System design parameter optimization method for recovering waste heat from data centers for building heating

Abstract

The present invention discloses a method for optimizing system design parameters for recovering waste heat from a data center for building heating, which belongs to the technical field of waste heat heating. The method comprises: building a numerical simulation model; constructing a system primary energy consumption calculation model based on the built numerical simulation model; wherein the system primary energy consumption calculation model is used to calculate the system primary energy consumption according to the system design parameters; based on the system primary energy consumption calculation model, with the goal of reducing the system primary energy consumption, the data center chilled water heat extraction intermediate temperature and chilled water flow are optimized to obtain the optimal values ​​of the data center chilled water heat extraction intermediate temperature and chilled water flow. By adopting the scheme of the present invention, the optimal heat extraction intermediate temperature and chilled water flow can be obtained, thereby saving the energy consumption of the waste heat recovery system to the greatest extent, and providing a selection basis for the heat pump system and boiler under the optimized parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of waste heat heating, and in particular to a method for optimizing system design parameters for recovering waste heat from a data center for building heating. Background Art

[0002] Data center servers and IT equipment have high power density and run uninterruptedly throughout the year. About 97% of the electricity consumed by IT equipment is converted into heat. Normally, indoor heat generation is directly discharged into the external environment through the air-conditioning system, resulting in a waste of resources. Under the background of carbon neutrality, using data center waste heat resources as a heat source for building heating is not only a way to reduce carbon emissions from building heating, but also an important measure to build a green data center. At present, data center operators are gradually aware of the necessity of waste heat utilization, and have begun to conduct research and development and layout in waste heat recovery. At present, there are many case studies on waste heat recovery heating in the form of water source heat pumps. However, when using data center waste heat for building heating, the first thing to consider is the matching of heat source and user supply and demand, and the reasonable design of system parameters. This is a problem that needs to be solved at present. At present, there is no relevant technical solution to achieve the optimization of system design parameters for recycling data center waste heat for building heating. Summary of the invention

[0003] The present invention provides a method for optimizing system design parameters for recovering waste heat from a data center for use in building heating, so as to fill the technical gap in the relevant field.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0005] In one aspect, the present invention provides a method for optimizing system design parameters for recovering waste heat from a data center for use in building heating. The method for optimizing system design parameters for recovering waste heat from a data center for use in building heating comprises:

[0006] Build a numerical simulation model; wherein the numerical simulation model includes: a data center heat exhaust model, a heat pump model, a boiler energy consumption model, and a centralized water cooling system energy consumption model;

[0007] Based on the constructed numerical simulation model, a system primary energy consumption calculation model is constructed; wherein the system primary energy consumption calculation model is used to calculate the system primary energy consumption according to the system design parameters;

[0008] Based on the constructed system primary energy consumption calculation model, with the goal of reducing the system primary energy consumption, the intermediate temperature of chilled water heat extraction and the chilled water flow rate of the data center are optimized to obtain the optimal values ​​of the intermediate temperature of chilled water heat extraction and the chilled water flow rate of the data center.

[0009] Furthermore, the system design parameters include: local heating outdoor design parameters, central heating system design parameters, data center room side heat removal system design parameters, central water cooling system design parameters, boiler design parameters and heat pump system design parameters; wherein,

[0010] The local heating outdoor design parameters include: local outdoor heating design dry bulb temperature and local outdoor heating wet bulb temperature;

[0011] The design parameters of the central heating system include: building heat load, heating network water supply temperature, heating network return water temperature and heating network water flow;

[0012] The design parameters of the room-side heat removal system of the data center include: the product of the heat transfer coefficient and area of ​​the heat exchanger of the cooling air in the computer room air handler CRAH, the supply air temperature and air volume required for cabinet heat removal, and the heat removal amount of the data center;

[0013] The design parameters of the centralized water cooling system include: the end difference on the condenser side of the chiller, the end difference on the evaporator side of the chiller, the thermal perfection of the chiller, the end difference at the outlet of the natural cooling source, the head of the water pump and the water pump efficiency;

[0014] The boiler design parameters include: boiler thermal efficiency and lower calorific value of natural gas;

[0015] The heat pump system design parameters include: the end difference on the heat pump condenser side, the end difference on the heat pump evaporator side, and the thermal perfection of the heat pump.

[0016] Furthermore, the data center heat removal model is expressed as:

[0017]

[0018] in,

[0019]

[0020] Among them, t ws Indicates the chilled water supply temperature; t wr Indicates the return water temperature; t ar Indicates the return air temperature of the air handling unit in the computer room; t as Indicates the air supply temperature required for cabinet heat dissipation; Q IT Indicates the heat generated by the data center; m a Indicates air supply volume; c pa Represents the specific heat capacity of air; C a represents the heat capacity of air; η represents the heat exchange efficiency when cooling air and chilled water undergo sensible heat exchange in CRAH; C r is the ratio of heat capacity, NTU stands for number of heat transfer units. Cw represents the heat capacity of water; m w Indicates the flow rate of chilled water; c w is the specific heat capacity of water; KF is the product of the heat transfer coefficient and area of ​​the heat exchanger in CRAH; c a is the specific heat capacity of air.

[0021] Further, the heat pump model is expressed as:

[0022] Q cond,hp =m h ×c w ×(t p -t r );

[0023]

[0024] in,

[0025]

[0026] t cond,hp =t p +Δt cond,hp ;

[0027] t evap,hp =t mid -Δt evap,hp ;

[0028] Among them, Q cond,hp Indicates the heat released by the heat pump condenser; W hp Indicates the heat pump compressor power; m h Indicates the water flow rate of the heating network at the heat user side; t p Indicates the temperature of the return water from the heat network after being preheated by the heat pump condenser; t r Indicates the return water temperature of the heating network; t evap,hp and t cond,hp Respectively represent the evaporation temperature and condensation temperature; ε hp Indicates the thermal perfection of the heat pump; Q h represents the heat load of heat users; t s Indicates the water supply temperature of the heating network; t mid Indicates the intermediate temperature of the chilled water after cooling by the heat pump evaporator; Δt cond,hp and Δt evap,hp Represent the end difference of the heat pump condenser side and evaporator side respectively.

[0029] Furthermore, the expression of the boiler energy consumption model is:

[0030]

[0031] Among them, V NG Indicates the amount of gas consumed; ηboiler Indicates boiler efficiency; H indicates the lower calorific value of natural gas.

[0032] Furthermore, the expression of the energy consumption model of the centralized water cooling system is:

[0033]

[0034] in,

[0035] Q evap,ref =m w ×c w ×(t ST,out -t ws );

[0036]

[0037] Among them, W PUMP Indicates the energy consumption of the chilled water system pump; W ref represents the energy consumption of the chiller; r represents the gravity of water; h PUMP Indicates the head of the pump; η PUMP Indicates the efficiency of the pump; Q evap,ref Indicates the cooling capacity of the refrigeration machine; t ST,out Indicates the outlet water temperature after cooling by natural cooling source, t ST,out =Δt ST +t wb , Δt ST Indicates the outlet difference of the natural cooling source, t wb Indicates the local heating design wet bulb temperature; t evap,ref Indicates the evaporation temperature of the chiller, t evap,ref =t ws -Δt evap,ref ;t cond,ref represents the condensation temperature, t cond,ref =t amb +Δt cond,ref ;t amb Indicates the local heating design dry bulb temperature; Δt cond,ref and Δt evap,ref are the terminal differences on the condenser side and the evaporator side of the chiller; ε ref Indicates the thermal perfection of the chiller.

[0038] Furthermore, the expression of the calculation model of the primary energy consumption of the system is:

[0039] m ce =0.1229×(W hp +W ref +W PUMP )+1.33×V NG ;

[0040] Among them, m ce Indicates the primary energy consumption of the system.

[0041] Furthermore, the primary energy consumption calculation model of the system constructed is used to optimize the intermediate temperature and flow rate of chilled water heat extraction in the data center with the goal of reducing the primary energy consumption of the system, and obtain the optimal values ​​of the intermediate temperature and flow rate of chilled water heat extraction in the data center, including:

[0042] Selecting a plurality of different chilled water flow values ​​within a preset process range, and selecting a plurality of different intermediate temperature values ​​within a preset temperature range; wherein the number of the intermediate temperature values ​​matches the number of the chilled water flow values;

[0043] Combining a plurality of different chilled water flow values ​​with a plurality of different intermediate temperature values ​​to obtain a plurality of data combinations; wherein each data combination includes a chilled water flow value and an intermediate temperature value;

[0044] For each data combination, the chilled water flow value and the intermediate temperature value are respectively substituted into the system primary energy consumption calculation model to calculate the system primary energy consumption corresponding to the current data combination;

[0045] The chilled water flow rate value and the intermediate temperature value in the data combination when the system primary energy consumption is the lowest are selected as the optimal values ​​of the intermediate temperature and chilled water flow rate for chilled water heat extraction in the data center.

[0046] On the other hand, the present invention further provides an electronic device, comprising a processor and a memory; wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the above method.

[0047] In yet another aspect, the present invention further provides a computer-readable storage medium, wherein at least one instruction is stored in the storage medium, and the instruction is loaded and executed by a processor to implement the above method.

[0048] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0049] The technical solution of the present invention is based on the method of numerical simulation. Under the design conditions of the heating system, such as the heat load of the heating user, the supply and return water temperature and water supply flow of the heating network, and the operating conditions of the data center, such as the air supply temperature, air supply volume, heat rejection, KF of CRAH, outdoor dry bulb and wet bulb temperatures on the local heating design day, and the two-device end difference and thermodynamic perfection under the design conditions of the heat pump system for heat recovery, the energy consumption of the heat pump system, the energy consumption of the centralized water cooling system and the energy consumption of the boiler system are obtained, and the standard coal conversion coefficients of electricity and gas are used to convert them into primary energy consumption respectively. The primary energy consumption is comprehensively considered, with the goal of reducing the total primary energy consumption of data center cooling and heating building heating. According to the ratio of different building heat loads to the heat rejection of the data center, the intermediate temperature and chilled water flow of the data center are optimized to obtain the optimal intermediate temperature and chilled water flow of the heat under the lowest primary energy consumption. Therefore, the energy consumption of the waste heat recovery system can be saved to the greatest extent, and the selection basis for the heat pump system and boiler can be provided under the optimized parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 It is a schematic diagram of the execution flow of a method for optimizing system design parameters for recovering waste heat from a data center for building heating provided by an embodiment of the present invention;

[0052] Figure 2 This is a flow chart of recovering waste heat from a data center for building heating provided by an embodiment of the present invention;

[0053] Figure 3 is a schematic diagram of a system performance simulation optimization process provided by an embodiment of the present invention;

[0054] Figure 4 It is a schematic diagram of system energy consumption calculation optimization logic provided by an embodiment of the present invention;

[0055] Figure 5 It is a system block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0057] First of all, it should be noted that in the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "exemplarily" is intended to present the concept in a concrete way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0058] First embodiment

[0059] This embodiment provides a method for optimizing system design parameters for recovering waste heat from a data center for building heating. The method can be implemented by an electronic device. The execution process of the method is as follows: Figure 1 As shown, the following steps are included:

[0060] S1, building a numerical simulation model; wherein the numerical simulation model includes: a data center heat exhaust model, a heat pump model, a boiler energy consumption model, and a centralized water cooling system energy consumption model;

[0061] S2, based on the constructed numerical simulation model, construct a system primary energy consumption calculation model; wherein the system primary energy consumption calculation model is used to calculate the system primary energy consumption according to the system design parameters;

[0062] S3, based on the constructed system primary energy consumption calculation model, with the goal of reducing the system primary energy consumption, optimizes the data center chilled water heat extraction intermediate temperature and chilled water flow rate to obtain the optimal values ​​of the data center chilled water heat extraction intermediate temperature and chilled water flow rate.

[0063] The process of recovering waste heat from data centers for building heating is as follows: Figure 2 The data center air conditioning system uses a centralized water cooling system and room-level cooling with cold and hot aisle isolation. The cooling air exchanges heat with the chilled water in the cold source system in the computer room air handler (CRAH), and the temperature changes from t ar Down to t as After that, it is sent to the cabinet to remove the heat dissipation of the server. For the chilled water side, the flow rate is m w The chilled water is sent to the CRAH to cool the cooling air, and the temperature changes from t ws Rise to t wr Then, the chilled water passes through the evaporator of the heat pump before being sent to the natural cooling source or active cooling source system, and the temperature is increased from t wr Drop to the middle temperature t mid If t mid Greater than the required water supply temperature t ws , the chilled water will continue to cool down to t at the natural cooling source or active cooling source wsThe specific operation strategy is as follows:

[0064] When t mid =t ws , no need for refrigeration, open valve 1, close valve 2 and valve 3;

[0065] When t mid >t ws , and the spray tower outlet water temperature t ST,out ≤ Chilled water supply temperature t ws , perform natural cooling, open valve 3, and close valves 1 and 2;

[0066] When t mid >t ws , and t ws <t ST,out <t mid , carry out mixed refrigeration, first rely on the spray tower to complete natural refrigeration, then start the refrigerator for active refrigeration, open valve 2, and close valve 1 and valve 3.

[0067] During the heat recovery process, the heat pump consumes a part of mechanical work to improve the temperature quality of the recovered heat and preheat the return water of the heat network flowing through the condenser side of the heat pump. r Rise to preheat temperature t p If t p The water supply temperature of the heating network cannot be reached s When the gas boiler is needed to supplement the remaining heat, the specific operation strategy is as follows:

[0068] When the preheating temperature t p Less than the water supply temperature t s When , open valve 4 and close valve 5;

[0069] When the preheating temperature t p Equal to the water supply temperature t s When , open valve 5 and close valve 4.

[0070] Based on the above, the system performance simulation optimization process proposed in this embodiment is as follows: Figure 3 As shown, the process is as follows:

[0071] The performance of the above-mentioned “data center waste heat heating” process is analyzed using numerical simulation methods.

[0072] The numerical simulation models built include: data center heat exhaust model, heat pump model, boiler energy consumption model and centralized water cooling system energy consumption model. The specific description of each model is as follows:

[0073] (1) Data Center Heat Dissipation Model

[0074] For the terminal using room-level cooling, when the hot and cold aisles are strictly separated, the return air temperature tar It can be calculated using formula (1):

[0075]

[0076] In the formula, t as is the air supply temperature required for cabinet heat removal, °C; Q IT is the heat generated by the data center, kW; C a is the heat capacity of air, kW / ℃; m a is the air supply volume, kg / s; c pa is the specific heat capacity of air, which is set at 1.005 kJ / (kg·℃).

[0077] Since the wet load of the data center can be ignored, the cooling air and chilled water undergo sensible heat exchange in the CRAH, and the heat exchange efficiency can be calculated using formula (2):

[0078]

[0079] Among them, C r is the ratio of heat capacity, NTU is the number of heat transfer units, calculated as formula (3) ~ (4):

[0080]

[0081] In the formula, C w is the heat capacity of water, kW / ℃; m w is the flow rate of chilled water, kg / s; c a is the specific heat capacity of air, taken as 1.005 kJ / (kg·℃); c w is the specific heat capacity of water, taken as 4.2 kJ / (kg·℃); KF is the product of the heat transfer coefficient and area of ​​the heat exchanger in the CRAH, kW / ℃.

[0082] From equations (1) and (2), we can get the chilled water supply temperature t ws , as shown in formula (5):

[0083]

[0084] According to the law of conservation of energy, the return water temperature t can be calculated by formula (6): wr :

[0085]

[0086] (2) Heat pump model

[0087] Heat pump evaporator side heat absorption Q evap,hp It can be calculated by formula (7):

[0088] Q evap,hp =m w ×cw ×(t wr -t mid ) (7)

[0089] Where, t mid It is the intermediate temperature of the chilled water after being cooled by the heat pump evaporator, ℃.

[0090] m h It can be calculated by formula (8):

[0091]

[0092] In the formula, Q h is the heat load of the heat user, kW; t s and t r is the supply and return water temperature of the heating network, ℃.

[0093] Heat pump condenser heat release Q cond,hp It can be calculated by the following formula (9):

[0094] Q cond,hp =m h ×c w ×(t p -t r ) (9)

[0095] In the formula, m h is the water flow rate of the heating network at the heat user side, kg / s; t p is the temperature of the return water from the heating network after being preheated by the condenser, ℃; t r is the return water temperature of the heating network, ℃.

[0096] Heat pump compressor power W hp It can be calculated by formula (10):

[0097]

[0098] In the formula, COP hp is the energy efficiency ratio of the heat pump; ε hp is the thermal perfection of the heat pump; t evap,hp and t cond,hp are the evaporation temperature and condensation temperature, ℃ respectively.

[0099] Condensation temperature t cond,hp and evaporation temperature t evap,hp Calculated by formula (11) to (12) respectively:

[0100] t cond,hp =t p +Δt cond,hp (11)

[0101] t evap,hp =t mid-Δt evap,hp (12)

[0102] In the formula, t p is the return water temperature of the heating network, the water temperature after preheating through the heat pump condenser, ℃; Δt cond,hp and Δt evap,hp are the terminal differences on the condenser side and the evaporator side of the heat pump, ℃.

[0103] (3) Boiler energy consumption model

[0104] If the temperature of the hot water network after preheating by the heat pump condenser is t p The water supply temperature cannot be reached s , need to continue heating through gas boiler, consuming gas V NG (m 3 / h) is calculated by formula (13):

[0105]

[0106] In the formula, Q boiler is the heat supplied by the boiler, kW; η boiler is the boiler efficiency; H is the lower calorific value of natural gas, kJ / (kg·m 3 ).

[0107] (4) Energy consumption model of centralized water cooling system

[0108] The energy consumption of the data center cooling system includes the energy consumption of the chilled water system pump W PUMP And cooling machine energy consumption W ref .W PUMP It can be calculated by formula (14):

[0109]

[0110] Where r is the density of water, 9.8 kN / m 3 ;h PUMP is the head of the pump; η PUMP is the pump efficiency.

[0111] Due to the low outdoor temperature in winter, in order to prevent the water temperature from freezing due to too low a temperature, the cooling tower used as a natural cooling source does not turn on the fan, and the fan energy consumption is negligible. The outlet water temperature after cooling by the natural cooling source is t ST,out Formula (15) can be used for simple calculation:

[0112] t ST,out =Δt ST +t wb (15)

[0113] In the formula, Δt ST is the outlet difference of the natural cooling source, ℃; twb is the local heating design wet bulb temperature, ℃.

[0114] If ST,out >t ws , the chiller needs to be turned on for supplementary cooling. The evaporation temperature of the chiller is t evap,ref , condensation temperature t cond,ref It can be calculated by formula (16) to (17):

[0115] t evap,ref =t ws -Δt evap,ref (16)

[0116] t cond,ref =t amb +Δt cond,ref (17)

[0117] Among them, t amb is the local heating design dry bulb temperature, °C; Δt cond,ref and Δt evap,ref They are the terminal differences on the condenser side and the evaporator side of the chiller, ℃.

[0118] Similarly, in order to prevent icing, the cooling tower fan is generally not turned on. cond,ref The approach temperature is the outdoor dry bulb temperature. ref It can be calculated by formula (18):

[0119]

[0120] In the formula, ε ref is the thermal perfection of the chiller; Q evap,ref is the cooling capacity of the refrigeration machine, which can be calculated by formula (19):

[0121] Q evap,ref =m w ×c w ×(t ST,out -t ws ) (19)

[0122] W ref is the energy consumption of the cooling machine, which can be calculated by formula (20):

[0123]

[0124] (5) Performance evaluation indicators

[0125] The energy consumed by the above systems mainly includes electricity and gas, which can be converted into primary energy consumption. The standard coal coefficients of various energy consumption can refer to the comprehensive energy consumption calculation criteria (GB / T 2589-2020), then the primary energy consumption m ce(kgce / h) can be calculated by formula (21):

[0126] m ce =0.1229×(W hp +W ref +W PUMP )+1.33×V NG (twenty one)

[0127] In the formula, 0.1229 is the standard coal conversion factor of electricity, kgce / kWh; 1.33 is the standard coal conversion factor of gas, kgce / m 3 .

[0128] Among them, the ratio of building heat load to data center heat exhaust It can be calculated using formula (22):

[0129]

[0130] Based on the above model, we can build Figure 3 The system performance simulation optimization platform shown in the figure. The input design parameters are shown in Table 1; the output parameter is the total primary energy consumption m ce . The chilled water flow m w and the intermediate temperature t mid Optimize so that the total primary energy consumption of the system is m ce lowest.

[0131] Table 1 Design parameters list

[0132]

[0133]

[0134] System energy consumption calculation optimization logic is as follows Figure 4 As shown. At each chilled water flow rate (m w,1～n ) corresponds to different supply and return water temperatures (t ws,1～n and t wr,1～n ), different flow rates within the supply and return water temperature range have their own intermediate temperature range (t ws,1 ~t wr,1 , t ws,2 ~t wr,2 ,…t ws,n ~t wr,n ); Calculate according to the above formula, different heat extraction intermediate temperatures t mid,i The following correspond to different preheating temperatures t p,i , heat pump evaporator heat absorption Q evap,hp,i , the heat pump compressor does work W hp,i And the heat pump condenser heat release Q cond,hp,i, corresponding to different refrigeration compressor work W ref,i and different gas boiler consumption V NG,i , and the pump does work W PUMP,i The system energy consumption mainly includes electricity and gas. Considering their respective standard coal reduction coefficients, the minimum system primary energy consumption m is obtained as shown in formula (23): ce,min , thus obtaining the corresponding optimization parameter m w,opt and t mid,opt .

[0135] m ce,min =min[0.1229×(W hp,i +W ref,i +W PUMP,i )+1.33×V NG,i ] (twenty three)

[0136] In summary, this embodiment provides a method for optimizing system design parameters for recovering waste heat from a data center for building heating. The method is based on a numerical simulation method. Under the design conditions of the heating system, such as the heat load of the heating user, the supply and return water temperature and water supply flow of the heating network, and the operating conditions of the data center, such as the supply air temperature, the supply air volume, the heat rejection, the KF of the CRAH, the outdoor dry-bulb and wet-bulb temperatures on the local heating design day, and the two-device end difference and thermodynamic perfection under the design conditions of the heat pump system for heat recovery, the energy consumption of the heat pump system, the energy consumption of the centralized water cooling system and the energy consumption of the boiler system are obtained, and the standard coal conversion coefficients of electricity and gas are used to convert them into primary energy consumption respectively. The primary energy consumption is comprehensively considered, with the goal of reducing the total primary energy consumption of cooling and heating buildings for the data center. According to the ratio of different building heat loads to the heat rejection of the data center, the intermediate temperature and chilled water flow of the data center are optimized to obtain the optimal intermediate temperature and chilled water flow of the heat extraction under the lowest primary energy consumption. This can save energy consumption in the waste heat recovery system to the greatest extent and provide a basis for selecting heat pump systems and boilers under optimized parameters.

[0137] Second embodiment

[0138] This embodiment provides an electronic device, such as Figure 5 As shown, the electronic device includes: a processor and a memory; wherein the processor and the memory can be connected via a communication bus; the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method of the first embodiment. In addition, the electronic device may also include a transceiver, the processor and the transceiver can be connected via a communication bus, and the transceiver is used to communicate with other devices.

[0139] Next, combine Figure 5The following is a detailed introduction to the various components of the electronic device:

[0140] Among them, the processor is the control center of the electronic device, and the electronic device may include multiple processors, each of which may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here may be a processor or a general term for multiple processing elements. For example, the processor is one or more central processing units (CPUs), or other general-purpose processors, application specific integrated circuits (ASICs), or one or more integrated circuits configured to implement an embodiment of the present invention, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (field programmable gate arrays, FPGAs), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor may execute various functions of the electronic device by running or executing software programs stored in the memory and calling data stored in the memory.

[0141] In a specific implementation, as an embodiment, the processor may include one or more CPUs, such as Figure 5 The CPU0 and CPU1 shown in the figure are, of course, only exemplary.

[0142] The memory is used to store the software program for executing the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can refer to the above method embodiment and will not be repeated here.

[0143] Optionally, the memory may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory may be integrated with the processor or exist independently and accessed through the interface circuit ( Figure 5 (not shown) is coupled to the processor, which is not specifically limited in this embodiment of the present invention.

[0144] The transceiver may include a receiver and a transmitter ( Figure 5 The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function. The transceiver can be integrated with the processor or exist independently and communicate with the electronic device through the interface circuit ( Figure 5 (not shown) is coupled to the processor, which is not specifically limited in this embodiment of the present invention.

[0145] In addition, it should be noted that Figure 5 The structure of the electronic device shown in the figure does not constitute a limitation on the device, and the actual device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. In addition, the technical effects achieved by the electronic device when executing the method of the first embodiment above can refer to the technical effects described in the first embodiment above, so they are not repeated here.

[0146] Third embodiment

[0147] This embodiment provides a computer-readable storage medium, which stores at least one instruction, and the instruction is loaded and executed by a processor to implement the method of the first embodiment. The computer-readable storage medium may be a ROM, a random access memory, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc. The instructions stored therein may be loaded by a processor in a terminal to execute the method.

[0148] In addition, it should be noted that the present invention can be provided as a method, an apparatus or a computer program product. Therefore, the embodiment of the present invention can be in the form of a full or partial hardware embodiment, a full or partial software embodiment or an embodiment combining software and hardware. Moreover, when implemented using software, the embodiment of the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center containing one or more available media sets. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium. The semiconductor medium may be a solid state hard disk.

[0149] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0150] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0151] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements. In addition, the term "and / or" is only an association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone, wherein A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding. "At least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can be represented by: a, b, c, ab, ac, bc or abc, where a, b, c can be single or plural.

[0152] In addition, it can be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0153] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0154] In several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of functional modules / units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0155] If the method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0156] Finally, it should be noted that the above is only a preferred embodiment of the present invention. It should be pointed out that although the preferred embodiment of the present invention has been described, for ordinary technicians in this technical field, once the basic creative concept of the present invention is known, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the protection scope of the present invention. Therefore, the attached claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A method for optimizing system design parameters for recovering waste heat from a data center for building heating, characterized in that: The system design parameter optimization method for recovering data center waste heat for building heating includes: Build a numerical simulation model; wherein the numerical simulation model includes: a data center heat exhaust model, a heat pump model, a boiler energy consumption model, and a centralized water cooling system energy consumption model; Based on the constructed numerical simulation model, a system primary energy consumption calculation model is constructed; wherein the system primary energy consumption calculation model is used to calculate the system primary energy consumption according to the system design parameters; Based on the constructed system primary energy consumption calculation model, with the goal of reducing the system primary energy consumption, the data center chilled water heat extraction intermediate temperature and chilled water flow are optimized to obtain the optimal values ​​of the data center chilled water heat extraction intermediate temperature and chilled water flow; The data center heat rejection model is expressed as: in, Among them, t ws Indicates the chilled water supply temperature; t wr Indicates the return water temperature; t ar Indicates the return air temperature of the air handling unit in the computer room; t as Indicates the air supply temperature required for cabinet heat dissipation; Q IT Indicates the heat generated by the data center; m a Indicates air supply volume; c pa Represents the specific heat capacity of air; C a represents the heat capacity of air; η represents the heat exchange efficiency when cooling air and chilled water undergo sensible heat exchange in CRAH; C r is the ratio of heat capacity, NTU stands for number of heat transfer units. C w represents the heat capacity of water; m w Indicates the flow rate of chilled water; c w is the specific heat capacity of water; KF is the product of the heat transfer coefficient and area of ​​the heat exchanger in CRAH; c a is the specific heat capacity of air; The heat pump model is expressed as: Q cond,hp =m h ×c w ×(t p -t r ); in, t cond,hp =t p +Δt cond,hp ; t evap,hp =t mid -Δt evap,hp ; Among them, Q cond,hp Indicates the heat released by the heat pump condenser; W hp Indicates the heat pump compressor power; m h Indicates the water flow rate of the heating network at the heat user side; t p Indicates the temperature of the return water from the heat network after being preheated by the heat pump condenser; t r Indicates the return water temperature of the heating network; t evap,hp and t cond,hp Respectively represent the evaporation temperature and condensation temperature; ε hp Indicates the thermal perfection of the heat pump; Q h represents the heat load of heat users; t s Indicates the water supply temperature of the heating network; t mid Indicates the intermediate temperature of the chilled water after cooling by the heat pump evaporator; Δt cond,hp and Δt evap,hp Respectively represent the terminal difference between the condenser side and the evaporator side of the heat pump; The expression of the boiler energy consumption model is: Among them, V NG Indicates the amount of gas consumed; η boiler Indicates boiler efficiency; H indicates the lower calorific value of natural gas; The expression of the energy consumption model of the centralized water cooling system is: in, Q evap,ref =m w ×c w ×(t ST,out -t ws ); Among them, W PUMP Indicates the energy consumption of the chilled water system pump; W ref represents the energy consumption of the chiller; r represents the gravity of water; h PUMP Indicates the head of the pump; η PUMP Indicates the pump efficiency; Q evap,ref Indicates the cooling capacity of the refrigeration machine; t ST,out Indicates the outlet water temperature after cooling by natural cooling source, t ST,out =Δt ST +t wb , Δt ST Indicates the outlet difference of the natural cooling source, t wb Indicates the local heating design wet bulb temperature; t evap,ref Indicates the evaporation temperature of the chiller, t evap,ref =t ws -Δt evap,ref ;t cond,ref represents the condensation temperature, t cond,ref =t amb +Δt cond,ref ;t amb Indicates the local heating design dry bulb temperature; Δt cond,ref and Δt evap,ref are the terminal differences on the condenser side and the evaporator side of the chiller; ε ref Indicates the thermal perfection of the chiller; The expression of the calculation model of the primary energy consumption of the system is: m ce =0.1229×(W hp +W ref +W PUMP )+1.33×V NG ; Among them, m ce Indicates the primary energy consumption of the system.

2. The system design parameter optimization method for recovering waste heat from a data center for building heating according to claim 1, characterized in that: The system design parameters include: local heating outdoor design parameters, central heating system design parameters, data center room side heat removal system design parameters, central water cooling system design parameters, boiler design parameters and heat pump system design parameters; The local heating outdoor design parameters include: local outdoor heating design dry bulb temperature and local outdoor heating wet bulb temperature; The design parameters of the central heating system include: building heat load, heating network water supply temperature, heating network return water temperature and heating network water flow; The design parameters of the room-side heat removal system of the data center include: the product of the heat transfer coefficient and area of ​​the heat exchanger of the cooling air in the computer room air handler CRAH, the supply air temperature and air volume required for cabinet heat removal, and the heat removal amount of the data center; The design parameters of the centralized water cooling system include: the end difference on the condenser side of the chiller, the end difference on the evaporator side of the chiller, the thermal perfection of the chiller, the end difference at the outlet of the natural cooling source, the head of the water pump and the water pump efficiency; The boiler design parameters include: boiler thermal efficiency and lower calorific value of natural gas; The heat pump system design parameters include: the end difference on the heat pump condenser side, the end difference on the heat pump evaporator side, and the thermal perfection of the heat pump.

3. The system design parameter optimization method for recovering waste heat from a data center for building heating according to claim 1, characterized in that: The primary energy consumption calculation model of the system constructed is based on the goal of reducing the primary energy consumption of the system, optimizing the intermediate temperature and flow rate of chilled water heat extraction in the data center, and obtaining the optimal values ​​of the intermediate temperature and flow rate of chilled water heat extraction in the data center, including: Selecting a plurality of different chilled water flow values ​​within a preset process range, and selecting a plurality of different intermediate temperature values ​​within a preset temperature range; wherein the number of the intermediate temperature values ​​matches the number of the chilled water flow values; Combining a plurality of different chilled water flow values ​​with a plurality of different intermediate temperature values ​​to obtain a plurality of data combinations; wherein each data combination includes a chilled water flow value and an intermediate temperature value; For each data combination, the chilled water flow value and the intermediate temperature value are respectively substituted into the system primary energy consumption calculation model to calculate the system primary energy consumption corresponding to the current data combination; The chilled water flow rate value and the intermediate temperature value in the data combination when the system primary energy consumption is the lowest are selected as the optimal values ​​of the intermediate temperature and chilled water flow rate for chilled water heat extraction in the data center.

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