An air conditioning system overall collaborative optimization method based on lowest annual refrigeration energy consumption

Abstract

The application discloses a kind of based on the whole year refrigeration energy consumption minimum air conditioning system overall collaborative optimization method, the energy consumption module of the air conditioning system is coupled based on heat balance, the coupling and the constraint relationship between the dynamic cold and heat load variation characteristics of building whole year, the operation water supply temperature of different time cold water and system static design parameter are fully considered, and with the minimum total energy consumption of air conditioning system whole year as control target, through collaborative optimization, accurate and reliable obtain the design parameter and operation control parameter of air conditioning system based on whole system whole year working condition overall high energy consumption.

Description

Technical Field

[0001] This invention belongs to the field of building energy consumption control technology, specifically involving a method for overall collaborative optimization of air conditioning systems based on minimizing annual cooling energy consumption. Background Technology

[0002] In building energy consumption, air conditioning systems account for a particularly large proportion, making them a key area for building energy conservation.

[0003] Common large-scale chilled water air conditioning systems are mostly in the form of chiller units + combined air conditioners. The main energy-consuming modules of this air conditioning system include chiller units, chilled water pumps, cooling water pumps, combined air conditioner units and cooling towers.

[0004] Although there is a great deal of research on air conditioning system optimization technology, the following problems still exist: (1) Most optimization studies focus on a single component of the system, only considering the impact of a single optimization strategy on the energy consumption of that component, ignoring the mutual influence of the operation of different parts of the air conditioning system, and making it impossible to determine whether the optimized result satisfies the optimal overall energy efficiency of the system; (2) Studies generally make unreasonable simplifications to the terminal units and do not analyze based on the actual thermal balance, resulting in simulations that fail to accurately reflect the actual operating conditions of the air conditioning system; (3) The coupling relationship between system operating control parameters and design parameters is ignored. Design parameters determine the system configuration. In the face of dynamic changes in load throughout the year, the operating parameters with the lowest energy consumption should be determined based on the existing equipment capacity. Existing studies generally do not consider this factor, resulting in inaccurate energy consumption data and affecting the conclusions. The above problems lead to inaccurate calculated energy consumption data and unsatisfactory optimization effects of the air conditioning system. Summary of the Invention

[0005] To address the problems of inaccurate calculation results and unsatisfactory optimization effects of existing technologies due to their focus on only local aspects, unreasonable simplification of terminal components, or neglect of the coupling relationship between design parameters and operational control parameters, this invention provides a method for overall collaborative optimization of an air conditioning system based on minimizing annual cooling energy consumption. This invention couples the various energy-consuming modules of the air conditioning system based on thermal balance, fully considering the coupling and constraints between factors such as the building's dynamic annual cooling and heating load variations, chilled water supply temperatures at different times, and the system's static design parameters. With the goal of minimizing the total annual energy consumption of the air conditioning system, collaborative optimization accurately and reliably obtains the design parameters and operational control parameters of the air conditioning system based on the overall high energy consumption of the entire system throughout the year.

[0006] This invention is achieved through the following technical solution:

[0007] A method for overall collaborative optimization of an air conditioning system based on minimizing annual cooling energy consumption, the method comprising:

[0008] Based on the indoor and outdoor air calculation parameters, calculation load and surface cooler technical parameters, and on the basis of thermal balance, the design parameter cluster that meets the basic conditions is determined.

[0009] Under the design parameter cluster, initial operating parameters are set, and the energy consumption is calculated hourly throughout the year using the air conditioning system energy consumption model. By iteratively changing the operating parameters, the system searches for optimization to obtain the operating parameters corresponding to the lowest energy consumption of the air conditioning system under the current design parameters. The optimized energy consumption and operating parameters are then output. The air conditioning system energy consumption model is based on the thermal balance of the air conditioning system and is obtained by coupling the various energy consumption modules of the air conditioning system.

[0010] By traversing the set of design parameters and repeating the optimization process, the energy consumption and corresponding operating parameters of all design parameters that meet the conditions after optimization can be obtained.

[0011] Among all the energy consumption values ​​after optimizing the design parameters that meet the conditions, the design parameters and operating parameters corresponding to the minimum energy consumption are obtained, which are the optimal design parameters and operating parameters of the air conditioning system.

[0012] Compared with existing technologies, the overall collaborative optimization method proposed in this invention constructs an overall energy consumption model of the air conditioning system based on thermal balance, couples different design parameters and system operation control parameters, takes the minimum energy consumption as the optimization objective, and thus obtains the optimal design parameters and system operation parameters, which can improve the optimization performance of the air conditioning system.

[0013] As a preferred embodiment, the energy consumption model of the air conditioning system of the present invention is expressed as follows:

[0014] P = P chiller +P chilledpump +P condpump +P tower +P fan

[0015] Where P is the total energy consumption of the air conditioning system; P chiller Energy consumption of the chiller unit; P chilledpump Energy consumption of chilled water pump; P condpump Energy consumption of cooling water pump; P tower Energy consumption of the cooling tower; P fan This refers to the energy consumption of the air conditioning unit.

[0016] As a preferred embodiment, the energy consumption model of the conventional chiller unit for direct cooling according to the present invention is expressed as follows:

[0017]

[0018] Among them, P chiller Energy consumption of the chiller unit; Q ref Rated cooling capacity of the chiller unit; COP refRated energy efficiency of the chiller unit; CAPFT is the correction factor for the chiller unit's cooling capacity based on water temperature; EIRFT is the correction factor for the chiller unit's power based on water temperature; EIRPLR is the correction factor for the chiller unit's power based on part load rate.

[0019] The energy consumption model for water-cooled chiller units is expressed as follows:

[0020]

[0021] Among them, P waterstorage Energy consumption of the main unit of the water-cooled storage system; CAPFT water EIRFT is the correction factor for the cooling capacity of a water-storage chiller unit based on water temperature. water EIRPLR is the correction factor for the power output of a water-storage chiller unit based on water temperature. water This is the correction factor for the power of the water storage chiller unit based on the partial load rate;

[0022] The energy consumption model for ice storage chiller units is expressed as follows:

[0023]

[0024] Among them, P icestorage Energy consumption of the ice storage system; Q ice,ref Q ref These are the rated capacities of the unit during ice storage and direct supply, respectively; COP ice,ref COP ref These are the energy efficiency figures for the unit during ice storage and direct supply, respectively; CAPFT ice CAPFT and EIRFT are correction factors for the cooling capacity of water temperature during ice storage chiller operation and direct supply, respectively; ice EIRFT and EIRPLR are the correction factors for power output based on water temperature during ice storage and direct supply, respectively. ice EIRPLR and EIRPLR are the partial load correction factors for ice storage chillers during ice storage and direct supply, respectively.

[0025] As a preferred embodiment, the energy consumption model of the chilled water pump of the present invention is expressed as follows:

[0026]

[0027] Among them, G water H1 is the mass flow rate of chilled water; H1 is the head of the chilled water pump; η1 is the efficiency of the chilled water pump.

[0028] mass flow rate G of chilled water water Due to the influence of load demand and the temperature difference between supply and return water, the following formula is used for calculation:

[0029]

[0030] Where Q is the terminal load demand; c is the specific heat of water; T cw,l T cw,e These are the supply water temperature and return water temperature of the chilled water, respectively.

[0031] As a preferred embodiment, the energy consumption model of the cooling water pump of the present invention is expressed as follows:

[0032]

[0033] Among them, G coud water H2 is the mass flow rate of the cooling water; H2 is the head of the cooling water pump; η2 is the efficiency of the cooling water pump.

[0034] As a preferred embodiment, the cooling tower energy consumption model of the present invention is expressed as follows:

[0035]

[0036] Among them, P tower For the cooling tower fan energy consumption; G tower air η is the air volume of the cooling tower; p is the ventilation resistance of the cooling tower; ρ is the air density; η3 is the fan efficiency.

[0037] As a preferred embodiment, the energy consumption model of the air conditioning unit of the present invention is expressed as follows:

[0038]

[0039] Among them, P fan Energy consumption of the air conditioning unit; P is the total fan pressure after removing the surface cooler; G is the total energy consumption of the air conditioning unit. air P is the mass flow rate of air. coil,dry P coil,wet ρ represents the resistance of the surface cooler under dry and wet conditions, respectively; ρ is the air density; and η is the fan efficiency.

[0040] In a preferred embodiment, the design parameter cluster determination process of the present invention includes:

[0041] The air volume is obtained based on the air temperature difference.

[0042] Determine the air supply point parameters and air mixing point parameters based on the indoor and outdoor air calculation parameters, calculate the surface cooler contact coefficient that satisfies the thermal and humid process, and find the oncoming wind speed v1 that satisfies the thermal and humid process of the surface cooler based on the surface cooler contact coefficient.

[0043] Based on the air supply volume and the technical parameters of the standard model of the surface cooler, the windward area under the standard model of the surface cooler is found, and the actual wind speed v2 is calculated.

[0044] Determine if the supply air temperature difference is greater than the maximum allowable supply air temperature difference. If it is, the iteration ends and the design parameter corresponding to the minimum face velocity difference, i.e., min|v1-v2|, is found. If not, the iteration does not end, and the supply air temperature difference is changed and the above process is repeated.

[0045] As a preferred embodiment, the operating parameter control strategy of the present invention is as follows:

[0046] Based on the input parameters, the cooling season is divided into several cooling periods;

[0047] The operating parameters for each cooling period are calculated separately. The specific calculation process is as follows:

[0048] Set the initial chilled water supply temperature;

[0049] Steps for calculating the required cooling capacity of the surface cooler: Calculate the required cooling capacity Q1 of the surface cooler at the current moment;

[0050] Set the initial return temperature of chilled water;

[0051] The actual cooling capacity of the surface cooler is calculated as follows: Calculate the chilled water flow rate and the water velocity in the coil, and then calculate the heat transfer coefficient and logarithmic mean temperature difference of the surface cooler to obtain the actual cooling capacity Q2 of the surface cooler.

[0052] Determine if the return water temperature iteration is complete. If not, change the return water temperature and return to the step of calculating the actual cooling capacity of the surface cooler. If yes, store the minimum value of the surface cooler cooling capacity difference, i.e., the return water temperature corresponding to min|Q1-Q2|, and calculate the air conditioning system energy consumption at the current supply water temperature and return water temperature at the current time.

[0053] Determine whether all time points in the current cooling period have been calculated. If not, use the next time point as the current time point and return to execute the step of calculating the cooling capacity to be processed by the surface cooler. If yes, sum up the air conditioning energy consumption of all time points to obtain the air conditioning system energy consumption for the current cooling period and the current water supply temperature.

[0054] Determine if the water supply temperature iteration is complete. If not, change the water supply temperature and return to the step of calculating the cooling capacity required by the surface cooler. If yes, output the minimum energy consumption of the air conditioning system during the current cooling period and its corresponding water supply temperature.

[0055] Based on the minimum energy consumption of the air conditioning system during all cooling periods, the total energy consumption of the air conditioning system for the entire cooling season is obtained and output.

[0056] On the other hand, this invention proposes an overall collaborative optimization system for air conditioning systems based on minimizing annual cooling energy consumption. This system includes:

[0057] Design parameter determination module: Based on indoor and outdoor air calculation parameters, calculation load and surface cooler technical parameters, and based on thermal balance, determine the design parameter cluster that meets the basic conditions and pass it to the year-round optimization module;

[0058] The year-round optimization module: After receiving the design parameter cluster from the design parameter determination module, it sets initial operating parameters under the design parameter cluster, calculates energy consumption hourly throughout the year using the air conditioning system energy consumption model, and iterates through the operating parameters to find the operating parameters corresponding to the lowest energy consumption of the air conditioning system under the current design parameters. It then outputs the optimized energy consumption and operating parameters to the output module. The air conditioning system energy consumption model is based on the thermal balance of the air conditioning system and is obtained by coupling the various energy consumption modules of the air conditioning system.

[0059] Output module: From the energy consumption of all the design parameters that meet the conditions output by the annual optimization module, obtain the design parameters and operating parameters corresponding to the minimum energy consumption and output them as the optimal design parameters and operating parameters of the air conditioning system.

[0060] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0061] 1. This invention comprehensively considers the coupling effects of various energy-consuming modules in the air conditioning system, takes thermal balance as the basis, and aims to minimize the overall energy consumption of the system. It performs collaborative optimization of the system, while fully considering factors such as the dynamic load variation characteristics of the building throughout the year, the operation under varying water temperature conditions at different times, and the coupling and constraint relationship between the static design parameters and dynamic operating parameters of the system. Through collaborative optimization, it can accurately and reliably obtain the design parameters and operation control parameters of the air conditioning system based on the overall high energy efficiency of the entire system throughout the year, thereby ensuring the optimization effect of the air conditioning system.

[0062] 2. This invention establishes a heat and humidity treatment model for the system terminal, i.e., the surface cooler, according to actual conditions, avoiding calculation errors caused by assuming the terminal as an ideal heat exchange model, thereby further improving the optimization effect of the air conditioning system. Attached Figure Description

[0063] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and form part of this application, do not constitute a limitation thereof. In the drawings:

[0064] Figure 1 Schematic diagram of the collaborative optimization principle of the air conditioning system.

[0065] Figure 2 This is a schematic diagram illustrating multi-dimensional and multi-parameter optimization.

[0066] Figure 3 A flowchart for the overall collaborative optimization method of the air conditioning system.

[0067] Figure 4 This is a schematic diagram of the thermal balance relationship of the surface cooler.

[0068] Figure 5 Flowchart for determining design parameters.

[0069] Figure 6 This is a flowchart of the process for controlling operating parameters. Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0071] Example:

[0072] Most existing technologies focus only on local aspects, making it difficult to achieve optimal total system energy consumption. They also generally simplify the terminal components unreasonably, failing to accurately reflect the actual operating status of the air conditioning system. Furthermore, they neglect the coupling relationship between system design parameters and operating parameters, resulting in inaccurate energy consumption calculations and unsatisfactory optimization effects. To address these issues, this embodiment proposes a comprehensive collaborative optimization method for air conditioning systems based on minimizing annual cooling energy consumption. This method first establishes a comprehensive energy consumption model of the air conditioning system based on thermal balance. Then, it couples different design parameters and system operation control parameters, using minimum energy consumption as the control objective to obtain the optimal design parameters and system operation control parameters, thereby accurately and reliably achieving the minimum total energy consumption of the air conditioning system. Figure 1-2 As shown.

[0073] Specifically, such as Figure 3 As shown, the optimization method proposed in this embodiment includes the following steps:

[0074] Step 1: Based on the indoor and outdoor air calculation parameters, calculation load, and surface cooler technical parameters, determine the design parameter cluster that meets the basic conditions based on thermal balance.

[0075] Step 2: Under the design parameter cluster, set the initial operating parameters, calculate the energy consumption hourly throughout the year using the air conditioning system energy consumption model, and iterate through the operating parameters to find the lowest energy consumption of the air conditioning system under the current design parameters. Then, output the optimized energy consumption and operating parameters. The air conditioning system energy consumption model is based on the thermal balance of the air conditioning system and is obtained by coupling the various energy-consuming modules of the air conditioning system.

[0076] Step 3: By traversing the design parameter cluster and repeating the optimization process in Step 2, the energy consumption and corresponding operating parameters after optimization of all design parameters that meet the conditions can be obtained.

[0077] Step 4: Among all the energy consumption values ​​after optimizing the design parameters that meet the conditions, obtain the design parameters and operating parameters corresponding to the minimum energy consumption. These are the optimal design parameters and operating parameters for the air conditioning system.

[0078] In one alternative implementation, for large-scale air conditioning systems, the common form of cold source is a chiller unit, and the terminal units mostly adopt an all-air system, that is, a combined air handling unit (AHU) to centrally process the air and deliver it to the indoor space in the form of all-air. The main energy-consuming modules of this typical air conditioning system include the chiller unit, chilled water pump, cooling water pump, combined air handling unit, and cooling tower. Each energy-consuming component will be modeled, and a system collaborative optimization model will be established based on this.

[0079] The expression for the energy consumption model of the air conditioning system is:

[0080] P = P chiller +P chilledpump +P condpump +P tower +P fan

[0081] Where P is the total energy consumption of the air conditioning system; P chiller Energy consumption of the chiller unit; P chilledpump Energy consumption of chilled water pump; P condpump Energy consumption of cooling water pump; P tower Energy consumption of the cooling tower; P fan This refers to the energy consumption of the air conditioning unit.

[0082] The operation of an air conditioning system is the result of the coupling of its various components, with the terminal units being the key to system operation: the heat exchange capacity on the air side of the terminal units directly determines the indoor thermal and humidity environment, while the heat exchange capacity on the water side determines the parameters of the distribution system. Through heat exchange on the air and water sides and their mutual coupling, the heat pump, distribution system, and terminal units are interconnected to form a complete system. This embodiment comprehensively considers the coupling effects of each component and optimizes the system based on thermal balance. The optimization goal is to minimize the total energy consumption P of the air conditioning system while ensuring the cooling effect.

[0083] Considering that chiller units have multiple cooling modes, such as direct cooling or cooling storage via water or ice, the energy consumption models for chiller units are established below for each of these different cooling modes:

[0084] (1) Conventional chiller system

[0085] The mathematical model used to calculate the energy consumption of chiller units is shown in the following formula:

[0086]

[0087] CAPFT = a + b(T) cw,l )+c(T cw,l ) 2 +d(T cond,e )+e(T cond,e ) 2 +f(T cw,l (T) cond,e )

[0088] EIRFT = a1 + b1(T) cw,l )+c1(T cw,l ) 2 +d1(T cond,e )+e1(T cond,e ) 2 +f1(T cw,l (T) cond,e )

[0089] EIRPLR = a² + b²(PLR) + c²(PLR) 2

[0090] Among them, P chiller Energy consumption of the chiller unit; Q ref Rated cooling capacity of the chiller unit; COP ref Rated energy efficiency of the chiller unit; CAPFT is the correction factor for the chiller unit's cooling capacity based on water temperature; EIRFT is the correction factor for the chiller unit's power based on water temperature; EIRPLR is the correction factor for the chiller unit's power based on part load rate.

[0091] The correction factor can be obtained by fitting the variable operating characteristics given in the chiller unit sample. The ASHRAE standard provides the coefficient values ​​for a certain chiller unit. When the actual operating characteristics of the chiller unit cannot be obtained, the values ​​can also be calculated based on the data in the table.

[0092] Reference for Chiller Unit Operation Correction Curve Coefficient

[0093] Correction curve a b c d e f CAPFT 0.257183345 0.0387941020 -0.00021678 0.04673887 -0.0009402350 -0.000342491 EIRFT 0.933678591 -0.058199196 0.00449937 0.002429466 0.000485893 -0.001214733 EIRPLR 0.222903 0.31387 0.46371 —— —— ——

[0094] (2) Water-cooled system

[0095] Water-based cooling is an energy-saving air conditioning system that utilizes the peak-valley electricity price difference in the power grid. At night, chillers store cold water in storage tanks, and during the day, the chilled water is released while the main chiller operates to avoid peak hours. The energy consumption calculation formula for the chiller unit in a water-based cooling system is as follows:

[0096]

[0097] In the formula, P waterstorage Energy consumption of the main unit of the water-cooled storage system, kW; Q refRated cooling capacity of the chiller unit; COP ref Rated energy efficiency of the chiller unit; CAPFT water EIRFT is the correction factor for the cooling capacity of a water-storage chiller unit based on water temperature. water EIRPLR is the correction factor for the power output of a water-storage chiller unit based on water temperature. water This is the correction factor for the power of a water-storage chiller unit based on its partial load rate.

[0098] Among them, EIRFT water The value of should take into account the cold storage demand, the cold supply demand, and the cold release capacity simultaneously, and should be calculated according to the following formula.

[0099]

[0100] In the formula, Q terminal For the cooling demand at the terminal; Q release Q represents the amount of cold released from the cold storage tank. storage This refers to the cold storage capacity of the cold storage tank.

[0101] (3) Ice storage system

[0102] Ice storage is a method of making ice from water and storing cold energy using the latent heat of phase change of ice. Because ice storage chiller units are dual-mode units, operating differently during cold storage and cooling, the energy consumption of an ice storage air conditioning system should be calculated separately for both cold storage and cooling scenarios using the following formula:

[0103]

[0104] Among them, P icestorage Energy consumption of the ice storage system; Q ice,ref Q ref These are the rated capacities of the unit during ice storage and direct supply, respectively; COP ice,ref COP ref These are the energy efficiency figures for the unit during ice storage and direct supply, respectively; CAPFT ice CAPFT and EIRFT are correction factors for the cooling capacity of water temperature during ice storage chiller operation and direct supply, respectively; ice EIRFT and EIRPLR are the correction factors for power output based on water temperature during ice storage and direct supply, respectively. ice EIRPLR and EIRPLR are the partial load correction factors for ice storage chillers during ice storage and direct supply, respectively.

[0105] EIRPLR ice The EIRPLR calculation formula is as follows:

[0106]

[0107]

[0108] In the formula, Q terminal For the cooling demand at the terminal; Q release Q represents the cooling capacity released by the ice storage system. storage This refers to the amount of cold storage capacity of the ice storage system.

[0109] The energy consumption model of chilled water pumps can be expressed as:

[0110]

[0111] Among them, G water H1 is the mass flow rate of chilled water; H1 is the head of the chilled water pump; η1 is the efficiency of the chilled water pump.

[0112] G water The cold water flow rate is affected by load demand and the temperature difference between the supply and return water, and can be calculated using the following formula:

[0113]

[0114] Where Q is the terminal load demand; c is the specific heat of water; Tcw,l, T cw,e These are the supply water temperature and return water temperature of the chilled water, respectively.

[0115] The chilled water supply / return water temperature and terminal load demand are coupled through the heat exchange characteristics of the terminal, and must be coupled with the heat exchange of the terminal to be determined.

[0116] The cooling water system consists of a cooling water pump, a chiller unit, and a cooling tower. The cooling water flows through the chiller unit's condenser to carry away the heat from the refrigerant inside the main unit. The cooling water pump sends the heated cooling water into the cooling tower to exchange heat with the outdoor air. The cooled cooling water then returns to the chiller unit's condenser.

[0117] The Michael enthalpy difference method is commonly used for thermal calculations of cooling towers. The basic equations for the thermodynamic parameters of cooling towers are shown below:

[0118]

[0119] In the formula, β is the volumetric mass transfer coefficient of the cooling tower packing expressed as the difference in moisture content; V is the volume of the cooling tower packing; Q is the cooling water flow rate; C w t is the specific heat capacity of water; K is the heat dissipation coefficient of evaporating water; a t b The inlet and outlet water temperatures of the cooling tower; i″ t Let t be the enthalpy of saturated air at water temperature t; i is the enthalpy of air.

[0120] The difference between the outlet water temperature and the wet-bulb air temperature of a cooling tower is called the cooling range. The wet-bulb air temperature is the limit temperature at which the cooling tower can handle water. When the cooling water temperature is close to the wet-bulb air temperature, the enthalpy difference within the cooling tower is small, resulting in low heat dissipation. Therefore, the cooling range is generally taken as 3–5°C. The ASHRAE manual recommends the following formula for calculating the cooling range:

[0121] T approach =Coeff(1)+Coeff(2)(FR air )+Coeff(3)(FR air ) 2 +Coeff(4)(FR air ) 3 +Coeff(5)(FR water )+Coeff(6)(FR air (FR) water )+Coeff(7)(FR air ) 2 (FR water )+Coeff(8)(FR water ) 2 +Coeff(9)(FR air (FR) water ) 2 +Coeff(10)(FR water ) 3 +Coeff(11)(T wb )+Coeff(12)(FR air (T) wb )+Coeff(13)(FR air ) 2 (T wb )+Coeff(14)(FR water (T) wb )+Coeff(15)(FR air (FR) water (T) wb )+Coeff(16)(FR water ) 2 (T wb )+Coeff(17)(T wb ) 2 +Coeff(18)(FR air (T) wb ) 2 +Coeff(19)(FR water (T) wb ) 2 +Coeff(20)(T wb ) 3+Coeff(21)(T r )+Coeff(22)(FR air (T) r )+Coeff(23)(FR air ) 2 (T r )+Coeff(24)(FR water (T) r )+Coeff(25)(FR air (FR) water (T) r )+Coeff(26)(FR water ) 2 (T r )+Coeff(27)(T wb (T) r )+Coeff(28)(FR air (T) wb (T) r )+Coeff(29)(FR water (T) wb (T) r )+Coeff(30)(T wb ) 2 (T r )+Coeff(31)(T r ) 2 +Coeff(32)(FR air (T) r ) 2 +Coeff(33)(FR water (T) r ) 2 +Coeff(34)(T wb (T) r ) 2 +Coeff(35)(T r ) 3

[0122] In the formula, T approach The difference between the outlet water temperature and the inlet air wet-bulb temperature of the cooling tower is required for high cooling range; FR air FR is the airflow ratio, the ratio of actual airflow to design airflow. water T is the ratio of actual water flow to design water flow; r T is the difference between the inlet and outlet water temperatures of the cooling tower. wb is the wet-bulb temperature of the inlet air; Coeff is a coefficient, the values ​​of which are shown in the table below.

[0123] Coefficient value table

[0124] Coeff(1) 0.520497098 Coeff(2) -10.6170464 Coeff(3) 10.72929747 Coeff(4) -2.74988377158227 Coeff(5) 4.736299439 Coeff(6) -8.257597009 Coeff(7) 1.57640938114136 Coeff(8) 6.51119643791324 Coeff(9) 1.504335252 Coeff(10) -3.288852929 Coeff(11) 0.02577861453538 Coeff(12) 0.182464289 Coeff(13) -0.081894729 Coeff(14) -0.21501000399629 Coeff(15) 0.01867413096353 Coeff(16) 0.053682418 Coeff(17) -0.00270969 Coeff(18) 0.001122775 Coeff(19) -0.00127758497498 Coeff(20) 7.60420796601607E-05 Coeff(21) 1.436000883 Coeff(22) -0.5198695909109 Coeff(23) 0.11733957691051 Coeff(24) 1.504928108 Coeff(25) -0.135898906 Coeff(26) -0.152577582 Coeff(27) -0.05338438281146 Coeff(28) 0.004932949 Coeff(29) -0.00796260394174 Coeff(30) 0.00022262

[0125] The mass flow rate of the cooling water is:

[0126]

[0127] COP stands for Chiller Energy Efficiency.

[0128] Based on this, the energy consumption model of the cooling water pump can be expressed as:

[0129]

[0130] Among them, G coud water H2 is the mass flow rate of the cooling water; H2 is the head of the cooling water pump; η2 is the efficiency of the cooling water pump.

[0131] The air-to-water ratio λ is the ratio of the air volume to the water volume in a cooling tower, representing the number of kilograms of air required to cool one kilogram of water. The air-to-water ratio is a crucial parameter in cooling tower calculations; a higher ratio generally indicates greater cooling capacity. Typically, λ is between 0.8 and 1.5. Based on the determined air-to-water ratio, the amount of air entering the cooling tower can be calculated.

[0132] G tower air =λ×G cond water

[0133] Where λ is the air-to-water ratio; G tower air This refers to the air volume in the cooling tower.

[0134] The main energy-consuming component of a cooling tower is the fan; therefore, the energy consumption model of a cooling tower can be represented as follows:

[0135]

[0136] Among them, P tower η is the cooling tower fan energy consumption; p is the cooling tower ventilation resistance; ρ is the air density; η3 is the fan efficiency.

[0137] Combined air conditioning units (AHUs) use surface coolers to treat the heat and humidity of the air. This air treatment process is a multi-factor coupled process. The chilled water from the main unit reaches the terminal units via the distribution system and then exchanges heat with the air through the surface coolers. The characteristics of the surface coolers, water temperature, water flow rate, and air flow rate all influence the heat exchange process. After heat exchange, the chilled water, now at a higher temperature, returns to the main unit. The air-side treatment process of the surface coolers directly affects the AHU's fan energy consumption and the indoor thermal and humidity environment, while the water-side treatment process affects the chilled water system's distribution energy consumption and the main unit's energy consumption. Therefore, the air heat and humidity treatment process of the surface coolers is a key area for coordinated optimization.

[0138] Under certain operating conditions, whether the surface cooler can process air to the required point is determined by the combined parameters of the air side, water side, and the characteristic parameters of the surface cooler. Current research largely ignores this process, assuming the terminal unit is an ideal heat exchange model, meaning that under any conditions, the terminal equipment can provide the required cooling capacity at fixed supply and return water temperatures. This simplified design neglects the coupling effect between modules in the system, making collaborative optimization impossible. Therefore, this embodiment establishes a thermal and humidity treatment model for the surface cooler based on actual conditions, and performs collaborative analysis and optimization of each module.

[0139] Based on the relationship between the surface temperature of the surface cooler and the air state, the air handling by the surface cooler can be divided into two states: dry process and wet process.

[0140] When the surface temperature of the cooler is lower than the dry-bulb temperature of the air being processed, but still higher than its dew point temperature, the air is cooled without condensation. This process is called isothermal cooling or dry cooling. If the surface temperature of the cooler is lower than the dew point temperature of the air, the air is not only cooled, but the water vapor it contains will also partially condense and form a water film on the finned tube surface of the cooler. This process is called dehumidification cooling or wet cooling. In this process, a saturated air boundary layer will form around the water film, and not only sensible heat exchange, but also mass exchange and the resulting latent heat exchange will occur between the processed air and the cooler.

[0141] The increased heat transfer due to moisture exchange is represented by the moisture removal coefficient. The formula for calculating the moisture removal coefficient of a surface cooler is as follows:

[0142]

[0143] Among them, dQ t dQ represents the total heat exchange rate; dQ represents the sensible heat exchange rate.

[0144] Whether a surface cooler can process air to the target state, and to what state, is primarily determined by its contact coefficient. The contact coefficient is a crucial parameter in the thermal calculations of surface coolers in practical engineering, representing how close the actual temperature drop of the air within the cooler is to the ideal temperature drop. The formula for calculating the contact coefficient of a surface cooler is shown below:

[0145]

[0146] Among them, t1, t s1 The dry-bulb and wet-bulb temperatures of the air before treatment; t2, t s2 t3 represents the dry-bulb and wet-bulb temperatures of the treated air; t3 represents the final dry-bulb temperature of the air when the surface cooler is operating under ideal conditions (with sufficient contact time).

[0147] The contact coefficient is mainly determined by the number of rows of the surface cooler and the air velocity on the air side. The larger the contact coefficient, the stronger the dehumidification capacity of the surface cooler when handling the same air volume. Existing studies have derived the relationship between the contact coefficient of various models of water-cooled surface coolers and the number of rows and the oncoming air velocity through experiments and theoretical calculations.

[0148] Taking the JW-type cooler as an example, the contact coefficients corresponding to different numbers of rows and oncoming wind speeds are shown in the table below.

[0149] JW type surface cooler contact coefficient

[0150]

[0151] The main factors affecting the heat transfer coefficient of finned tube heat exchangers, commonly used in air conditioning engineering, include the heat transfer coefficients of their inner and outer surfaces and the moisture removal coefficient. The heat transfer coefficient of the outer surface of the heat exchanger is related to the face velocity or mass flow velocity of the air, while the heat transfer coefficient of the inner surface is related to the flow velocity of water within the heat exchanger tubes. The moisture removal coefficient is related to the state of the air being processed and the water temperature inside the tubes. The experimental formula for the heat transfer coefficient of the heat exchanger in practical engineering is shown below:

[0152]

[0153] Among them, v y denoted as , where is the face velocity of the air being processed as it passes through the surface cooler; w is the flow velocity of water within the surface cooler tubes; A and B are experimentally derived coefficients, dimensionless; m, n, and p are experimentally derived exponents, dimensionless.

[0154] The heat transfer coefficients of some surface coolers are shown in the table below.

[0155] Table of values ​​for heat transfer coefficient calculation for surface cooler

[0156] A m p B n 2nd row 42.1 0.52 1.03 331.6 0.8 4 rows 39.7 0.52 1.03 332.6 0.8 6 rows 41.5 0.52 1.02 325.6 0.8 8 rows 35.5 0.58 1.0 353.6 0.8

[0157] Establish such as Figure 4 The thermal balance relationship of the surface cooler is shown. For the air side, the heat change due to the decrease in air enthalpy is considered to be Q1, calculated using the following formula:

[0158] Q1 = G air (h1-h2)

[0159] Where Q1 represents the heat change caused by the change in air enthalpy; G air h1 represents the mass flow rate of air; h2 and h1 represent the enthalpy values ​​of the air at the inlet and outlet of the surface cooler, respectively.

[0160] The enthalpy of air can be expressed as a function of the dry-bulb temperature and the wet-bulb temperature, i.e., h = f(t, t sAs the analysis above shows, the wet-bulb temperature of the air at the outlet of the surface cooler can be related to the state parameters at the inlet of the surface cooler through the contact coefficient. Therefore, the above formula can be modified as follows:

[0161]

[0162] For the water side, the cold water in the coil absorbs heat, causing its temperature to rise. The absorbed heat is Q2, which can be calculated using the following formula:

[0163] Q2 = G water c(T cw,e -T cw,l )

[0164] In the formula, Q2 represents the heat absorbed by the cold water in the coil; G water T is the mass flow rate of chilled water. cw,l T cw,e These are the supply and return temperatures of the chilled water, respectively.

[0165] For the surface cooler, assuming the heat transfer between water and air through the surface cooler is Q3, it can be calculated using the following formula:

[0166]

[0167] Based on the thermal equilibrium relationship, we can obtain the following equation:

[0168] Q1 = Q2 = Q3

[0169] The equations for the heat and humidity treatment of air by the surface cooler are as follows:

[0170]

[0171] By solving the above formula, important parameters such as return water temperature, outlet air temperature, and moisture extraction rate can be obtained.

[0172] For combined air conditioning units, the main energy-consuming component is the fan, and the energy consumption model calculation formula is as follows:

[0173]

[0174] Among them, P fan P represents the energy consumption of the air conditioning unit; P is the total fan pressure after removing the surface cooler; P coil,dry P coil,wet ρ represents the resistance of the surface cooler under dry and wet conditions, respectively; ρ is the air density; and η is the fan efficiency.

[0175] Based on this, with the goal of minimizing the annual energy consumption of the air conditioning system, the expression is as follows:

[0176]

[0177] One alternative implementation involves calculating air parameters, determining design parameters, and controlling operating parameters during the optimization process.

[0178] In the optimization calculation process, a large number of different air parameters are solved. Other air state parameters are solved based on two known independent air parameters, including but not limited to dry-bulb temperature, wet-bulb temperature, relative humidity, moisture content, enthalpy, etc.

[0179] Based on the calculated indoor and outdoor air parameters, calculated load (sensible heat and latent heat), and the technical parameters of the surface cooler, and based on thermal balance, a set of design parameters that meet the basic conditions is determined, including supply water temperature, supply and return water temperature difference, and supply air status parameters, etc. The specific process is as follows: Figure 5 As shown. The process for determining this design parameter cluster includes:

[0180] Step 11, input parameters, including sensible heat / latent heat load at the design point, outdoor calculation parameters, indoor calculation parameters, and surface cooler technical parameters;

[0181] Step 12, set the initial supply air temperature difference;

[0182] Step 13: Obtain the air volume based on the air supply temperature difference;

[0183] Step 14: Determine the air supply point parameters and air mixing point parameters based on indoor and outdoor air calculation parameters;

[0184] Step 15: Calculate the contact coefficient of the surface cooler that satisfies the thermal and humid process based on the air supply point parameters and the air mixing point parameters. Then, find the oncoming wind speed v1 that satisfies the thermal and humid process of the surface cooler based on the contact coefficient of the surface cooler.

[0185] Step 16: Based on the air supply volume and the technical parameters of the standard model of the surface cooler, find out the windward area of ​​the standard model of the surface cooler and calculate the actual wind speed v2.

[0186] Step 17: Determine if the supply air temperature difference is greater than the maximum allowable supply air temperature difference. If yes, the iteration ends, and the design parameters corresponding to the minimum face velocity difference, i.e., min|v1-v2|, are found (including the selection of the surface cooler, the design supply air temperature difference, the design supply air volume, and the cooling capacity to be handled by the surface cooler). If no, the iteration does not end, and the supply air temperature difference is changed to return to step 13 for the next face velocity calculation.

[0187] Air conditioning systems are designed based on the worst-case operating conditions. However, in actual operation, outdoor meteorological parameters, population density, lighting, and equipment usage often differ from the design conditions. This results in the air conditioning system operating at partial load most of the time. Therefore, the air conditioning system should adopt reasonable operating strategies (changing the chilled water supply temperature) to meet indoor usage and comfort needs and reduce system energy consumption.

[0188] In this embodiment, the main focus is on controlling the water supply temperature of the chiller during operation. The water supply temperature of the chiller directly affects the energy consumption of the main unit and the heat exchange capacity of the terminal surface cooler, which in turn causes changes in the water volume of the system and changes in the energy consumption of the water pump.

[0189] There are two main basic control strategies: one is to keep the water supply temperature constant during partial load conditions and reduce the terminal supply flow to adapt to the load, thereby reducing transmission and distribution energy consumption; the other is to increase the water supply temperature. In this case, compared to the case where the water supply temperature remains constant, the flow rate increases when the water supply temperature is increased, leading to increased transmission and distribution energy consumption, but the energy consumption of the main unit is reduced. Therefore, it is necessary to comprehensively weigh the weight relationship between the energy consumption of the main unit and the energy consumption of the water pump to find the optimal water supply temperature and ensure that the overall energy consumption of the system is minimized.

[0190] Based on the design parameters, dynamic calculations are performed hourly throughout the year, and the optimal system operating parameters are found within a given time period. In this embodiment, this mainly refers to the water supply temperature, ensuring the lowest possible annual energy consumption for system operation. The specific process is as follows: Figure 6 As shown:

[0191] Step 21: Based on the input parameters, including building parameters, hourly sensible / latent heat load, hourly outdoor air calculation parameters, indoor air calculation parameters, and design point calculation results, divide the cooling season into m cooling periods.

[0192] Step 22, i = i + 1, calculate the operating parameters for the i-th cooling period, with the initial value of i being 1.

[0193] Step 23: Set the initial chilled water supply temperature;

[0194] Step 24, j = j + 1, calculate the cooling capacity Q1 that the surface cooler needs to handle at the j-th time (the initial value of j is 1);

[0195] Step 25: Set the initial return temperature of chilled water;

[0196] Step 26: Calculate the chilled water flow rate and the water velocity in the coil, and then calculate the heat transfer coefficient and logarithmic mean temperature difference of the surface cooler to obtain the actual cooling capacity Q2 of the surface cooler.

[0197] Step 27: Determine whether the return water temperature iteration is complete. If not, change the return water temperature and return to step 26. If yes, store the minimum value of the surface cooler cooling capacity difference, i.e., the return water temperature corresponding to min|Q1-Q2|, and calculate the air conditioning system energy consumption P(i,j) at that time and under that return water temperature.

[0198] Step 28: Determine if all time periods for the cooling period have been calculated. If not, return to step 24; if yes, sum the air conditioning energy consumption for all time periods to obtain the air conditioning system energy consumption for the cooling period at the specified water supply temperature.

[0199] Step 29: Determine if the water supply temperature iteration is complete. If not, change the water supply temperature and return to step 24. If yes, output the minimum air conditioning system energy consumption for the cooling period.

[0200] Step 30: Determine if all cooling periods have been calculated. If not, return to step 22; if yes, sum the air conditioning energy consumption for all cooling periods. The total energy consumption of the air conditioning system for the entire cooling season is obtained and output.

[0201] This embodiment proposes an overall collaborative optimization system for air conditioning systems based on minimizing annual cooling energy consumption. The system includes:

[0202] The design parameter determination module determines the set of design parameters that meet the basic conditions based on the indoor and outdoor air calculation parameters, calculation load and surface cooler technical parameters, and then passes them to the annual optimization module.

[0203] The year-round optimization module, upon receiving the design parameter set from the design parameter determination module, sets initial operating parameters under the design parameter set, calculates energy consumption hourly throughout the year using the air conditioning system energy consumption model, and iteratively changes the operating parameters to perform optimization, obtaining the operating parameters corresponding to the lowest energy consumption of the air conditioning system under the current design parameters, and outputs the optimized energy consumption and operating parameters to the output module; wherein, the air conditioning system energy consumption model is based on the thermal balance of the air conditioning system and is obtained by coupling the various energy consumption modules of the air conditioning system;

[0204] The output module extracts and outputs the design and operating parameters corresponding to the minimum energy consumption from all the design parameters that meet the conditions output by the optimization module throughout the year, as the optimal design and operating parameters for the air conditioning system.

[0205] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0206] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0207] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0208] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0209] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An overall collaborative optimization method for an air conditioning system based on the lowest annual refrigeration energy consumption, characterized in that, The method comprises: According to the indoor and outdoor air calculation parameters, the calculation load and the technical parameters of the cooling coil, the design parameter cluster meeting the basic conditions is determined based on the heat balance; Under the design parameter cluster, the initial operation parameters are set, the energy consumption is calculated by the air conditioning system energy consumption model on a yearly hourly basis, and the operation parameters corresponding to the lowest energy consumption of the air conditioning system under the current design parameters are obtained by iterative change of the operation parameters for traversal optimization, and the optimized energy consumption and operation parameters are output; wherein the air conditioning system energy consumption model is coupled by the heat balance of the air conditioning system to obtain each energy consumption module of the air conditioning system; By traversing the design parameter cluster, the optimization process is repeated, and the optimized energy consumption and corresponding operation parameters of all design parameters meeting the conditions are obtained; Among the optimized energy consumption of all design parameters meeting the conditions, the design parameters and operation parameters corresponding to the minimum energy consumption are obtained, which are the optimal design parameters and operation parameters of the air conditioning system; The determination process of the design parameter cluster comprises: According to the supply air temperature difference, the supply air volume is obtained; According to the indoor and outdoor air calculation parameters, the supply air point parameters and the mixing air point parameters are determined, the cooling coil contact coefficient meeting the heat and moisture process is calculated, and the face velocity v1 meeting the cooling coil heat and moisture process is obtained according to the cooling coil contact coefficient; Based on the supply air volume and the technical parameters of the cooling coil standard model, the windward area under the cooling coil standard model is obtained, and the actual face velocity v2 is calculated; It is judged whether the supply air temperature difference is greater than the maximum allowable supply air temperature difference, if yes, the iteration is ended, and the design parameters corresponding to the minimum face velocity difference value, i.e. min|v1-v2|, are found; if not, the iteration is not ended, and the supply air temperature difference is changed to repeat the above process; The method for obtaining the optimal design parameters and operation parameters of the air conditioning system comprises: According to the input parameters, the cooling supply season is divided into several cooling time periods; The operation parameters of each cooling time period are calculated respectively, and the specific calculation process comprises: The initial chilled water supply water temperature is set; The cooling coil required cooling capacity calculation step: the cooling coil required cooling capacity Q1 at the current time is calculated; The initial chilled water return water temperature is set; The cooling coil actual cooling capacity calculation step: the chilled water flow rate and the water flow rate in the coil are calculated to obtain the cooling coil heat transfer coefficient and the logarithmic mean temperature difference, and the cooling coil actual cooling capacity Q2 is obtained; It is judged whether the return water temperature iteration is completed, if not, the return water temperature is changed, and the cooling coil actual cooling capacity calculation step is returned to be executed; if yes, the minimum cooling capacity difference value, i.e. min|Q1-Q2|, corresponding to the return water temperature is stored, and the air conditioning system energy consumption at the current time under the current supply water temperature and return water temperature is calculated; It is judged whether all time periods in the current cooling time period are calculated, if not, the next time is taken as the current time to return to execute the cooling coil required cooling capacity calculation step; if yes, the air conditioning energy consumption of all time periods is summed to obtain the air conditioning system energy consumption under the current supply water temperature in the current cooling time period; determining whether the supply water temperature is iterated, if not, changing the supply water temperature, returning to execute the cooling coil required cooling capacity calculation step; if yes, outputting the minimum air conditioning system energy consumption in the current cooling period and its corresponding supply water temperature; According to the minimum air conditioning system energy consumption of all cooling periods, the total air conditioning system energy consumption in the entire cooling season is obtained and outputted.

2. The overall collaborative optimization method of an air conditioning system based on the lowest energy consumption of refrigeration throughout the year according to claim 1, characterized in that, The air conditioning system energy consumption model is represented as: ； wherein, is the total energy consumption of the air conditioning system; is the energy consumption of the chiller unit; is the energy consumption of the chilled water pump; is the energy consumption of the cooling water pump; is the energy consumption of the cooling tower; is the energy consumption of the air conditioning box.

3. The overall co-optimization method of an air conditioning system based on the lowest energy consumption of refrigeration throughout the year according to claim 2, characterized in that, The energy consumption model of the conventional direct-cooling chiller is represented as: ； wherein, is the rated cooling capacity of the water chiller; is the rated energy efficiency of the water chiller; is the water temperature correction coefficient of the water chiller on the cooling capacity; is the water temperature correction coefficient of the water chiller on the power; is the part load ratio correction coefficient of the water chiller on the power; The energy consumption model of the water storage cooling chiller is represented as: ； wherein, is the main energy consumption of the water storage system; is the correction coefficient of water temperature of the water storage chillers on refrigerating capacity; is the correction coefficient of water temperature of the water storage chillers on power; is the correction coefficient of partial load rate of the water storage chillers on power; The energy consumption model of the ice storage cooling chiller is represented as: ； wherein, is the energy consumption of the ice storage system; , are the rated capacities of the unit when storing ice and when directly supplying, respectively; , are the energy efficiencies of the unit when storing ice and when directly supplying, respectively; , are the correction coefficients of water temperature to refrigerating capacity of the ice storage chiller unit when storing ice and when directly supplying, respectively; , are the correction coefficients of water temperature to power of the ice storage chiller unit when storing ice and when directly supplying, respectively, , are the part load correction coefficients of the ice storage chiller unit when storing ice and when directly supplying, respectively.

4. The overall co-optimization method of an air conditioning system based on the lowest energy consumption of refrigeration throughout the year according to claim 2, characterized in that, The chilled water pump energy consumption model is represented as: ； wherein, is the mass flow rate of chilled water; is the head of the chilled water pump; is the chilled water pump efficiency; Mass flow rate of chilled water Subject to the load demand and the supply and return water temperature difference, the following formula is used for calculation: ； wherein, is the terminal load demand; is the specific heat of water; , is the chilled water supply temperature, respectively, the chilled water return temperature.

5. The overall co-optimization method of an air conditioning system based on the lowest energy consumption of refrigeration throughout the year according to claim 2, characterized in that, The cooling water pump energy consumption model is represented as: ； wherein, is the mass flow rate of the cooling water; is the head of the cooling water pump; is the cooling water pump efficiency.

6. The overall co-optimization method of an air conditioning system based on the lowest energy consumption of refrigeration throughout the year according to claim 2, characterized in that, The cooling tower energy consumption model is represented as: ； wherein, is the cooling tower air quantity; is the cooling tower draft; is the air density; is the fan efficiency.

7. The overall co-optimization method of an air conditioning system based on the lowest energy consumption of refrigeration throughout the year according to claim 2, characterized in that, The air conditioning box energy consumption model is represented as: ； wherein, Pf is the total pressure of the aftercooler fan; is the mass flow rate of air; , Pd, dry and Pd, wet are the resistances of the aftercooler under dry and wet conditions, respectively; is the air density; is the fan efficiency.

8. An overall collaborative optimization system for an air conditioning system based on the lowest annual refrigeration energy consumption, characterized in that, The system comprises, The design parameter determination module: according to the indoor and outdoor air calculation parameters, the calculated load and the technical parameters of the cooling coil, the design parameter cluster meeting the basic conditions is determined based on the heat balance, and is transmitted to the annual optimization module; The annual optimization module: after receiving the design parameter cluster transmitted by the design parameter determination module, the initial operating parameters are set under the design parameter cluster, the energy consumption is calculated hour by hour in the entire year by using the air conditioning system energy consumption model, and the operating parameters are changed by iteration for traversal optimization, the operating parameters corresponding to the minimum air conditioning system energy consumption under the current design parameters are obtained, and the optimized energy consumption and operating parameters are outputted to the output module; wherein, the air conditioning system energy consumption model is coupled by the heat balance of the air conditioning system to obtain each energy consumption module of the air conditioning system; The output module: from all the optimized energy consumption of the design parameters meeting the conditions outputted by the annual optimization module, the design parameters and operating parameters corresponding to the minimum energy consumption are obtained and outputted as the optimal design parameters and operating parameters of the air conditioning system; The determination process of the design parameter cluster comprises: According to the supply air temperature difference, the supply air volume is obtained; According to the indoor and outdoor air calculation parameters, the supply air point parameters and the air mixing point parameters are determined, the cooling coil contact coefficient meeting the heat and moisture process is calculated, and the face velocity v1 meeting the heat and moisture process of the cooling coil is obtained by looking up the cooling coil contact coefficient; Based on the supply air volume and the technical parameters of the cooling coil standard model, the windward area under the cooling coil standard model is obtained, and the actual face velocity v2 is calculated; determining whether the supply air temperature difference is greater than the maximum allowable supply air temperature difference, if yes, the iteration is ended, the design parameters corresponding to the minimum face velocity difference value min|v1-v2| are found; if not, the iteration is not ended, the supply air temperature difference is changed and the above process is repeated; The method for obtaining the optimal design parameters and operating parameters of the air conditioning system comprises: According to the input parameters, the cooling season is divided into several cooling periods; The operating parameters of each cooling period are calculated respectively, and the specific calculation process is as follows: setting the initial chilled water supply temperature; cooling coil required cooling capacity calculation step: calculating the cooling coil required cooling capacity Q1 at the current time; setting the initial chilled water return temperature; cooling coil actual cooling capacity calculation step: calculating the chilled water flow rate and the water flow rate in the coil, so as to calculate the cooling coil heat transfer coefficient and the logarithmic mean temperature difference, and obtain the cooling coil actual cooling capacity Q2; determining whether the return water temperature is iterated, if not, changing the return water temperature, returning to execute the actual processing cold quantity calculation step of the table cooler; if yes, storing the return water temperature corresponding to the minimum value of the table cooler cold quantity difference, i.e. min|Q1-Q2|, and calculating the air conditioning system energy consumption at the current time under the current supply water temperature and return water temperature; determining whether all time points in the current cooling period are calculated, if not, taking the next time point as the current time point to return to execute the table cooler processing cold quantity calculation step; if yes, summing the air conditioning energy consumption of all time points to obtain the air conditioning system energy consumption under the current supply water temperature in the current cooling period; determining whether the supply water temperature is iterated, if not, changing the supply water temperature, returning to execute the table cooler processing cold quantity calculation step; if yes, outputting the minimum air conditioning system energy consumption in the current cooling period and the corresponding supply water temperature; obtaining the total air conditioning system energy consumption in the entire cooling season according to the minimum air conditioning system energy consumption in all cooling periods and outputting.

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