the rated refrigeration power of the chiller, the minimum operating load rate of the chiller, the rated chilled water flow rate of the chiller, the minimum allowable chilled water flow rate of the chiller, the rated cooling water flow rate of the chiller, and the maximum allowable cooling water flow rate of the chiller. For pumps (including chilled water pumps and cooling water pumps), the device parameter information can include: the rated frequency of the pump, the minimum allowable operating frequency of the pump, the rated water flow rate of the pump, the rated head of the pump, and the rated efficiency of the pump. For a cooling tower, the device parameter information can include the rated frequency of the cooling tower fan, the minimum allowable operating frequency of the cooling tower fan, the rated cooling water flow rate of the cooling tower, and the rated electric power of the cooling tower fan.

[0034] The energy-saving optimization control of the central air-conditioning system is an optimization control under the premise of ensuring that the demand information of the central air-conditioning system's cooling load on the user side is met. Therefore, first, it is necessary to obtain the demand information of the central air-conditioning system's cooling load on the user side, which reflects the demand for the cooling load at the user terminal. In practical applications, the demand information of the central air-conditioning system's cooling load on the user side can be obtained through load forecasting or calculated based on the water temperature difference and chilled water flow rate between the chilled water supply and return.

[0035] After obtaining the performance characteristic models of each device in the central air-conditioning system and the demand information of the central air-conditioning system's cooling load on the user side, heuristic search algorithms such as ant colony algorithm, genetic algorithm, particle swarm algorithm, cuckoo algorithm, etc. can be used to determine all possible operating states of each device in the central air-conditioning system based on the performance characteristic models of each device in the central air-conditioning system and the demand information of the central air-conditioning system's cooling load on the user side, and obtain multiple operating state combinations of each device in the central air-conditioning system. Among them, the operating state includes the device identifier of the device that is turned on or off, and the operating analog quantities of the turned-on devices, such as temperature, frequency, etc., that is, it is clear which devices are turned on, which devices are turned off, and set the corresponding temperature and frequency for the turned-on devices. For example, the operating state combination can include the device identifiers of the chiller, chilled water pump, cooling water pump, and cooling tower that are turned on or off, as well as the chilled water supply temperature setting value of the chiller, the frequency setting value of the chilled water pump, the frequency setting value of the cooling water pump, and the frequency setting value of the cooling tower, etc.

[0036] Taking the particle swarm algorithm as an example, a fitness function can be established based on the energy-saving optimization goal, and the particle swarm information can be initialized; based on the fitness function, the fitness value of each particle can be determined, and based on the fitness value, the historical optimal position of each particle and the historical global optimal position of the particle swarm can be determined; according to the historical optimal position of each particle and the historical global optimal position of the particle swarm, the velocity and position of each particle can be updated, and the step of determining the fitness value of each particle based on the fitness function can be repeatedly executed until the convergence condition is reached, so as to obtain multiple operating state combinations of each device in the central air-conditioning system.

[0037] S102. Determine the target operating state combination from multiple operating state combinations according to the preset screening conditions.

[0038] In practical applications, screening conditions can be preset, such as the energy consumption being less than a preset threshold or the lowest energy consumption, etc. Based on this screening condition, the target operating state combination that meets the screening condition can be determined from multiple operating state combinations.

[0039] In an optional implementation manner, the operating state combination with the lowest energy consumption can be selected from multiple operating state combinations as the target operating state combination.

[0040] S103. Control the central air conditioning system to operate according to the target operating state combination, and determine the actual value of the system refrigeration efficiency of the central air conditioning system under the target operating state combination.

[0041] Among them, after determining the target operating state combination, according to the device opening or closing strategy in the target operating state combination, control the opening or closing of the corresponding devices in the central air conditioning system, and according to the device frequency or temperature setting strategy in the target operating state combination, control the corresponding devices to operate at the determined frequency or temperature. At the same time, after the central air conditioning system operates according to this target operating state combination, the actual value of the system refrigeration efficiency of the central air conditioning system under this target operating state combination can also be determined to further determine whether the central air conditioning system has achieved the required energy-saving optimization goal. Of course, the energy-saving optimization goal can be obtained in advance by analyzing the actual situation of the central air conditioning system devices and historical operation data.

[0042] S104. When the actual value of the system refrigeration efficiency does not meet the preset requirements, obtain the target value of the return water temperature of the chilled water main pipe of the central air conditioning system and the target value of the system refrigeration efficiency of the central air conditioning system.

[0043] S105. According to the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency, further control each device of the central air conditioning system through a pre-established model predictive controller, so that the actual value of the system refrigeration efficiency of the central air conditioning system reaches the target value of the system refrigeration efficiency, and the actual value of the return water temperature of the chilled water main pipe of the central air conditioning system reaches the target value of the return water temperature of the chilled water main pipe.

[0044] Specifically, when the actual value of the system refrigeration efficiency of the central air conditioning system under the target operating state combination does not meet the preset requirements, it indicates that there is still room for further energy-saving optimization of the central air conditioning system. At this time, the target value of the return water temperature of the chilled water main pipe of the central air conditioning system and the target value of the system refrigeration efficiency of the central air conditioning system can be obtained, and used as the optimization control target. On the basis of the previous adjustment of the device temperature and frequency, further optimize the temperature and frequency of the central air conditioning system devices through the model predictive controller. That is to say, take the temperature and frequency of the devices under the target operating state combination as the initial values of the model predictive controller, the above target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency as the tracking values of the model predictive controller, and optimize the temperature and frequency of the devices that have been turned on in the central air conditioning system as a whole, so that the actual value of the system refrigeration efficiency of the central air conditioning system reaches the target value of the system refrigeration efficiency, and the actual value of the return water temperature of the chilled water main pipe reaches the target value of the return water temperature of the chilled water main pipe.

[0045] An optimization control period is set in the above model predictive controller, which can control the operating analog quantities of the turned-on devices in the central air-conditioning system at time k based on the return water temperature target value of the chilled water main pipe and the system refrigeration efficiency target value. For example, the temperature and frequency of the turned-on devices (the chilled water supply temperature at time k (here refers to the set value of the chilled water supply temperature of each turned-on chiller), the total frequency of the chilled water pumps at time k (here the total frequency refers to the sum of the frequencies of multiple pumps), the total frequency of the cooling water pumps at time k (here the total frequency refers to the sum of the frequencies of multiple pumps), the total frequency of the cooling tower fans at time k (here the total frequency refers to the sum of the frequencies of multiple fans), etc.). After the time reaches k+1, it is judged whether the actual value of the return water temperature of the chilled water main pipe in the central air-conditioning system at time k+1 reaches the return water temperature target value of the chilled water main pipe, and whether the actual value of the system refrigeration efficiency at time k+1 reaches the system refrigeration efficiency target value. If not, the operating analog quantities of the turned-on devices in the central air-conditioning system are further adjusted in combination with the return water temperature target value of the chilled water main pipe and the system refrigeration efficiency target value until the actual value of the system refrigeration efficiency of the central air-conditioning system reaches the system refrigeration efficiency target value, and the actual value of the return water temperature of the chilled water main pipe of the central air-conditioning system reaches the return water temperature target value of the chilled water main pipe.

[0046] In practical applications, when adjusting the temperature or frequency of each device in the central air-conditioning system, it is also necessary to judge whether the adjustment amount of the temperature or frequency of the device exceeds the adjustment upper limit value. If it does not exceed the adjustment upper limit value, the corresponding device is adjusted according to the determined adjustment amount. If it exceeds the adjustment upper limit value, the corresponding device can be adjusted according to the adjustment upper limit value. Taking the chilled water supply temperature as an example, the user's indoor temperature and humidity control target values can be obtained. Generally, the dry bulb temperature target value indoors is less than or equal to 26°C, and the relative humidity target value is less than or equal to 60%. Then, based on the user's indoor temperature and humidity control target values, the upper limit of the allowable indoor dew point temperature of the user is determined, and based on the upper limit value of the allowable indoor dew point temperature of the user minus the pre-determined heat exchange temperature difference (wherein, this heat exchange temperature difference is generally determined in advance according to project experience. Optionally, this heat exchange temperature difference can be 3-5 degrees Celsius), the upper limit value of the chilled water supply temperature is obtained. Then, when optimizing the control of the chilled water supply temperature, the chilled water supply temperature does not exceed the above-determined upper limit value of the chilled water supply temperature.

[0047] The energy-saving optimization control method for a central air-conditioning system provided by an embodiment of the present application can determine the target operating state combination of each device in the central air-conditioning system based on the performance characteristic models of each device in the central air-conditioning system and the demand information of the user side for the cooling load of the central air-conditioning system. Initially control the opening or closing of the corresponding devices in the central air-conditioning system through the determined target operating state combination, and at what temperature and frequency to operate, initially reducing the energy consumption of the central air-conditioning system while ensuring that the cooling load demand of the user side is fully met; and, when the actual value of the system refrigeration efficiency does not meet the preset requirements, on the basis of the above adjustment, based on the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency, further adjust the temperature and frequency of the corresponding devices in the central air-conditioning system through a pre-established model predictive controller, so that each device in the central air-conditioning system operates under relatively optimal working conditions, thereby further reducing the energy consumption of the central air-conditioning system and achieving the purpose of energy-saving optimization.

[0048] In one embodiment, an optional implementation manner for determining the actual value of the system refrigeration efficiency of the central air-conditioning system in the target operating state combination is further provided. On the basis of the above embodiment, optionally, determining the actual value of the system refrigeration efficiency of the central air-conditioning system in the target operating state combination in S103 above may include: determining the actual value of the system refrigeration efficiency of the central air-conditioning system in the target operating state combination according to the performance characteristic models of each device in the central air-conditioning system.

[0049] Among them, the performance characteristic models of each device can reflect the relationship between the operating characteristics of the device and the system refrigeration efficiency. Therefore, after controlling the operation of the central air-conditioning system according to the target operating state combination, the actual value of the system refrigeration efficiency of the central air-conditioning system in the target operating state combination can be determined based on the performance characteristic models of the devices that have been turned on in the central air-conditioning system and the current operating parameters.

[0050] Optionally, before S101 above, a system refrigeration efficiency time series model with each device in the central air-conditioning system as a whole can also be established through the historical operation data of the central air-conditioning system, and a model predictive controller can be constructed according to this system refrigeration efficiency time series model.

[0051] Among them, the network structure of the above system refrigeration efficiency time series model is a time series neural network, that is, the pre-established time series neural network is trained through the historical operation data of the central air-conditioning system, so as to obtain the system refrigeration efficiency time series model of the central air-conditioning system.

[0052] The input parameters of the above system refrigeration efficiency time series model include: the supply water temperature of the chilled water main pipe at time k, the total frequency of the cooling tower fans (here the total frequency refers to the sum of the frequencies of multiple fans), the total frequency of the chilled water pumps (here the total frequency refers to the sum of the frequencies of multiple pumps), the total frequency of the cooling water pumps (here the total frequency refers to the sum of the frequencies of multiple pumps), the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the system refrigeration power, the total system refrigeration efficiency, and the return water temperature of the chilled water main pipe; the output parameters of the above system refrigeration efficiency time series model include: the total system refrigeration efficiency of the central air-conditioning system at time k+1 and the return water temperature of the chilled water main pipe.

[0053] The historical operation data of the above central air-conditioning system can include: the supply water temperature of the chilled water main pipe, the return water temperature of the chilled water main pipe, the total frequency of the cooling tower fans (the sum of the frequencies of multiple fans), the total frequency of the chilled water pumps (the sum of the frequencies of multiple pumps), the total frequency of the cooling water pumps (the sum of the frequencies of multiple pumps), the total frequency of the indoor terminal fans (the sum of the frequencies of multiple fans), the opening degree of the fresh air valve at the indoor terminal, the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the system refrigeration power, and the total system refrigeration efficiency.

[0054] Further, keep the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, and the total system refrigeration power at time k in the input parameters of the system refrigeration efficiency time series model unchanged, and conduct step response experiments on the supply water temperature of the chilled water main pipe at time k, the total frequency of the cooling tower fans (the sum of the frequencies of multiple fans), the total frequency of the chilled water pumps (the sum of the frequencies of multiple pumps), and the total frequency of the cooling water pumps (the sum of the frequencies of multiple pumps) in the input parameters respectively, to obtain the dynamic response characteristics of the total system refrigeration efficiency and the return water temperature of the chilled water main pipe of the central air-conditioning system at time k+1, so as to obtain the above model predictive controller. That is to say, the control variables of the model predictive controller are the supply water temperature of the chilled water of each started chiller at time k, the total frequency of the cooling tower fans (the sum of the frequencies of multiple fans), the total frequency of the chilled water pumps (the sum of the frequencies of multiple pumps), and the total frequency of the cooling water pumps (the sum of the frequencies of multiple pumps); the controlled variables of the model predictive controller are: the total system refrigeration efficiency of the central air-conditioning system at time k+1 and the return water temperature of the chilled water main pipe; the control tracking values of the model predictive controller are: the target value of the system refrigeration efficiency and the target value of the return water temperature of the chilled water main pipe of the central air-conditioning system at time k+1.

[0055] In one embodiment, an alternative implementation for obtaining the target value of the return water temperature of the chilled water main pipe of the central air-conditioning system and the target value of the system refrigeration efficiency of the central air-conditioning system is also provided. On the basis of the above embodiment, optionally, obtaining the target value of the return water temperature of the chilled water main pipe in S104 may include: determining the return water temperature of the chilled water main pipe of the central air-conditioning system at the (k + 1)-th moment according to the user terminal energy consumption time series model; and determining the return water temperature of the chilled water main pipe at the (k + 1)-th moment as the target value of the return water temperature of the chilled water main pipe.

[0056] Among them, the input parameters of the user terminal energy consumption time series model include: the supply water temperature of the chilled water main pipe at the k-th moment, the total frequency of the chilled water pumps (the sum of the frequencies of multiple pumps), the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the total frequency of the indoor terminal fans (the sum of the frequencies of multiple fans), the opening degree of the indoor terminal fresh air valve, the system refrigeration power, and the return water temperature of the chilled water main pipe; the output parameter of the user terminal energy consumption time series model includes: the return water temperature of the chilled water main pipe at the (k + 1)-th moment. Among them, the return water temperature of the chilled water main pipe at the (k + 1)-th moment here is the target value of the return water temperature of the chilled water main pipe.

[0057] Optionally, before the above S101, a user terminal energy consumption time series model may also be established through the historical operation data of the central air-conditioning system.

[0058] Among them, the network structure of the above user terminal energy consumption time series model is a time series neural network, that is, the pre-established time series neural network is trained through the historical operation data of the central air-conditioning system, so as to obtain the user terminal energy consumption time series model.

[0059] On the basis of the above embodiment, optionally, obtaining the target value of the system refrigeration efficiency of the central air-conditioning system in S104 may include: determining the target value of the system refrigeration efficiency of the central air-conditioning system according to the energy saving rate target value and the actual value of the system refrigeration efficiency.

[0060] Among them, the energy saving rate target value can be obtained by analyzing the actual situation and historical operation data of the existing equipment in the central air-conditioning system, and then the target value of the system refrigeration efficiency of the central air-conditioning system is calculated through the energy saving rate target value and the actual value of the system refrigeration efficiency.

[0061] In this way, after obtaining the target value of the system refrigeration efficiency and the target value of the return water temperature of the chilled water main pipe, the target value of the system refrigeration efficiency and the target value of the return water temperature of the chilled water main pipe can be used as the optimization control target (i.e., the tracking value). On the basis of the adjustment of the above equipment temperature and frequency, the temperature or frequency of the central air-conditioning system equipment is further optimized by a model predictive controller, so as to further achieve the purpose of energy saving and consumption reduction.

[0062] It should be noted that the above process of energy-saving optimization control for the central air-conditioning system can be adapted to any cold load demand. In actual applications, the central air-conditioning system can be divided into multiple segments from the minimum cooling power to the maximum cooling power. For each segment of cold load demand, the above-described process of energy-saving optimization control for the central air-conditioning system can be used to optimize the control of each device in the central air-conditioning system, so as to achieve energy conservation and consumption reduction of the central air-conditioning system while meeting each segment of cold load demand.

[0063] In actual applications, considering that there are multiple branches at the end of the central air-conditioning system, in order to make the cold load provided by each branch match the actual environment, in one embodiment, the opening degrees of the regulating valves of each branch of the water collector can also be adjusted. The specific adjustment process can include: obtaining the supply water temperature and return water temperature of the chilled water main pipe of the central air-conditioning system at each energy-saving optimization moment; determining the target value of the temperature difference between the supply and return water of the chilled water main pipe according to the supply water temperature and return water temperature of the chilled water main pipe; adjusting the opening degrees of the regulating valves of each branch of the water collector according to the target value of the temperature difference between the supply and return water of the chilled water main pipe, so that the actual value of the temperature difference between the supply and return water of the chilled water of each branch of the water collector reaches the target value of the temperature difference between the supply and return water of the chilled water main pipe.

[0064] Specifically, a proportional-integral-derivative (PID) controller is provided in each branch of the water collector. After determining the target value of the temperature difference between the supply and return water of the chilled water main pipe, the target value of the temperature difference between the supply and return water of the chilled water main pipe is input into the PID controller. The PID controller combines the actual value of the temperature difference between the supply and return water of the chilled water of the branch and the target value of the temperature difference between the supply and return water of the chilled water main pipe to adjust the opening degree of the branch regulating valve, so that the actual value of the temperature difference between the supply and return water of the chilled water of each branch of the water collector reaches the target value of the temperature difference between the supply and return water of the chilled water main pipe.

[0065] In one embodiment, taking Figure 2 as an example, the energy-saving optimization control process of the central air-conditioning system is introduced as follows:

[0066] I. Preliminary optimization process:

[0067] Combining the device types, quantities, and parameter information of each device in the central air-conditioning system, a performance characteristic model of each device is established. Based on the performance characteristic model of each device in the central air-conditioning system and the demand information of the cold load of the central air-conditioning system on the user side, all possible operation strategies of each device in the central air-conditioning system are determined through a heuristic search algorithm, that is, multiple operation state combinations are obtained; then, with the principle of the lowest power consumption, the target operation state combination with the lowest power consumption is determined from multiple operation state combinations (the target operation state combination includes temperature or frequency setting strategies, device on or off strategies), so as to obtain which devices in the central air-conditioning system are on, which devices are off, and the operation analog values of the on devices.

[0068] II. Further optimization process:

[0069] Control the central air-conditioning system to operate according to the target operating state combination. When the actual value of the system refrigeration efficiency of the central air-conditioning system under the target operating state combination does not meet the preset requirements, the operating analog quantity of the turned-on equipment obtained in the above preliminary optimization process can be used as the initial value of the model predictive controller, and the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency are used as the tracking values. Based on the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency, further optimize and control the temperature or frequency of each turned-on equipment of the central air-conditioning system on the basis of the above adjustment through the model predictive controller. For example, adjust the chilled water supply temperature of each turned-on chiller, the total frequency of the cooling tower fans (the sum of the frequencies of multiple fans), the total frequency of the chilled water pumps (the sum of the frequencies of multiple pumps), and the total frequency of the cooling water pumps (the sum of the frequencies of multiple pumps). After adjusting the temperature or frequency of each equipment, after the time reaches the k + 1 moment, determine the actual value of the system refrigeration efficiency and the actual value of the return water temperature of the chilled water main pipe of the central air-conditioning system at the k + 1 moment, and feedback them to the model predictive controller to determine whether the actual value of the system refrigeration efficiency reaches the target value of the system refrigeration efficiency and whether the actual value of the return water temperature of the chilled water main pipe reaches the target value of the return water temperature of the chilled water main pipe. If not, continue the optimization control.

[0070] The above target value of the return water temperature of the chilled water main pipe can be obtained through the following process: Input the supply water temperature of the chilled water main pipe at the k moment, the total frequency of the chilled water pumps, the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the total frequency of the indoor terminal fans, the opening degree of the fresh air valve of the indoor terminal, the system refrigeration power, and the return water temperature of the chilled water main pipe into the user terminal energy consumption time series model to obtain the return water temperature of the chilled water main pipe at the k + 1 moment. Among them, the return water temperature of the chilled water main pipe at the k + 1 moment is the target value of the return water temperature of the chilled water main pipe.

[0071] At the same time, the water temperature difference between the return water temperature of the chilled water main pipe and the supply water temperature of the chilled water main pipe can also be determined, and this water temperature difference is input into the PID controllers of each branch of the water collector. The opening degrees of the regulating valves of each branch of the water collector are adjusted through the PID controllers of each branch so that the actual value of the chilled water supply and return water temperature difference of each branch of the water collector reaches the target value of the chilled water supply and return water temperature difference of the chilled water main pipe.

[0072] In this embodiment, since the system refrigeration efficiency time series model and the user terminal energy consumption time series model of the central air-conditioning system are established based on the historical operation data of the central air-conditioning system, the model predictive controller established based on the system refrigeration efficiency time series model and the user terminal energy consumption time series model match the actual situation of the central air-conditioning system. As a result, the accuracy of the chilled water main return temperature target value of the central air-conditioning system determined through the user terminal energy consumption time series model is relatively high, thus achieving the accuracy of energy-saving optimization control. At the same time, regarding each device of the central air-conditioning system as a whole, the model predictive controller is used to optimize and adjust the operating parameters of the activated devices again to ensure that the central air-conditioning system operates under the optimal working conditions, achieving the purpose of energy conservation and consumption reduction.

[0073] Figure 3 FIG. is a schematic structural diagram of an energy-saving optimization control device for a central air-conditioning system provided by an embodiment of the present application. As Figure 3 shown, the device may include: a determination module 301, a control module 302, and an acquisition module 303.

[0074] Specifically, the determination module 301 is configured to determine various operating state combinations of each device of the central air-conditioning system according to the performance characteristic model of each device of the central air-conditioning system and the demand information of the user side for the cooling load of the central air-conditioning system;

[0075] The determination module 301 is further configured to determine a target operating state combination from the various operating state combinations according to a preset screening condition;

[0076] The control module 302 is configured to control the central air-conditioning system to operate according to the target operating state combination;

[0077] The determination module 301 is further configured to determine the actual value of the system refrigeration efficiency of the central air-conditioning system in the target operating state combination;

[0078] The acquisition module 303 is configured to, when the actual value of the system refrigeration efficiency does not meet the preset requirement, acquire the target value of the chilled water main return temperature of the central air-conditioning system and the target value of the system refrigeration efficiency of the central air-conditioning system;

[0079] The control module 302 is further configured to further control each device of the central air-conditioning system according to the target value of the chilled water main return temperature and the target value of the system refrigeration efficiency through a pre-established model predictive controller, so that the actual value of the system refrigeration efficiency of the central air-conditioning system reaches the target value of the system refrigeration efficiency, and the actual value of the chilled water main return temperature of the central air-conditioning system reaches the target value of the chilled water main return temperature.

[0080] The energy-saving optimization control device for the central air-conditioning system provided by the embodiments of the present application can determine the target operating state combination of each device in the central air-conditioning system based on the performance characteristic models of each device in the central air-conditioning system and the demand information of the user side for the cooling load of the central air-conditioning system. Initially control the opening or closing of the corresponding devices in the central air-conditioning system through the determined target operating state combination, and the operating temperature and frequency, and initially reduce the energy consumption of the central air-conditioning system while ensuring that the cooling load demand of the user side is fully met; and when the actual value of the system refrigeration efficiency does not meet the preset requirements, on the basis of the above adjustment, based on the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency as tracking values, further adjust the temperature and frequency of the corresponding devices in the central air-conditioning system through the pre-established model predictive controller, so that each device in the central air-conditioning system operates under relatively optimal working conditions, thereby further reducing the energy consumption of the central air-conditioning system and achieving the purpose of energy-saving optimization.

[0081] Based on the above embodiments, optionally, the determination module 301 is specifically configured to determine the actual value of the system refrigeration efficiency of the central air-conditioning system in the target operating state combination according to the performance characteristic models of each device in the central air-conditioning system.

[0082] Based on the above embodiments, optionally, the acquisition module 303 is specifically configured to determine the return water temperature of the chilled water main pipe of the central air-conditioning system at the k + 1 moment according to the user terminal energy consumption time series model; determine the return water temperature of the chilled water main pipe at the k + 1 moment as the target value of the return water temperature of the chilled water main pipe;

[0083] Wherein, the input parameters of the user terminal energy consumption time series model include: the supply water temperature of the chilled water main pipe at the k moment, the total frequency of the chilled water pumps, the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the total frequency of the indoor terminal fans, the opening degree of the indoor terminal fresh air valve, the system refrigeration power, and the return water temperature of the chilled water main pipe; the output parameter of the user terminal energy consumption time series model is: the return water temperature of the chilled water main pipe at the k + 1 moment.

[0084] Based on the above embodiments, optionally, the device further includes: a model establishment module.

[0085] Specifically, the model establishment module is used to establish a system refrigeration efficiency time series model and the user terminal energy consumption time series model with each device in the central air-conditioning system as a whole according to the historical operation data of the central air-conditioning system before the determination module 301 determines various operating state combinations of each device in the central air-conditioning system according to the performance characteristic models of each device in the central air-conditioning system and the demand information of the user side for the cooling load of the central air-conditioning system; construct the model predictive controller according to the system refrigeration efficiency time series model;

[0086] Among them, the input parameters of the system refrigeration efficiency time series model include: the supply water temperature of the chilled water main pipe at time k, the total frequency of the cooling tower fans (the sum of the frequencies of multiple fans), the total frequency of the chilled water pumps (the sum of the frequencies of multiple pumps), the total frequency of the cooling water pumps (the sum of the frequencies of multiple pumps), the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the system refrigeration power, the total system refrigeration efficiency, and the return water temperature of the chilled water main pipe; the output parameters of the system refrigeration efficiency time series model include: the total system refrigeration efficiency of the central air conditioning system at time k + 1 and the return water temperature of the chilled water main pipe.

[0087] The control variables of the model predictive controller are the supply water temperature of the chilled water of each operating chiller at time k, the total frequency of the cooling tower fans, the total frequency of the chilled water pumps, and the total frequency of the cooling water pumps; the controlled variables of the model predictive controller are: the total system refrigeration efficiency of the central air conditioning system at time k + 1 and the return water temperature of the chilled water main pipe; the control tracking values of the model predictive controller are: the system refrigeration efficiency target value and the return water temperature target value of the chilled water main pipe of the central air conditioning system at time k + 1.

[0088] Based on the above embodiments, optionally, the obtaining module 303 is further specifically configured to determine the system refrigeration efficiency target value of the central air conditioning system according to the energy saving rate target value and the actual value of the system refrigeration efficiency.

[0089] Based on the above embodiments, optionally, the model establishment module is further configured to establish the performance characteristic models of the various devices of the central air conditioning system according to the attribute information of the various devices of the central air conditioning system before the determination module 301 determines various operating state combinations of the various devices of the central air conditioning system according to the performance characteristic models of the various devices of the central air conditioning system and the demand information of the user side for the cooling load of the central air conditioning system; among them, the performance characteristic models include: the refrigeration efficiency model of the chiller, the head characteristic models of the chilled water pump and the cooling water pump, the power consumption characteristic models of the chilled water pump and the cooling water pump, the approach characteristic model of the cooling tower, and the power consumption characteristic model of the cooling tower fan.

[0090] Based on the above embodiments, optionally, the obtaining module 303 is further configured to obtain the supply water temperature and the return water temperature of the chilled water main pipe of the central air conditioning system.

[0091] The determination module 301 is further configured to determine the target value of the temperature difference between the supply and return water of the chilled water main pipe according to the supply water temperature and the return water temperature of the chilled water main pipe.

[0092] The control module 302 is further configured to adjust the opening degrees of the regulating valves of each branch of the water collector according to the target value of the temperature difference between the supply and return water of the chilled water main pipe, so that the actual value of the temperature difference between the supply and return water of the chilled water of each branch of the water collector reaches the target value of the temperature difference between the supply and return water of the chilled water main pipe.

[0093] In one embodiment, an electronic device is provided, and its internal structure diagram can be as shown in Figure 4 the following. The electronic device may include a processor 40, a memory 41, an input device 42, and an output device 43; the number of processors 40 in the electronic device may be one or more. Figure 4 Here, one processor 40 is taken as an example; the processor 40, the memory 41, the input device 42, and the output device 43 in the electronic device may be connected through a bus or other means. Figure 4 Here, connection through a bus is taken as an example.

[0094] The memory 41, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the energy-saving optimization control method of the central air-conditioning system in the embodiments of the present application (for example, the determination module 301, the control module 302, and the acquisition module 303 in the energy-saving optimization control device of the central air-conditioning system). The processor 40 executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory 41, that is, implements the above-mentioned energy-saving optimization control method of the central air-conditioning system.

[0095] The memory 41 may mainly include a program storage area and a data storage area. Among them, the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 41 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some instances, the memory 41 may further include a memory remotely set relative to the processor 40, and these remote memories may be connected to the device / terminal / server through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0096] The input device 42 can be used to receive input digital or character information, and generate key signal inputs related to the user settings and function control of the electronic device. The output device 43 may include a display device such as a display screen.

[0097] The embodiments of the present application also provide a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute an energy-saving optimization control method of a central air-conditioning system when executed by a computer processor. The method includes:

[0098] Determine multiple operating state combinations of each device in the central air-conditioning system according to the performance characteristic models of each device in the central air-conditioning system and the demand information of the cooling load of the central air-conditioning system on the user side;

[0099] Determine a target operating state combination from multiple operating state combinations according to preset screening conditions;

[0100] Control the central air-conditioning system to operate according to the target operating state combination, and determine the actual value of the system refrigeration efficiency of the central air-conditioning system under the target operating state combination;

[0101] When the actual value of the system refrigeration efficiency does not meet the preset requirements, obtain the target value of the return water temperature of the chilled water main pipe of the central air-conditioning system and the target value of the system refrigeration efficiency of the central air-conditioning system;

[0102] According to the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency, further control each device of the central air-conditioning system through a pre-established model predictive controller, so that the actual value of the system refrigeration efficiency of the central air-conditioning system reaches the target value of the system refrigeration efficiency, and the actual value of the return water temperature of the chilled water main pipe of the central air-conditioning system reaches the target value of the return water temperature of the chilled water main pipe.

[0103] Of course, the computer-executable instructions included in the storage medium provided by the embodiments of the present application are not limited to the method operations described above, and can also execute related operations in the energy-saving optimization control method of the central air-conditioning system provided by any embodiment of the present application.

[0104] From the above description of the embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software and necessary general-purpose hardware. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disc of a computer, etc., including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application.

[0105] It should be noted that in the embodiments of the above search device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present application.

[0106] Note that the above is only the preferred embodiment of the present application and the technical principles applied. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments only. Without departing from the concept of the present application, more other equivalent embodiments can be included, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. An energy-saving optimization control method for a central air-conditioning system, characterized in that, Including: Determine multiple operating state combinations of each device in the central air-conditioning system according to the performance characteristic models of each device in the central air-conditioning system and the demand information of the cooling load of the central air-conditioning system on the user side; Determine the target operating state combination from multiple operating state combinations according to the preset screening conditions; Control the central air-conditioning system to operate according to the target operating state combination, and determine the actual value of the system refrigeration efficiency of the central air-conditioning system under the target operating state combination; When the actual value of the system refrigeration efficiency does not meet the preset requirements, obtain the target value of the return water temperature of the chilled water main pipe of the central air-conditioning system and the target value of the system refrigeration efficiency of the central air-conditioning system; According to the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency, further control each device of the central air-conditioning system through the pre-established model predictive controller, so that the actual value of the system refrigeration efficiency of the central air-conditioning system reaches the target value of the system refrigeration efficiency, and the actual value of the return water temperature of the chilled water main pipe of the central air-conditioning system reaches the target value of the return water temperature of the chilled water main pipe.

2. The method according to claim 1, characterized in that, The determining the actual value of the system refrigeration efficiency of the central air-conditioning system under the target operating state combination includes: Determine the actual value of the system refrigeration efficiency of the central air-conditioning system under the target operating state combination according to the performance characteristic models of each device in the central air-conditioning system.

3. The method according to claim 2, characterized in that, The obtaining the target value of the return water temperature of the chilled water main pipe of the central air-conditioning system includes: Determine the return water temperature of the chilled water main pipe of the central air-conditioning system at the (k + 1)th moment according to the user terminal energy consumption time series model; Determine the return water temperature of the chilled water main pipe at the (k + 1)th moment as the target value of the return water temperature of the chilled water main pipe; Wherein, the input parameters of the user terminal energy consumption time series model include: the supply water temperature of the chilled water main pipe at the kth moment, the total frequency of the chilled water pumps, the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the total frequency of the indoor terminal fans, the opening degree of the indoor terminal fresh air valve, the system refrigeration power, and the return water temperature of the chilled water main pipe; the output parameter of the user terminal energy consumption time series model includes: the return water temperature of the chilled water main pipe at the (k + 1)th moment.

4. The method according to claim 3, characterized in that, Before the determining multiple operating state combinations of each device in the central air-conditioning system according to the performance characteristic models of each device in the central air-conditioning system and the demand information of the cooling load of the central air-conditioning system on the user side, the method further includes: Establish a system refrigeration efficiency time series model with each device in the central air-conditioning system as a whole and the user terminal energy consumption time series model according to the historical operation data of the central air-conditioning system; Construct the model predictive controller according to the system refrigeration efficiency time series model; Among them, the input parameters of the system refrigeration efficiency time series model include: the supply water temperature of the chilled water main pipe at time k, the total frequency of the cooling tower fans, the total frequency of the chilled water pumps, the total frequency of the cooling water pumps, the indoor dry bulb temperature of the user, the indoor wet bulb temperature of the user, the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the system refrigeration power, the total system refrigeration efficiency, and the return water temperature of the chilled water main pipe; the output parameters of the system refrigeration efficiency time series model include: the total system refrigeration efficiency of the central air conditioning system at time k + 1 and the return water temperature of the chilled water main pipe. The control variables of the model predictive controller are: the supply water temperature of the chilled water of each operating chiller at time k, the total frequency of the cooling tower fans, the total frequency of the chilled water pumps, and the total frequency of the cooling water pumps; the controlled variables of the model predictive controller are: the total system refrigeration efficiency of the central air conditioning system at time k + 1 and the return water temperature of the chilled water main pipe; the control tracking values of the model predictive controller are: the target value of the system refrigeration efficiency of the central air conditioning system at time k + 1 and the target value of the return water temperature of the chilled water main pipe.

5. The method according to claim 1, characterized in that, The obtaining of the target value of the system refrigeration efficiency of the central air conditioning system includes: Determining the target value of the system refrigeration efficiency of the central air conditioning system according to the target value of the energy saving rate and the actual value of the system refrigeration efficiency.

6. The method according to any one of claims 1 to 5, characterized in that, Before determining various operating state combinations of the equipment of the central air conditioning system according to the performance characteristic models of the equipment of the central air conditioning system and the demand information of the cooling load of the central air conditioning system on the user side, the method further includes: Establishing performance characteristic models of the equipment of the central air conditioning system according to the attribute information of the equipment of the central air conditioning system; Among them, the performance characteristic models include: the refrigeration efficiency model of the chiller, the head characteristic models of the chilled water pumps and the cooling water pumps, the power consumption characteristic models of the chilled water pumps and the cooling water pumps, the approach characteristic model of the cooling tower, and the power consumption characteristic model of the cooling tower fans.

7. The method according to any one of claims 1 to 5, characterized in that, It also includes: Obtaining the supply water temperature and the return water temperature of the chilled water main pipe of the central air conditioning system; Determining the target value of the temperature difference between the supply and return water of the chilled water main pipe according to the supply water temperature and the return water temperature of the chilled water main pipe; Adjusting the opening degrees of the regulating valves of each branch of the water collector according to the target value of the temperature difference between the supply and return water of the chilled water main pipe, so that the actual value of the temperature difference between the supply and return water of the chilled water of each branch of the water collector reaches the target value of the temperature difference between the supply and return water of the chilled water main pipe.

8. An energy-saving optimization control device for a central air-conditioning system, characterized in that, It includes: A determination module, configured to determine various operating state combinations of the equipment of the central air conditioning system according to the performance characteristic models of the equipment of the central air conditioning system and the demand information of the cooling load of the central air conditioning system on the user side; The determination module is further configured to determine a target operating state combination from various operating state combinations according to a preset screening condition; A control module, configured to control the central air conditioning system to operate according to the target operating state combination; The determination module is further configured to determine the actual value of the system refrigeration efficiency of the central air conditioning system in the target operating state combination; An obtaining module, configured to obtain the target value of the return water temperature of the chilled water main pipe of the central air conditioning system and the target value of the system refrigeration efficiency of the central air conditioning system when the actual value of the system refrigeration efficiency does not meet the preset requirements; The control module is further configured to, according to the target value of the return water temperature of the chilled water main pipe and the target value of the system refrigeration efficiency, further control each device of the central air-conditioning system through a pre-established model prediction controller, so that the actual value of the system refrigeration efficiency of the central air-conditioning system reaches the target value of the system refrigeration efficiency, and the actual value of the return water temperature of the chilled water main pipe of the central air-conditioning system reaches the target value of the return water temperature of the chilled water main pipe.

9. An electronic device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 7.

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