Central air conditioner chilled water system and energy-saving optimization control method

Abstract

The invention relates to the technical field of energy-saving optimization of central air conditioners, and discloses an energy-saving optimization control method for a chilled water system of a central air conditioner, which comprises the following steps: establishing a target function to construct an energy consumption model based on the composition of chilled water circulation and cooling water circulation modules; constraint conditions are established based on chilled water circulation and cooling water circulation module optimization; calculating parameter settings in the chilled water circulation and the cooling water circulation based on a binary particle swarm algorithm, and performing optimization; according to the central air conditioner chilled water system and the energy-saving optimization control method, energy-saving optimization control over the chilled water system is achieved on the basis of optimized parameter setting, and by constructing energy consumption models of all modules, target functions and constraint conditions needed by optimization are established; and according to a binary particle swarm algorithm, calculating and optimizing parameter setting in a chilled water circulation and cooling water circulation module in the system, and based on optimized parameters, automatically adjusting operation parameters of the chilled water system in a load period so as to realize an effect of efficient and energy-saving optimization control on the system.

Description

Technical Field

[0001] The present invention relates to the technical field of central air-conditioning energy-saving optimization, and specifically provides a central air-conditioning chilled water system and an energy-saving optimization control method therefor. Background Art

[0002] A central air-conditioning system consists of one or more cold and heat source systems and multiple air-conditioning systems. By using the principle of liquid vaporization refrigeration, it provides the required cooling capacity for the air-conditioning system to offset the heat load of the indoor environment. The heating system provides the required heat for the air-conditioning system to offset the cooling and heating loads of the indoor environment. The chilled water system is a crucial part of the central air-conditioning system, and its type, operation mode, structural form, etc. directly affect the economy, efficiency, and rationality of the central air-conditioning system during operation.

[0003] Currently, in the prior art, the conventional control method for the central air-conditioning chilled water system is to control and manage the lower-level machine controller by using a constant or manually modified set value. This is prone to energy waste and poor control characteristics during partial load, and it is impossible to optimize and adjust the system operation parameters according to the change of the air-conditioning load during partial load. Therefore, it is necessary to propose a central air-conditioning chilled water system and an energy-saving optimization control method that can minimize the energy consumption of the system on the premise of meeting the system load requirements and ensuring the system stability. Summary of the Invention

[0004] (1) Technical Problems to be Solved

[0005] Aiming at the deficiencies of the prior art, the present invention provides a central air-conditioning chilled water system and an energy-saving optimization control method, which have the advantage of being able to automatically optimize and adjust the operation parameters to reduce the system energy consumption, and solve the problems that in some central air-conditioning chilled water systems in the prior art, it is inconvenient to optimize and adjust the operation parameters, and there is a large energy loss during partial load.

[0006] (2) Technical Solutions

[0007] To achieve the above purpose of automatically optimizing and adjusting the operation parameters to reduce the system energy consumption, the present invention provides the following technical solutions: A central air-conditioning chilled water system includes a refrigeration host module for installing refrigeration unit equipment and generating chilled water through refrigerant circulation;

[0008] A chilled water circulation module for transporting the chilled water to the terminal equipment to achieve heat exchange;

[0009] A cooling water circulation module for discharging the heat generated during the operation of the refrigeration equipment;

[0010] A voltage stabilization processing module for maintaining the water quality stability and system pressure of the chilled water output;

[0011] The end heat exchange module is used to install heat exchange equipment to realize the heat exchange between chilled water and air;

[0012] The makeup and drainage module is used to replace the circulating water quality and supplement the water quality loss during the refrigeration process;

[0013] The system monitoring module is used to realize automatic monitoring and the regulation and operation of the air conditioning system;

[0014] The energy-saving module is used to improve the energy efficiency of the air conditioning system.

[0015] Preferably, the refrigeration host module includes a compressor, a condenser, an evaporator and a throttling component. The throttling component includes an expansion valve and a capillary tube for regulating the refrigerant flow. The chilled water circulation module includes a chilled water pump, a pipeline system, a valve assembly and monitoring instruments. The chilled water pump is divided into a primary pump and a secondary pump. The pipeline system includes a water supply pipe, a return pipe, a water distributor and a water collector. The monitoring instruments include a pressure gauge, a thermometer and a flow meter.

[0016] Preferably, the cooling water circulation module includes a cooling water pump, a cooling tower and a water treatment device. The water treatment device includes a descaling instrument, a dosing device and a side filter. The pressure stabilizing treatment module includes a pressure stabilizing device composed of an expansion tank, a pressure vessel and a makeup water pump, a water quality softening device, a filter and a sterilization and disinfection device. The end heat exchange module includes an air heat exchange device composed of a fan coil unit, an air handling unit and a fresh air unit. The makeup and drainage module includes a makeup water tank, a pressure makeup valve, a drain pipe and a floor drain.

[0017] An energy-saving optimization control method for a central air-conditioning chilled water system includes the following specific steps:

[0018] S1. Based on the composition of the chilled water circulation and the cooling water circulation modules, establish an objective function to construct an energy consumption model;

[0019] S2. Based on the optimization of the chilled water circulation and the cooling water circulation modules, establish constraint conditions;

[0020] S3. Based on the binary particle swarm optimization algorithm, calculate the parameter settings in the chilled water circulation and the cooling water circulation and optimize them;

[0021] S4. Based on the optimized parameter settings, realize the energy-saving optimization control of the chilled water system.

[0022] Preferably, the specific steps of constructing the objective function based on the energy consumption model in step S1 include:

[0023] 1) Set that on the premise of ensuring the cooling load demand of the end heat exchange equipment, taking the maximum energy saving of the system as the objective function, and set the total energy consumption of the chilled water system as P Wtotal, establish the objective function expression:

[0024] minP Wtotal = P chiller + P CHW1pump + P CHW2pump + P CWpump + P tfan

[0025] where P chiller is the energy consumption of the refrigeration unit, kW; P CHW1pump is the energy consumption of the primary chilled water pump, kW; P CHW2pump is the energy consumption of the secondary chilled water pump, kW; P CWpump is the energy consumption of the cooling water pump, kW; P tfan is the energy consumption of the cooling tower fan, kW;

[0026] 2) Build the energy consumption model of the refrigeration unit, expressed as:

[0027]

[0028] where Q nom is the nominal refrigerating capacity of a single refrigeration unit, kW; Q chiller is the actual refrigerating capacity, kW; COP nom is the energy efficiency ratio under full load, dimensionless; T CHWS is the inlet temperature of the chilled water of the refrigeration unit, °C; N 1 is the number of operating refrigeration units, a i 、b i are constant coefficients;

[0029] 3) Set the primary chilled water pump to deliver at a constant flow rate, then its energy consumption model is expressed as:

[0030]

[0031] where P CHW1pump,nom is the nominal energy consumption of a single primary chilled water pump, m CHW1 is the actual flow rate, m 3 / s; m CHW1,nom is the nominal flow rate, m 3 / s; N 2 is the number of operating primary chilled water pumps, d i is a constant coefficient;

[0032] Set the secondary chilled water pump to deliver at a variable speed, then its energy consumption model is expressed as:

[0033]

[0034] where m CHW2 is the water flow rate of the secondary chilled water pump, m 3 / s; HCHW2 is the head of the secondary chilled water pump, m; η CHW2 is the efficiency of the secondary chilled water pump, %; g w is a constant, N 3 is the number of operating units of the secondary chilled water pump;

[0035] 4) Build the energy consumption models of the cooling water pump and the cooling tower fan, which are respectively expressed as:

[0036]

[0037] where m CW is the water flow rate of the cooling water pump, m 3 / s; H CW is the head of the cooling water pump, m; η CW is the efficiency of the cooling water pump, %; N 4 is the number of operating units of the cooling water pump;

[0038]

[0039] where Q tfan is the air volume of the cooling tower fan, m 3 / s; ΔP tfan is the total pressure of the cooling tower fan, Pa; η tfan is the efficiency of the cooling tower fan, %; N 5 is the number of operating units of the cooling tower fan, g tfan is a constant.

[0040] Preferably, the specific steps of constructing the constraint conditions in step S2 include:

[0041] 1) According to the refrigeration capacity and chilled water flow rate constraints of the refrigeration unit, establish an energy balance expression as:

[0042] N 1 Q chiller = m CHW2 ·C pw ·(T CHWS - T CHWR )

[0043] where C pw is the specific heat of water, kJ / (kg·°C); T CHWR is the outlet water temperature of the refrigeration unit, and the outlet water temperature is set to 7°C;

[0044] 2) According to the chilled water circulation process, construct a mass balance expression as:

[0045]

[0046] where m U,iThe chilled water flow rate of the i-th terminal heat exchange equipment passing by, m 3 / s;

[0047] 3) Considering the matching relationship between the chilled water pump and the cooling water pump, it is set that the number of chilled water pumps and cooling water pumps is equal during operation, then N 4 = N 2 + N 3 ;

[0048] 4) According to the relationship between the water pressure of the secondary chilled water pump and the water flow rate of the terminal heat exchange equipment, the optimized H CHW2 is calculated based on adaptive neuro-fuzzy inference and is expressed as:

[0049]

[0050] where o i,k is the adaptive coefficient, and μ k is the number of fuzzy rules of the linguistic variable related to m U,k ;

[0051] 5) According to the number constraints of the refrigeration unit and the water pump, at least ensure that the refrigeration unit, the primary chilled water pump, and the cooling water pump are in operation and do not exceed the total number, then there is:

[0052]

[0053] 6) It is set that the chilled water temperature entering the refrigeration unit should satisfy:

[0054] T CHWS,min ≤ T CHWS ≤ T CHWS,max

[0055] where T CHWS,min and T CHWS,max are the chilled water temperature parameters set for the refrigeration unit equipment, °C;

[0056] It is set that the chilled water flow rate of the refrigeration unit should satisfy:

[0057] m U,i,min ≤ m U,i ≤ m U,i.max

[0058] where m U,i,min and m U,i.max are the maximum and minimum chilled water flow rate parameters set for the terminal heat exchange equipment, m 3 / s.

[0059] Preferably, the specific steps of implementing energy-saving optimization control based on the binary particle swarm optimization algorithm in step S3 include: 1) Construct a binary particle swarm optimization algorithm model, which is expressed as:

[0060] vid (k + 1)= ωv id (k)+c 1 ·r 1 (k)·[p best,id (k)-x id (k)]+c 2 ·r 2 (k)·[g best,d (k)-x id (k)]

[0061]

[0062] where v id is the velocity vector of particle i in the d-th dimension, x id is the position of particle i in the d-th dimension, p best,id is the individual optimal position of particle i in the d-th dimension, g best,d is the global optimal position found in the d-th dimension, r 1 (k), r 2 (k) and ρ id (k + 1) are random numbers randomly generated within [0, 1], c 1 , c 2 are learning factors, ω is the inertia weight, and k is the current iteration number;

[0063] 2) Minimize P Wtotal while ensuring not to violate the constraint conditions, and construct the fitness function as:

[0064]

[0065] where v i is the penalty factor;

[0066] 3) Initialize the parameters, set the learning factors c 1 and c 2 , and the maximum number of generations is k max , set the initial generation number k = 1, and take (N 1 , N 2 , T CHWS , m U,i ) as particles and define a binary string for each particle as the initial position and initial velocity, and record the global optimal position g best,d and the individual optimal position p best,id of each particle;

[0067] 4) Compare the fitness function of particle x i (k) with the current individual optimal solution p best,i (k). If there exists a relationship:

[0068] fitness(x i (k)) < fitness(p best,i (k))

[0069] Then update the current optimal solution p best,i , and select the one with the minimum fitness function in p best,i (k) as the global optimal solution g best,i (k);

[0070] Compare fitness(g best,i (k)) with the current group optimal solution fitness(g best (k)) of the particle swarm. If there exists a relational expression:

[0071] fitness(g best,i (k)) < fitness(g best (k))

[0072] Then update the current optimal solution g best (k);

[0073] 5) Update the particle position and velocity, and determine whether the current iteration number k max has reached the maximum iteration number or all particles have obtained the optimal solution. If the condition is met, stop the iteration, and use the obtained (N 1 , N 2 , T CHWS , m U,i ) as the optimized parameter setting. Otherwise, update k * = k + 1, and repeat the operation in step 4).

[0074] (III) Beneficial Effects

[0075] Compared with the prior art, the present invention provides a central air - conditioning chilled - water system and an energy - saving optimization control method, having the following beneficial effects:

[0076] This central air - conditioning chilled - water system and energy - saving optimization control method, by constructing the energy - consumption models of each module, establishing the objective function and constraint conditions required for optimization, and calculating and optimizing the parameter settings in the chilled - water circulation and cooling - water circulation modules of the system according to the binary particle swarm algorithm, automatically adjusts the operating parameters of the chilled - water system during the load period based on the optimized parameters to achieve the effect of efficient energy - saving optimization control. Brief Description of the Drawings

[0077] Figure 1 is the flow chart of the energy - saving optimization control method for the central air - conditioning chilled - water system of the present invention;

[0078] Figure 2 is the schematic diagram of the modules of the central air - conditioning chilled - water system of the present invention;

[0079] Figure 3 This is a simulation data graph of the impact of optimizing the number of operating devices of the present invention on system energy consumption;

[0080] Figure 4 This is a simulation data graph of the impact of optimizing the inlet water temperature of the refrigeration unit of the present invention on system energy consumption;

[0081] Figure 5 This is a simulation data graph of the impact of optimizing the differential pressure between the supply and return water of the chilled water of the present invention on system energy consumption. Detailed implementation manners

[0082] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the embodiments and drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0083] Embodiment 1

[0084] In this embodiment, the system monitoring module is composed of a sensing controller, a sensing device unit, an execution unit, and an interaction unit. The sensing device unit includes temperature, pressure, flow rate, and differential pressure sensors. The execution unit includes an inverter and an electric valve for adjusting the speeds of the water pump and the fan. The interaction unit is composed of a control panel and a central monitoring software; the energy-saving module is composed of a variable-frequency drive unit and a heat recovery unit. The variable-frequency drive system is used to control the variable-frequency water pump and the variable-frequency cooling tower fan, and the heat recovery unit is used to recover the condensation heat to save energy consumption;

[0085] The overall control process of the chilled water system includes:

[0086] 1) Refrigeration cycle: After the system detects the cooling demand of the terminal heat exchange equipment, the refrigeration unit is started. First, the compressor compresses the low-temperature and low-pressure gaseous refrigerant into a high-temperature and high-pressure gas, which is sent to the condenser. The cooling water from the cooling tower absorbs the heat of the refrigerant to condense the refrigerant into a high-pressure liquid. The liquid refrigerant enters the evaporator after being depressurized and cooled by the throttling device, and the chilled water is further cooled by the evaporation and heat absorption of the refrigerant;

[0087] 2) Cooling capacity transmission and distribution: The system controls the primary pump to operate at a constant flow rate, directly pumping the chilled water from the evaporator to the water distributor. Then, the secondary pump adjusts the speed of the secondary pump through the inverter according to the load change of the terminal equipment to achieve variable flow transmission. At this time, the water distributor distributes the low-temperature chilled water to each branch, and then enters the terminal equipment and exchanges heat with the air through the surface cooler. After the chilled water absorbs heat and warms up, it is collected by the water collector and returned to the evaporator;

[0088] 3) Cooling water circulation and heat discharge: Start the cooling water pump to pump the cooling water from the condenser outlet to the cooling tower. In the tower, the cooling water is evenly sprayed on the filler through the water distributor. After full contact with the air, it evaporates and dissipates heat. The fan is used for ventilation to accelerate heat discharge. The cooled cooling water returns to the condenser to achieve the cooling water circulation effect. The side filter and dosing device can continuously remove impurities to prevent scaling and microbial growth.

[0089] 4) Temperature adjustment of terminal equipment: The fan coil unit drives air through the coil through the fan, transferring the chilled water cooling capacity to the indoor environment. The air handling unit mixes the fresh air and the return air, filters and cools them, and then sends them to various areas of the room through the air duct. At the same time, the condensed water generated by the terminal equipment is discharged to the floor drain through the drain pipe to prevent water accumulation and bacterial growth;

[0090] 5) Dynamic adjustment of the control system: Based on temperature, pressure and flow sensors, the chilled water supply and return water temperature and pipeline pressure difference and other parameters are monitored in real time. At this time, the DDC controller adjusts the compressor frequency, water pump speed and cooling tower fan start and stop control according to load changes, and controls the flow of each branch through the electric regulating valve to balance the system hydraulics;

[0091] 6) Energy-saving and optimized operation: Based on variable frequency technology, energy consumption can be reduced by reducing the speed of the chilled water pump, cooling water pump and fan at partial load, and the heat of the condenser can be recovered and used for domestic hot water or heating, further reducing energy consumption.

[0092] Embodiment 2

[0093] In this embodiment, the effects of optimizing the number of equipment, the water inlet temperature of the refrigeration unit, and the pressure difference between the supply and return water of chilled water on the energy consumption and energy saving optimization of the system are studied respectively, including:

[0094] 1) Impact of optimizing the number of equipment in operation on system energy consumption

[0095] Combination Figure 3 In the simulation data, the traditional energy-saving control method is to adjust the number of chillers according to the actual cooling load of the air-conditioning system, and at the same time adjust the number of corresponding cooling water pumps and chilled water primary pumps;

[0096] Through the optimization of the binary particle swarm algorithm, the number of operating units and pumps can be determined according to the minimum energy consumption of the objective function. Compared with the traditional method, when the load is an intermediate value (12.6-19.8kW), it can save about 10% of the average energy consumption compared with the traditional method. At high load (19.8-21.4kW) and low load (10.9-12.6kW), the total energy consumption of the two methods is close to the same.

[0097] 2) Impact of unit inlet water temperature optimization on system energy consumption

[0098] Combined with Figure 4 the simulation data in [reference], the traditional method is to fix the inlet temperature T of the chiller CHWS , and change the chilled water flow rate to meet the load demand. According to the overall energy-saving goal of the system, the inlet temperature T of the chiller CHWS varies with the load, and compared with the traditional method, it can save about 7% of the average energy consumption on average;

[0099] 3) Influence of chilled water supply and return pressure difference optimization on system energy consumption

[0100] Combined with Figure 5 the simulation data in [reference], the traditional method is to use a fixed supply and return pressure difference H CHW2 to ensure that there is enough chilled water in the terminal heat exchange equipment under various conditions, and ensure that the supply and return pressure difference H of the chilled water CHW2 varies with the load. Under full load conditions, the secondary chilled water pump is in full-speed operation, and the total energy consumption of the two methods approaches the same. Under partial load, by ensuring that at least one chilled water valve is fully open, the speed of the secondary chilled water pump is reduced, and at this time, the average energy consumption can be reduced by about 8%.

[0101] In summary, for this central air-conditioning chilled water system and energy-saving optimization control method, by constructing the energy consumption models of each module, establishing the objective function and constraint conditions required for optimization, and calculating and optimizing the parameter settings in the chilled water circulation and cooling water circulation modules of the system according to the binary particle swarm optimization algorithm, automatically adjusting the operating parameters of the chilled water system during the load period based on the optimized parameters to achieve the effect of efficient energy-saving optimization control.

[0102] The relevant modules involved in this system are all hardware system modules or functional modules that combine computer software programs or protocols in the prior art with hardware. The computer software programs or protocols themselves involved in this functional module are all well-known technologies to those skilled in the art, and they are not the improvements of this system; the improvement of this system is the interaction relationship or connection relationship between each module, that is, the overall structure of the system is improved to solve the corresponding technical problems to be solved by this system.

[0103] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A central air conditioning chilled water system, characterized in that: It includes a refrigeration host module, which is used to install refrigeration unit equipment and generate chilled water through refrigerant circulation; Chilled water circulation module, used to transport chilled water to terminal equipment to achieve heat exchange; Cooling water circulation module, used to discharge the heat generated by the operation of refrigeration equipment; The pressure stabilization module is used to maintain the stability of the water quality and system pressure of the chilled water output; The terminal heat exchange module is used to install heat exchange equipment to achieve heat exchange between chilled water and air; The water supply and drainage module is used to replace the circulating water and replenish the water loss during the refrigeration process; System monitoring module, used to realize automatic monitoring and air conditioning system control operation; Energy-saving module for improving the energy efficiency of air-conditioning systems.

2. A central air conditioning chilled water system according to claim 1, characterized in that: The refrigeration host module includes a compressor, a condenser, an evaporator and a throttling component. The throttling component includes an expansion valve and a capillary tube for adjusting the refrigerant flow. The chilled water circulation module includes a chilled water pump, a piping system, a valve assembly and a monitoring instrument. The chilled water pump is divided into a primary pump and a secondary pump. The piping system includes a water supply pipe, a return pipe, a water distributor and a water collector. The monitoring instrument includes a pressure gauge, a thermometer and a flow meter.

3. A central air conditioning chilled water system according to claim 1, characterized in that: The cooling water circulation module includes a cooling water pump, a cooling tower and a water treatment device. The water treatment device includes a descaling device, a dosing device and a bypass filter. The pressure stabilization treatment module includes a pressure stabilization device composed of an expansion water tank, a pressure tank and a water supply pump, a water softening device, a filter and a sterilization and disinfection device. The terminal heat exchange module includes an air heat exchange equipment composed of a fan coil, an air handling unit and a fresh air unit. The drainage module includes a water supply tank, a pressure water supply valve, a drain pipe and a floor drain.

4. A central air-conditioning chilled water system energy-saving optimization control method, characterized in that: The specific steps include: S1. Based on the chilled water cycle and cooling water cycle modules, establish the objective function to construct the energy consumption model; S2. Establish constraint conditions based on the optimization of chilled water cycle and cooling water cycle modules; S3. Calculate and optimize the parameter settings in the chilled water cycle and the cooling water cycle based on the binary particle swarm algorithm; S4. Implement energy-saving optimization control of the chilled water system based on the optimized parameter settings.

5. A central air-conditioning chilled water system energy-saving optimization control method according to claim 4, characterized in that: The specific steps of constructing the objective function based on the energy consumption model in step S1 include: 1) Under the premise of ensuring the cooling load demand of the terminal heat exchange equipment, the objective function is to maximize the energy consumption of the system and set the total energy consumption of the chilled water system as P Wtotal , establish the objective function expression: Where P chiller is the energy consumption of the refrigeration unit, kW; P CHW1pump P is the energy consumption of the chilled water primary pump, kW; CHW2pump is the energy consumption of the chilled water secondary pump, kW; P CWpump is the energy consumption of cooling water pump, kW; P tfan is the energy consumption of cooling tower fan, kW; 2) Construct the energy consumption model of the refrigeration unit, expressed as: Where Q nom is the nominal cooling capacity of a single refrigeration unit, kW; Q chiller is the actual cooling capacity, kW; COP nom is the energy efficiency ratio under full load, which is a dimensionless number; T CHWS is the chilled water inlet temperature of the refrigeration unit, ℃; N1 is the number of refrigeration units in operation, a i 、b i is a constant coefficient; 3) If the chilled water primary pump is set to deliver at a constant flow rate, its energy consumption model is expressed as: in is the nominal energy consumption of a single chilled water primary pump, m CHW1 is the actual flow rate, m 3 / s;m CHW1,nom is the nominal flow rate, m 3 / s; N2 is the number of chilled water primary pumps in operation, d i is a constant coefficient; Assuming the chilled water secondary pump is variable speed delivery, its energy consumption model is expressed as: Where m CHW2 is the water flow rate of the chilled water secondary pump, m 3 / s;H CHW2 is the head of the chilled water secondary pump, m; η CHW2 is the efficiency of the chilled water secondary pump, %; g w is a constant, N3 is the number of operating chilled water secondary pumps; 4) Construct the energy consumption model of cooling water pump and cooling tower fan, which are expressed as: Where m CW is the water flow rate of the cooling water pump, m 3 / s;H CW is the head of the cooling water pump, m; η CW is the efficiency of the cooling water pump, %; N4 is the number of cooling water pumps in operation; Where Q tfan is the air volume of the cooling tower fan, m 3 / s; ΔP tfan is the total pressure of the cooling tower fan, Pa; η tfan is the efficiency of the cooling tower fan, %; N5 is the number of cooling tower fans in operation, g tfan is a constant.

6. A central air-conditioning chilled water system energy-saving optimization control method according to claim 4, characterized in that: The specific steps of constructing the constraint conditions in step S2 include: 1) According to the cooling capacity of the refrigeration unit and the chilled water flow constraints, the energy balance expression is established as follows: N1Q chiller =m CHW2 ·C pw ·(T CHWS -T CHWR ) Among them C pw is the specific heat of water, kJ / (kg·℃); T CHWR The outlet water temperature of the refrigeration unit is set to 7°C. 2) According to the chilled water cycle process, the mass balance expression is constructed as follows: Where m U,i is the chilled water flow rate passing through the i-th terminal heat exchange device, m 3 / s; 3) Considering the matching relationship between the chilled water pump and the cooling water pump, the number of chilled water pumps and cooling water pumps is set to be equal during operation, then N4 = N2 + N3; 4) According to the relationship between the water pressure of the chilled water secondary pump and the water flow of the terminal heat exchanger, the optimized H CHW2 , expressed as: Among them i,k is the adaptive coefficient, μ k For m U,k The number of fuzzy rules related to the linguistic variables; 5) According to the number constraints of refrigeration units and water pumps, at least the refrigeration unit, the primary chilled water pump and the cooling water pump must be in operation and the total number must not exceed: 6) The chilled water temperature entering the refrigeration unit should meet the following requirements: T CHWS,min ≤T CHWS ≤T CHWS,max Where T CHWS,min With T CHWS,max Chilled water temperature parameter set for the refrigeration unit equipment, °C; The chilled water flow rate of the refrigeration unit should be set to meet the following requirements: m U,i,min ≤m U,i ≤m U,i.max Where m U,i,min With m U,i.max The maximum flow rate parameter of chilled water set for the terminal heat exchange equipment, m 3 / s.

7. A central air-conditioning chilled water system energy-saving optimization control method according to claim 4, characterized in that: The specific steps of realizing energy-saving optimization control based on binary particle swarm algorithm in step S3 include: 1) constructing a binary particle swarm algorithm model, which is expressed as: v id (k+1)=ωv id (k)+c1·r1(k)·[p best,id (k)-x id (k)]+c2·r2(k)·[g best,d (k)-x id (k)] where v id is the velocity vector of particle i in the dth dimension, x id is the position of particle i in the dth dimension, p best,id is the individual optimal position of particle i in the dth dimension, g best,d is the optimal position of the group found in the dth dimension, r1(k), r2(k) and ρ id (k+1) is a randomly generated number between [0,1], c1 and c2 are learning factors, ω is the inertia weight, and k is the current number of iterations; 2) Minimize P while ensuring that the constraints are not violated Wtotal , construct the fitness function as: where v i is the penalty factor; 3) Initialize parameters, set learning factors c1 and c2, and the maximum evolutionary number is k max , set the initial evolutionary number k = 1, and change (N1, N2, T CHWS ,m U,i ) as particles and define a binary string for each particle as the initial position and initial velocity, and record the optimal position of the group g best,d and the individual optimal position p of each particle best,id ; 4) Compare particles x i (k) and the individual's current optimal solution p best,i (k)'s fitness function, if there is a relationship: fitness(x i (k))<fitness(p best,i (k)) Then update the current optimal solution p best,i , select p best,i The solution with the smallest fitness function in (k) is taken as the global optimal solution g best,i (k); Will fitness(g best,i (k)) and the particle swarm’s current optimal solution fitness(g best (k)) for comparison, if there is a relationship: fitness(g best,i (k))<fitness(g best (k)) Then update the current optimal solution g best (k); 5) Update the particle position and velocity and determine the current number of iterations k max Whether the maximum number of iterations has been reached or all particles have obtained the optimal solution, if the condition is met, the iteration is stopped and the obtained (N1, N2, T CHWS ,m U,i ) as the optimized parameter setting, otherwise update k * =k+1, repeat step 4).

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