A control method and system for a central air conditioning system based on power demand response

Abstract

The embodiments of the present specification provide a control method and system for a central air-conditioning system based on power demand response, which belongs to the technical field of central air-conditioning systems. The method includes predicting air-conditioning load based on a characteristic parameter set, wherein the characteristic parameter set includes at least outdoor meteorological parameter forecasts, historical operating data, and building characteristic parameters; determining the amount of power load that can be reduced under different control strategies of the central air-conditioning system based on equipment parameters, wherein the equipment parameters include at least the upper limit of the current load rate of the chiller of the central air-conditioning system and the upper limit of the auxiliary equipment; obtaining the reduction amount of power demand response issued by the power grid side; determining the target control strategy of the central air-conditioning system based on the amount of power load that can be reduced and the reduction amount of power demand response under different control strategies, and controlling the operation of the central air-conditioning system based on the target control strategy, which has the advantages of realizing real-time management of air-conditioning load and improving the stability of operation of the central air-conditioning system.

Description

Technical Field

[0001] The present specification relates to the field of central air-conditioning systems, and in particular to a control method and system for a central air-conditioning system based on power demand response. Background Art

[0002] Central air conditioning system energy consumption accounts for a large proportion in many types of buildings, especially in public buildings such as hospitals, transportation hubs, industrial and commercial office buildings. Due to the special seasonal characteristics and load characteristics of this type of load, the power system faces the risk of increasing peak load and widening peak-to-valley difference in summer.

[0003] Therefore, there is a need to provide a control method and system for a central air-conditioning system based on power demand response, so as to achieve real-time management of the air-conditioning load and improve the stability of the operation of the central air-conditioning system. Summary of the invention

[0004] In order to solve the technical problems in the prior art, one of the embodiments of the present specification provides a control method for a central air-conditioning system based on power demand response, comprising: predicting the air-conditioning load based on a characteristic parameter set, wherein the characteristic parameter set at least includes an outdoor meteorological parameter forecast, historical operation data, and building characteristic parameters; determining the amount of reducible power load under different control strategies of the central air-conditioning system based on equipment parameters, wherein the equipment parameters at least include an upper limit of the current load rate of a chiller and an upper limit of auxiliary equipment of the central air-conditioning system; obtaining the reduction amount of the power demand response issued by the power grid side; determining a target control strategy of the central air-conditioning system based on the amount of reducible power load under the different control strategies and the reduction amount of the power demand response, and controlling the operation of the central air-conditioning system based on the target control strategy.

[0005] In some embodiments, the air conditioning load prediction based on the characteristic parameter set includes: predicting the air conditioning load Q based on the characteristic parameter set by using an ARIMA regression algorithm FC .

[0006] In some embodiments, the control strategy includes a parameter adjustment strategy and a load reduction unit strategy; the determination of the amount of power load that can be reduced under different control strategies of the central air-conditioning system based on equipment parameters includes: according to the set upper limit I of the current load rate of the chiller in the demand response mode MAX,DR , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXDR , Cooling pump frequency operating upper limit FRQ CWP,MAXDR And the frequency operating upper limit FRQ of the cooling tower COT,MAXDR , determine the upper limit of energy consumption Q1 under the parameter adjustment strategy, combine the number of running chillers N, calculate the total upper limit of energy consumption of the central air-conditioning system as N*Q1, combine the predicted air-conditioning load Q FC, calculate the power load reduction (Q FC -N*Q1); according to the upper limit of the chiller current load rate I in the normal operation mode MAX,NM , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXNM , Cooling pump frequency operating upper limit FRQ CWP,MAXNM , Cooling tower frequency operating upper limit FRQ COT,MAXNM , determine the upper limit of energy consumption Q2 under the load reduction strategy, and combine the number of chillers in operation after load reduction N-1 to calculate the upper limit of total energy consumption of the central air-conditioning system as (N-1)*Q2, combined with the predicted air-conditioning load Q FC , determine the amount of power load (Q) that can be reduced by the central air-conditioning system under the load reduction strategy FC -(N-1)*Q2).

[0007] In some embodiments, the target control strategy of the central air-conditioning system is determined based on the power load that can be reduced under the different control strategies and the reduction amount of the power demand response, and the operation of the central air-conditioning system is controlled based on the target control strategy, including: when the reduction amount Q of the power demand response is cut <(Q FC -N*Q1), the parameter adjustment strategy is used as the target control strategy to adjust the current load rate of the chiller to the upper limit I of the current load rate of the chiller in the set demand response mode. MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When (Q FC -N*Q1)≤Q cut ≤(Q FC -(N-1)*Q2), the load reduction unit strategy is used as the target control strategy, and a chiller unit is reduced from the central air-conditioning system, and a chilled water pump and a cooling water pump are reduced at the same time, and the indoor temperature setting value is increased to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When Q cut >(Q FC-(N-1)*Q2), the load reduction unit strategy is used as the target control strategy, and the load of one chiller in the central air-conditioning system is reduced, and at the same time, one refrigeration water pump and one cooling water pump are reduced, and the current load rate of the chiller is adjusted to the upper limit of the current load rate of the chiller in the set demand response mode I MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX .

[0008] In some embodiments, the energy consumption upper limit Q1 under the parameter adjustment strategy is determined based on the following formula: Q1 = Q CHL,MAXDR +Q CHWP,MAXDR +Q CWP,MAXDR +Q COT,MAXDR Where Q CHL,MAXDR is the upper limit load of the chiller in demand response mode, Q CHWP,MAXDR is the upper limit load of the chiller pump in demand response mode, Q CWP,MAXDR is the upper limit load of the cooling pump in demand response mode, Q COT,MAXDR is the upper limit load of the cooling tower in the demand response mode; the energy consumption upper limit Q2 under the load reduction unit strategy is determined based on the following formula, including: Q2 = Q CHL,MAXNM +Q CHWP,MAXNM +Q CWP,MAXNM +Q COT,MAXNM ; In the formula, Q CHL,MAXNM is the upper limit load of the chiller in normal operation mode, Q CHWP,MAXNM is the upper limit load of the refrigeration pump in normal operation mode, Q CWP,MAXNM is the upper limit load of the cooling pump in normal operation mode, Q COT,MAXNM is the upper limit load of the cooling tower in normal operation mode; where Q CHL,MAXNM >Q CHL,MAXDR , Q CHWP,MAXNM >Q CHWP,MAXDR , Q CWP,MAXNM >Q CWP,MAXDR , Q COT,MAXNM >Q COT,MAXD .

[0009] One of the embodiments of the present specification provides a control system for a central air-conditioning system based on power demand response, including a load prediction module for predicting air-conditioning load based on a characteristic parameter set, wherein the characteristic parameter set includes at least outdoor meteorological parameter forecasts, historical operating data, and building characteristic parameters; a load evaluation module for determining the amount of reducible power load under different control strategies of the central air-conditioning system based on equipment parameters, wherein the equipment parameters include at least an upper limit of the current load rate of a chiller and an upper limit of auxiliary equipment of the central air-conditioning system; an air-conditioning control module for obtaining a reduction amount in power demand response, and also for determining a target control strategy for the central air-conditioning system based on the amount of reducible power load under the different control strategies and the reduction amount in the power demand response, and controlling the operation of the central air-conditioning system based on the target control strategy.

[0010] In some embodiments, the load prediction module is further used to: predict the air conditioning load Q based on the characteristic parameter set by using an ARIMA regression algorithm FC .

[0011] In some embodiments, the control strategy includes a parameter adjustment strategy and a load reduction unit strategy; the load evaluation module is also used to: according to the set demand response mode, the upper limit of the current load rate of the chiller I MAX,DR , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXDR , Cooling pump frequency operating upper limit FRQ CWP,MAXDR And the frequency operating upper limit FRQ of the cooling tower COT,MAXDR , determine the upper limit of energy consumption Q1 under the parameter adjustment strategy, combine the number of running chillers N, calculate the total upper limit of energy consumption of the central air-conditioning system as N*Q1, combine the predicted air-conditioning load Q FC , calculate the power load reduction (Q FC -N*Q1); according to the upper limit of the chiller current load rate I in the normal operation mode MAX,NM , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXNM , Cooling pump frequency operating upper limit FRQ CWP,MAXNM , Cooling tower frequency operating upper limit FRQ COT,MAXNM , determine the upper limit of energy consumption Q2 under the load reduction strategy, and combine the number of chillers in operation after load reduction N-1 to calculate the upper limit of total energy consumption of the central air-conditioning system as (N-1)*Q2, combined with the predicted air-conditioning load Q FC , determine the amount of power load (Q) that can be reduced by the central air-conditioning system under the load reduction strategy FC -(N-1)*Q2).

[0012] In some embodiments, the air conditioning control module is further configured to: when the reduction amount Q of the power demand response is cut <(Q FC -N*Q1), the parameter adjustment strategy is used as the target control strategy to adjust the current load rate of the chiller to the upper limit I of the current load rate of the chiller in the set demand response mode. MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When Q cut >(Q FC -(N-1)*Q2), the load reduction unit strategy is used as the target control strategy, and the load of one chiller in the central air-conditioning system is reduced, and at the same time, one refrigeration water pump and one cooling water pump are reduced, and the current load rate of the chiller is adjusted to the upper limit of the current load rate of the chiller in the set demand response mode I MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX .

[0013] In some embodiments, the load evaluation module is further used to determine the energy consumption upper limit Q1 under the parameter adjustment strategy based on the following formula: Q1 = Q CHL,MAXDR +Q CHWP,MAXDR +Q CWP,MAXDR +Q COT,MAXDR ; In the formula, Q CHL,MAXDR is the upper limit load of the chiller in demand response mode, Q CHWP,MAXDR is the upper limit load of the chiller pump in demand response mode, Q CWP,MAXDR is the upper limit load of the cooling pump in demand response mode, Q COT,MAXDRis the upper limit load of the cooling tower in the demand response mode; the energy consumption upper limit Q2 under the load reduction unit strategy is determined based on the following formula, including: Q2 = Q CHL,MAXNM +Q CHWP,MAXNM +Q CWP,MAXNM +Q COT,MAXNM ; In the formula, Q CHL,MAXNM is the upper limit load of the chiller in normal operation mode, Q CHWP,MAXNM is the upper limit load of the refrigeration pump in normal operation mode, Q CWP,MAXNM is the upper limit load of the cooling pump in normal operation mode, Q COT,MAXNM is the upper limit load of the cooling tower in normal operation mode; where Q CHL,MAXNM >Q CHL,MAXDR , Q CHWP,MAXNM >Q CHWP,MAXDR , Q CWP,MAXNM >Q CWP,MAXDR , Q COT,MAXNM >Q COT,MAXD . BRIEF DESCRIPTION OF THE DRAWINGS

[0014] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0015] Figure 1 It is a schematic diagram of an application scenario of a control system of a central air-conditioning system based on power demand response according to some embodiments of this specification;

[0016] Figure 2 It is a module schematic diagram of a control system of a central air-conditioning system based on power demand response according to some embodiments of this specification;

[0017] Figure 3 This is an exemplary flow chart of a control method for a central air-conditioning system based on power demand response according to some embodiments of this specification.

[0018] In the figure, 110 is a processing device; 120 is a network; 130 is a user terminal; and 140 is a storage device. DETAILED DESCRIPTION

[0019] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0020] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0021] As shown in this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0022] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0023] Figure 1 It is a schematic diagram of an application scenario of a control system of a central air-conditioning system based on power demand response according to some embodiments of this specification.

[0024] like Figure 1 As shown, the application scenario may include a processing device 110 , a network 120 , a user terminal 130 , a storage device 140 and a central air conditioning system 150 .

[0025] In some embodiments, the processing device 110 can be used to process information and / or data related to the control of the central air-conditioning system 150. For example, the processing device 110 can predict the air-conditioning load based on a characteristic parameter set, wherein the characteristic parameter set includes at least outdoor meteorological parameter forecasts, historical operating data, and building characteristic parameters, determine the amount of power load that can be reduced under different control strategies of the central air-conditioning system 150 based on the equipment parameters, wherein the equipment parameters include at least the upper limit of the current load rate of the chiller of the central air-conditioning system 150 and the upper limit of the auxiliary equipment, obtain the reduction amount of the power demand response, determine the target control strategy of the central air-conditioning system 150 based on the amount of power load that can be reduced and the reduction amount of power demand response under different control strategies, and control the operation of the central air-conditioning system 150 based on the target control strategy. For more descriptions of the processing device 110, please refer to the descriptions in other parts of this application. For example, Figure 3 and its description.

[0026] In some embodiments, the processing device 110 may be regional or remote. For example, the processing device 110 may access information and / or data stored in the user terminal 130 and the storage device 140 through the network 120. In some embodiments, the processing device 110 may be directly connected to the user terminal 130 and the storage device 140 to access the information and / or data stored therein. In some embodiments, the processing device 110 may be executed on a cloud platform. For example, the cloud platform may include one or any combination of a private cloud, a public cloud, a hybrid cloud, a community cloud, a decentralized cloud, an internal cloud, etc.

[0027] In some embodiments, the processing device 110 may include a processor 210, which may include one or more sub-processors (e.g., a single-core processing device or a multi-core multi-core processing device). As examples only, the processor may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction processor (ASIP), a graphics processing unit (GPU), a physical processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction set computer (RISC), a microprocessor, etc., or any combination thereof.

[0028] The network 120 can facilitate the exchange of data and / or information in the application scenario. In some embodiments, one or more components in the application scenario (e.g., the processing device 110, the user terminal 130, and the storage device 140) can send data and / or information to other components in the application scenario through the network 120. For example, the processing device 110 can obtain outdoor meteorological parameter forecasts, historical operating data, and building feature parameters from the storage device 140 through the network 120. In some embodiments, the network 120 can be any type of wired or wireless network. For example, the network 120 can include a cable network, a wired network, a fiber optic network, a telecommunications network, an internal network, an Internet network, a local area network (LAN), a Bluetooth network, a ZigBee network, a near field communication (NFC) network, etc., or any combination thereof.

[0029] In some embodiments, the user terminal 130 may obtain information or data in the application scenario. For example, the user terminal 130 may obtain the target control strategy from the processing device 110 through the network 120. In some embodiments, the user terminal 130 may include a mobile device (e.g., a smart phone, a smart watch, etc.), a tablet computer, a laptop computer, etc., or any combination thereof.

[0030] In some embodiments, the storage device 140 may be connected to the network 120 to communicate with one or more components of the application scenario (e.g., the processing device 110, the user terminal 130, etc.). One or more components of the application scenario may access data or instructions stored in the storage device 140 through the network 120. In some embodiments, the storage device 140 may be directly connected to or communicate with one or more components in the application scenario (e.g., the processing device 110, the user terminal 130). In some embodiments, the storage device 140 may be a part of the processing device 110.

[0031] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of the present application. For those of ordinary skill in the art, various changes and modifications may be made under the guidance of the content of the present application. The features, structures, methods and other features of the exemplary embodiments described in the present application may be combined in various ways to obtain additional and / or alternative exemplary embodiments. For example, the storage device 140 may be a data storage device including a cloud computing platform, such as a public cloud, a private cloud, a community and a hybrid cloud. However, these changes and modifications will not deviate from the scope of the present application.

[0032] Figure 2 It is a module diagram of a control system of a central air-conditioning system based on power demand response according to some embodiments of this specification.

[0033] like Figure 2As shown, a control system of a central air-conditioning system based on power demand response may include a load prediction module, a load evaluation module and an air-conditioning control module.

[0034] The load prediction module can be used to predict the air conditioning load based on the characteristic parameter set, wherein the characteristic parameter set at least includes outdoor meteorological parameter forecast, historical operation data, and building characteristic parameters. In some embodiments, the load prediction module can predict the air conditioning load Q based on the characteristic parameter set using an ARIMA regression algorithm. FC .

[0035] The load evaluation module can be used to determine the amount of power load that can be reduced under different control strategies of the central air-conditioning system based on the equipment parameters, wherein the equipment parameters at least include the upper limit of the current load rate of the chiller unit and the upper limit of the auxiliary equipment of the central air-conditioning system. In some embodiments, the control strategy includes a parameter adjustment strategy and a load reduction unit strategy. The load evaluation module can determine the amount of power load that can be reduced under different control strategies of the central air-conditioning system based on the equipment parameters, wherein the equipment parameters at least include the upper limit of the current load rate of the chiller unit and the upper limit of the auxiliary equipment of the central air-conditioning system. MAX,DR , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXDR , Cooling pump frequency operating upper limit FRQ CWP,MAXDR And the frequency operating upper limit FRQ of the cooling tower COT,MAXDR , determine the upper limit of energy consumption Q1 under the parameter adjustment strategy, combined with the number of running chillers N, calculate the total upper limit of energy consumption of the central air-conditioning system as N*Q1, combined with the predicted air-conditioning load Q FC , calculate the power load reduction (Q FC -N*Q1), the load assessment module can also set the upper limit of the chiller current load rate I under the normal operating mode. MAX,NM , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXNM , Cooling pump frequency operating upper limit FRQ CWP,MAXNM , the frequency operating upper limit FRQ of the cooling tower COT,MAXNM , determine the upper limit of energy consumption Q2 under the load reduction strategy, combined with the number of chillers in operation after load reduction N-1, calculate the total energy consumption upper limit of the central air-conditioning system as (N-1)*Q2, combined with the predicted air-conditioning load Q FC , determine the amount of power load that can be reduced under the load reduction strategy of the central air-conditioning system (Q FC -(N-1)*Q2). In some embodiments, the load evaluation module can determine the energy consumption upper limit Q1 under the parameter adjustment strategy based on the following formula: Q1=Q CHL,MAXDR +Q CHWP,MAXDR +Q CWP,MAXDR +Q COT,MAXDR ; In the formula, Q CHL,MAXDR is the upper limit load of the chiller in demand response mode, Q CHWP,MAXDRis the upper limit load of the chiller pump in demand response mode, Q CWP,MAXDR is the upper limit load of the cooling pump in demand response mode, Q COT,MAXDR is the upper limit load of the cooling tower in the demand response mode. The energy consumption upper limit Q2 under the load reduction unit strategy can also be determined based on the following formula: Q2 = Q CHL,MAXNM +Q CHWP,MAXNM +Q CWP,MAXNM +Q COT,MAXNM ; In the formula, Q CHL,MAXNM is the upper limit load of the chiller in normal operation mode, Q CHWP,MAXNM is the upper limit load of the refrigeration pump in normal operation mode, Q CWP,MAXNM is the upper limit load of the cooling pump in normal operation mode, Q COT,MAXNM is the upper limit load of the cooling tower in normal operation mode; where Q CHL,MAXNM >Q CHL,MAXDR , Q CHWP,MAXNM >Q CHWP,MAXDR , Q CWP,MAXNM >Q CWP,MAXDR , Q COT,MAXNM >Q COT,MAXD .

[0036] The air conditioning control module can be used to obtain the reduction amount of the power demand response, and is also used to determine the target control strategy of the central air conditioning system based on the power load that can be reduced and the reduction amount of the power demand response under different control strategies, and control the operation of the central air conditioning system based on the target control strategy. In some embodiments, when the reduction amount Q of the power demand response is cut <(Q FC -N*Q1), the air conditioning control module can use the parameter adjustment strategy as the target control strategy to adjust the chiller current load rate to the upper limit of the chiller current load rate I under the set demand response mode. MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When (Q FC -N*Q1)≤Q cut ≤(Q FC-(N-1)*Q2), the air conditioning control module can use the load reduction unit strategy as the target control strategy to reduce the load of a chiller unit from the central air conditioning system, and reduce the load of a chilled water pump and a cooling water pump at the same time, and at the same time increase the indoor temperature set value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When Q cut >(Q FC -(N-1)*Q2), the air conditioning control module can use the load reduction unit strategy as the target control strategy, reduce the load of one chiller in the central air conditioning system, and reduce the load of one chilled water pump and one cooling water pump at the same time, and adjust the current load rate of the chiller to the upper limit of the current load rate of the chiller in the set demand response mode I MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX .

[0037] For more information about the load prediction module, load assessment module, and air conditioning control module, see Figure 3 The related descriptions will not be repeated here.

[0038] It should be noted that the above description of the candidate item display and determination system and its modules is only for convenience of description and does not limit the present specification to the scope of the embodiments. It is understandable that, after understanding the principle of the system, those skilled in the art may arbitrarily combine the modules or form a subsystem to connect with other modules without deviating from the principle. In some embodiments, Figure 1 The load prediction module, load evaluation module and air conditioning control module disclosed in the specification can be different modules in a system, or a module can realize the functions of two or more modules. For example, each module can share a storage module, or each module can have its own storage module. Such variations are all within the scope of protection of this specification.

[0039] Figure 3 is an exemplary flow chart of a control method of a central air conditioning system based on power demand response according to some embodiments of this specification. Figure 3As shown, a control method of a central air conditioning system based on power demand response includes the following steps. In some embodiments, a control method of a central air conditioning system based on power demand response can be executed by a control system or processing device 110 of a central air conditioning system based on power demand response.

[0040] Step 310, predicting the air conditioning load based on the characteristic parameter set. In some embodiments, step 310 may be performed by a load prediction module.

[0041] The characteristic parameter set may be a collection of multiple characteristic parameters, and the characteristic parameter set at least includes outdoor meteorological parameter forecasts, historical operation data, and building characteristic parameters.

[0042] The outdoor weather parameter forecast may include information related to the weather forecast of the external environment of the building where the central air conditioning system is located, such as temperature, humidity, wind direction and speed, air pressure, etc.

[0043] The historical operation data may include operation data of the central air-conditioning system at multiple historical time points.

[0044] The building characteristic parameters may include information related to the building where the central air conditioning system is located, such as thermal physical parameters of enclosures, electrical equipment, floor heights, ventilation duct layout, etc.

[0045] In some embodiments, the load prediction module may obtain characteristic parameters such as outdoor meteorological parameter forecasts, historical operation data, and building characteristic parameters from the processing device 110, the user terminal 130, the storage device 140, and / or an external data source.

[0046] In some embodiments, before the load prediction module predicts the air conditioning load, the characteristic parameter set may be cleaned. The load prediction module may clean the characteristic parameter set based on the operating time, parameter limit and PauTa criterion.

[0047] Data cleaning of feature parameter sets based on operating time specifically includes: the operation of the central air-conditioning system can be divided into the startup phase, the operation phase, and the shutdown phase. Due to the unstable operation in the startup phase and the shutdown phase, the data within 30 minutes after the central air-conditioning system is started and the data after the shutdown strategy is executed are filtered out.

[0048] The data cleaning of the characteristic parameter set based on parameter limits specifically includes: filtering out the data of the chiller, refrigeration pump, cooling pump, and cooling tower operating outside the range of 30-50Hz according to the upper and lower boundary constraints of the operating parameters of the central air-conditioning system; filtering out the data of the chilled water supply temperature T CHWS , Cooling water return temperature T CWR , Chilled water supply and return temperature difference ΔT CHW , Cooling water supply and return water temperature difference ΔTCW Data outside the upper and lower limits of the set value.

[0049] Data cleaning based on the PauTa criterion (3σ criterion) specifically includes: due to the large discreteness of the monitoring parameters and the existence of sensor measurement errors, the parameters are discretized and normally distributed, and the data outside the 3 standard deviations are filtered out.

[0050] In some embodiments, the load prediction module can predict the air conditioning load based on the feature parameter set in any manner, such as predicting the air conditioning load based on the feature parameter set through a machine learning model.

[0051] In some embodiments, the load forecasting module can use the ARIMA regression algorithm to forecast the air conditioning load Q based on the characteristic parameter set. FC The ARIMA regression algorithm predicts the air conditioning load Q based on the characteristic parameter set through the Autoregressive Integrated Moving Average Model (ARIMA). FC .

[0052] Step 320, determining the amount of power load that can be reduced under different control strategies of the central air conditioning system based on the equipment parameters. In some embodiments, step 310 can be performed by a load evaluation module.

[0053] The control strategy may include a parameter adjustment strategy and a load reduction unit strategy, wherein the load reduction unit strategy is to reduce the load of a chiller unit and the corresponding refrigeration pump and cooling pump.

[0054] In some embodiments, the load evaluation module can calculate the upper limit I of the current load rate of the chiller in the demand response mode according to the set MAX,DR , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXDR , Cooling pump frequency operating upper limit FRQ CWP,MAXDR And the frequency operating upper limit FRQ of the cooling tower COT,MAXDR , determine the upper limit of energy consumption Q1 under the parameter adjustment strategy, combined with the number of running chillers N, calculate the total upper limit of energy consumption of the central air-conditioning system as N*Q1, combined with the predicted air-conditioning load Q FC , calculate the power load reduction (Q FC -N*Q1).

[0055] In some embodiments, the load evaluation module may determine the energy consumption upper limit Q1 under the parameter adjustment strategy based on the following formula:

[0056] Q1=Q CHL,MAXDR +Q CHWP,MAXDR +Q CWP,MAXDR +QCOT,MAXDR ;

[0057] In the formula, Q CHL,MAXDR is the upper limit load of the chiller in demand response mode, Q CHWP,MAXDR is the upper limit load of the chiller pump in demand response mode, Q CWP,MAXDR is the upper limit load of the cooling pump in demand response mode, Q COT,MAXDR is the upper limit load of the cooling tower in demand response mode.

[0058] In some embodiments, the load evaluation module can be configured to calculate the upper limit I of the current load rate of the chiller in the normal operation mode according to the upper limit I of the current load rate of the chiller in the normal operation mode. MAX,NM , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXNM , Cooling pump frequency operating upper limit FRQ CWP,MAXNM , the frequency operating upper limit FRQ of the cooling tower COT,MAXNM , determine the upper limit of energy consumption Q2 under the load reduction strategy, combined with the number of chillers in operation after load reduction N-1, calculate the total energy consumption upper limit of the central air-conditioning system as (N-1)*Q2, combined with the predicted air-conditioning load Q FC , determine the amount of power load that can be reduced under the load reduction strategy of the central air-conditioning system (Q FC -(N-1)*Q2).

[0059] In some embodiments, the load evaluation module may determine the energy consumption upper limit Q2 under the load reduction strategy based on the following formula:

[0060] Q2=Q CHL,MAXNM +M QCHWP,MAXNM +Q CWP,MAXNM +Q COT,MAXNM ;

[0061] In the formula, Q CHL,MAXNM is the upper limit load of the chiller in normal operation mode, Q CHWP,MAXNM is the upper limit load of the refrigeration pump in normal operation mode, Q CWP,MAXNM is the upper limit load of the cooling pump in normal operation mode, Q COT,MAXNM It is the upper limit load of the cooling tower in normal operation mode.

[0062] Among them, Q CHL,MAXNM >Q CHL,MAXDR , Q CHWP,MAXNM >Q CHWP,MAXDR , Q CWP,MAXNM >Q CWP,MAXDR , Q COT,MAXNM >Q COT,MAXD .

[0063] Q CHL,MAXDR =Q CHL,rated ×I MAX,DR ;

[0064] Q CHWP,MAXDR =Q CHWP,rated ×(FRQ CHWP,MAXDR / 50) c ;

[0065] Q CWP,MAXDR =Q CWP,rated ×(FRQ CWP,MAXDR / 50) c ;

[0066] Q COT,MAXDR =Q COT,rated ×(FRQ COT,MAXDR / 50) c ;

[0067] In the formula, Q CHL,rated is the rated load of the chiller, Q CHWP,rated is the rated load of the refrigeration pump, Q CWP,rated is the rated load of the cooling pump, Q COT,rated is the rated load of the cooling tower. The value of c ranges from 2.5 to 3, mainly depending on the loss of the inverter.

[0068] Step 330, obtaining the reduction amount of the power demand response issued by the grid side. In some embodiments, step 330 can be performed by the air conditioning control module.

[0069] In some embodiments, the air conditioning control module may obtain the reduction amount of the power demand response issued by the grid side from the processing device 110, the user terminal 130, the storage device 140 and / or the external data source. For example, the air conditioning control module may obtain the reduction amount of the power demand response issued by the grid side through the data interface of the grid side.

[0070] Step 340, based on the amount of power load that can be reduced and the amount of reduction in power demand response under different control strategies, determine the target control strategy of the central air conditioning system, and control the operation of the central air conditioning system based on the target control strategy. In some embodiments, step 340 can be performed by an air conditioning control module.

[0071] In some embodiments, when the reduction amount Q of the power demand response cut <(Q FC -N*Q1), the air conditioning control module can use the parameter adjustment strategy as the target control strategy to adjust the chiller current load rate to the upper limit of the chiller current load rate I under the set demand response mode. MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response modeCWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX .

[0072] In some embodiments, when (Q FC -N*Q1)≤Q cut ≤(Q FC -(N-1)*Q2), the air conditioning control module can use the load reduction unit strategy as the target control strategy to reduce the load of a chiller unit from the central air conditioning system, and reduce the load of a chilled water pump and a cooling water pump at the same time, and at the same time increase the indoor temperature set value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX .

[0073] In some embodiments, when Q cut >(Q FC -(N-1)*Q2), the air conditioning control module can use the load reduction unit strategy as the target control strategy, reduce the load of one chiller in the central air conditioning system, and reduce the load of one chilled water pump and one cooling water pump at the same time, and adjust the current load rate of the chiller to the upper limit of the current load rate of the chiller in the set demand response mode I MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX .

[0074] In some embodiments, a control method and system for a central air-conditioning system based on power demand response is provided in the embodiments of the present description. The control method and system predict the air-conditioning load based on a characteristic parameter set, determine the amount of power load that can be reduced under different control strategies of the central air-conditioning system based on equipment parameters, obtain the reduction amount of power demand response, determine the target control strategy of the central air-conditioning system based on the amount of power load that can be reduced and the reduction amount of power demand response under different control strategies, and control the operation of the central air-conditioning system based on the target control strategy, thereby achieving control of the central air-conditioning system, real-time management of the load of the central air-conditioning system, participating in the power demand response mechanism of the power grid, and achieving optimal overall economic benefits and sustainable and stable operation.

[0075] It should be noted that the above description of a control method for a central air-conditioning system based on power demand response is only for example and explanation, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to a control method for a central air-conditioning system based on power demand response under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0076] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0077] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different locations in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification may be appropriately combined.

[0078] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0079] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0080] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification, documents that limit the broadest scope of the claims of this specification (currently or later attached to this specification) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions, and / or use of terms in this specification shall prevail.

[0081] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A control method for a central air conditioning system based on power demand response, characterized in that: include: Predicting air conditioning load based on a characteristic parameter set, wherein the characteristic parameter set at least includes outdoor meteorological parameter forecasts, historical operation data, and building characteristic parameters; Determine the amount of power load that can be reduced under different control strategies of the central air-conditioning system based on equipment parameters, wherein the equipment parameters at least include an upper limit of the current load rate of the chiller unit and an upper limit of the auxiliary equipment of the central air-conditioning system; Obtain the reduction amount of power demand response issued by the grid side; Determining a target control strategy for the central air-conditioning system based on the amount of power load that can be reduced under the different control strategies and the amount of reduction in the power demand response, and controlling the operation of the central air-conditioning system based on the target control strategy; The method of predicting the air conditioning load based on the characteristic parameter set includes: The air conditioning load Q is predicted based on the characteristic parameter set by using the ARIMA regression algorithm. FC ; The control strategy includes parameter adjustment strategy and load reduction unit strategy; The method of determining the amount of power load that can be reduced under different control strategies of the central air-conditioning system based on equipment parameters includes: According to the upper limit of the current load rate of the chiller in the demand response mode, I MAX,DR , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXDR , Cooling pump frequency operating upper limit FRQ CWP,MAXDR And the frequency operating upper limit FRQ of the cooling tower COT,MAXDR , determine the upper limit of energy consumption Q1 under the parameter adjustment strategy, combine the number of running chillers N, calculate the total upper limit of energy consumption of the central air-conditioning system as N*Q1, combine the predicted air-conditioning load Q FC , calculate the power load reduction (Q FC -N*Q1); According to the set upper limit of the chiller current load rate I in normal operation mode MAX,NM , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXNM , Cooling pump frequency operating upper limit FRQ CWP,MAXNM , Cooling tower frequency operating upper limit FRQ COT,MAXNM , determine the upper limit of energy consumption Q2 under the load reduction strategy, and combine the number of chillers in operation after load reduction N-1 to calculate the upper limit of total energy consumption of the central air-conditioning system as (N-1)*Q2, combined with the predicted air-conditioning load Q FC , determine the amount of power load (Q) that can be reduced by the central air-conditioning system under the load reduction strategy FC -(N-1)*Q2).

2. A control method for a central air conditioning system based on power demand response as claimed in claim 1, characterized in that: The step of determining a target control strategy for the central air-conditioning system based on the amount of power load that can be reduced under the different control strategies and the amount of reduction in the power demand response, and controlling the operation of the central air-conditioning system based on the target control strategy includes: When the power demand response reduction amount Q cut <(Q FC -N*Q1), the parameter adjustment strategy is used as the target control strategy to adjust the current load rate of the chiller to the upper limit I of the current load rate of the chiller in the set demand response mode. MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When (Q FC -N*Q1)≤Q cut ≤(Q FC -(N-1)*Q2), the load reduction unit strategy is used as the target control strategy, and a chiller unit is reduced from the central air-conditioning system, and a chilled water pump and a cooling water pump are reduced at the same time, and the indoor temperature setting value is increased to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When Q cut >(Q FC -(N-1)*Q2), the load reduction unit strategy is used as the target control strategy, and the load of one chiller in the central air-conditioning system is reduced, and at the same time, one refrigeration water pump and one cooling water pump are reduced, and the current load rate of the chiller is adjusted to the upper limit of the current load rate of the chiller in the set demand response mode I MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX .

3. A control method for a central air-conditioning system based on power demand response as claimed in claim 2, wherein the energy consumption upper limit Q1 under the parameter adjustment strategy is determined based on the following formula: Q1=Q CHL,MAXDR +Q CHWP,MAXDR +Q CWP,MAXDR +Q COT,MAXDR ; In the formula, Q CHL,MAXDR is the upper limit load of the chiller in demand response mode, Q CHWP,MAXDR is the upper limit load of the chiller pump in demand response mode, Q CWP,MAXDR is the upper limit load of the cooling pump in demand response mode, Q COT,MAXDR is the upper limit load of the cooling tower in demand response mode; The energy consumption upper limit Q2 under the load reduction strategy is determined based on the following formula: Q2=Q CHL,MAXNM +Q CHWP,MAXNM +Q CWP,MAXNM +Q COT,MAXNM ; In the formula, Q CHL,MAXNM is the upper limit load of the chiller in normal operation mode, Q CHWP,MAXNM is the upper limit load of the refrigeration pump in normal operation mode, Q CWP,MAXNM is the upper limit load of the cooling pump in normal operation mode, Q COT,MAXNM is the upper limit load of the cooling tower in normal operating mode; in, Q CHL,MAXNM >Q CHL,MAXDR ,Q CHWP,MAXNM >Q CHWP,MAXDR ,Q CWP,MAXNM >Q CWP,MAXDR ,Q COT,MAXNM >Q COT,MAXD 。 4. A control system for a central air-conditioning system based on power demand response, characterized in that: include: A load prediction module, used to predict air conditioning load based on a characteristic parameter set, wherein the characteristic parameter set at least includes outdoor meteorological parameter forecasts, historical operation data, and building characteristic parameters; A load evaluation module, used to determine the amount of power load that can be reduced under different control strategies of the central air-conditioning system based on equipment parameters, wherein the equipment parameters at least include an upper limit of the current load rate of the chiller of the central air-conditioning system and an upper limit of the auxiliary equipment; an air conditioning control module, used to obtain a reduction amount of the power demand response, and further used to determine a target control strategy of the central air conditioning system based on the reducible power load amount and the reduction amount of the power demand response under the different control strategies, and control the operation of the central air conditioning system based on the target control strategy; The load forecasting module is also used for: The air conditioning load Q is predicted based on the characteristic parameter set by using the ARIMA regression algorithm. FC ; The control strategy includes parameter adjustment strategy and load reduction unit strategy; The load assessment module is also used for: According to the upper limit of the current load rate of the chiller in the demand response mode, I MAX,DR , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXDR , Cooling pump frequency operating upper limit FRQ CWP,MAXDR And the frequency operating upper limit FRQ of the cooling tower COT,MAXDR , determine the upper limit of energy consumption Q1 under the parameter adjustment strategy, combine the number of running chillers N, calculate the total upper limit of energy consumption of the central air-conditioning system as N*Q1, combine the predicted air-conditioning load Q FC , calculate the power load reduction (Q FC -N*Q1); According to the set upper limit of the chiller current load rate I in normal operation mode MAX,NM , Refrigeration pump frequency operating upper limit FRQ CHWP,MAXNM , Cooling pump frequency operating upper limit FRQ CWP,MAXNM , Cooling tower frequency operating upper limit FRQ COT,MAXNM , determine the upper limit of energy consumption Q2 under the load reduction strategy, and combine the number of chillers in operation after load reduction N-1 to calculate the upper limit of total energy consumption of the central air-conditioning system as (N-1)*Q2, combined with the predicted air-conditioning load Q FC , determine the amount of power load (Q) that can be reduced by the central air-conditioning system under the load reduction strategy FC -(N-1)*Q2).

5. A control system for a central air-conditioning system based on power demand response as claimed in claim 4, characterized in that: The air conditioning control module is also used for: When the power demand response reduction amount Q cut <(Q FC -N*Q1), the parameter adjustment strategy is used as the target control strategy to adjust the current load rate of the chiller to the upper limit I of the current load rate of the chiller in the set demand response mode. MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When (Q FC -N*Q1)≤Q cut ≤(Q FC -(N-1)*Q2), the load reduction unit strategy is used as the target control strategy, and a chiller unit is reduced from the central air-conditioning system, and a chilled water pump and a cooling water pump are reduced at the same time, and the indoor temperature setting value is increased to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX ; When Q cut >(Q FC -(N-1)*Q2), the load reduction unit strategy is used as the target control strategy, and the load of one chiller in the central air-conditioning system is reduced, and at the same time, one refrigeration water pump and one cooling water pump are reduced, and the current load rate of the chiller is adjusted to the upper limit of the current load rate of the chiller in the set demand response mode I MAX,DR , adjust the frequency of the refrigeration pump to the upper limit FRQ of the frequency of the refrigeration pump in the set demand response mode CHWP,MAXDR , adjust the frequency of the cooling pump to the upper limit FRQ of the cooling pump frequency under the set demand response mode CWP,MAXDR And adjust the frequency of the cooling tower to the upper frequency operating limit FRQ of the cooling tower in the set demand response mode COT,MAXDR , and at the same time, adjust the indoor temperature setting value to the upper limit of the indoor temperature confidence interval T indoor,MAX , adjust the chilled water supply temperature to the upper limit of the supply temperature confidence interval T CHWS,MAX .

6. A control system for a central air-conditioning system based on power demand response as claimed in claim 5, characterized in that: The load assessment module is also used for: The energy consumption upper limit Q1 under the parameter adjustment strategy is determined based on the following formula: Q1=Q CHL,MAXDR +Q CHWP,MAXDR +Q CWP,MAXDR +Q COT,MAXDR ; In the formula, Q CHL,MAXDR is the upper limit load of the chiller in demand response mode, Q CHWP,MAXDR is the upper limit load of the chiller pump in demand response mode, Q CWP,MAXDR is the upper limit load of the cooling pump in demand response mode, Q COT,MAXDR is the upper limit load of the cooling tower in demand response mode; The energy consumption upper limit Q2 under the load reduction strategy is determined based on the following formula, including: Q2=Q CHL,MAXNM +Q CHWP,MAXNM +Q CWP,MAXNM +Q COT,MAXNM ; In the formula, Q CHL,MAXNM is the upper limit load of the chiller in normal operation mode, Q CHWP,MAXNM is the upper limit load of the refrigeration pump in normal operation mode, Q CWP,MAXNM is the upper limit load of the cooling pump in normal operation mode, Q COT,MAXNM is the upper limit load of the cooling tower in normal operating mode; Among them, Q CHL,MAXNM > Q CHL,MAXDR , Q CHWP,MAXNM > Q CHWP,MAXDR , Q CWP,MAXNM > Q CWP,MAXDR , Q COT,MAXNM > Q COT,MAXD .

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