Optimization method and system for mixed refrigerant components based on simulation and life cycle

Abstract

The invention discloses a simulation and life cycle-based mixed refrigerant component optimization method and system, and the method comprises the steps: generating a plurality of mixed refrigerants with different component mass proportions according to a plurality of refrigerant elementary substances through an exhaustion method or a genetic algorithm; calculating a refrigeration energy efficiency ratio, a heat pump energy efficiency ratio and a first global warming potential value of the mixed refrigerant; simulating the mixed refrigerant through the mixed refrigerant life cycle carbon emission model, and calculating life cycle carbon emission; simulating the mixed refrigerant through a flammability model, and calculating a flammability calculation factor; and according to the target function, performing component optimization on the life cycle carbon emission and the flammability calculation factor to obtain a target mixed refrigerant. According to the method, the carbon emission and the flammability of various refrigerant simple substance combinations of the mixed refrigerant can be comprehensively analyzed, the proper mixed refrigerant can be rapidly and reliably determined according to the use requirements of different refrigeration systems, and the method can be widely applied to the technical field of computers.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method and system for optimizing mixed refrigerant components based on simulation and life cycle. Background Art

[0002] At present, with the development of new technologies, a new generation of refrigerants will become mainstream. However, the new compounds cannot balance safety, high energy efficiency and low carbon emissions at the same time, forming an "impossible triangle". At the same time, natural refrigerants have problems such as high operating pressure, low energy efficiency and high risk. Therefore, mixing different refrigerants to form mixed refrigerants has become a new technical direction.

[0003] Since mixed refrigerants have a variety of component options, the selection range of refrigerants has expanded from only dozens to tens of thousands, and suitable refrigerant components need to be selected for different systems and operating conditions. When determining the components of mixed refrigerants, the relevant technology only analyzes and selects based on thermodynamic cycles, which has certain limitations. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose a method and system for optimizing the mixed refrigerant components based on simulation and life cycle, aiming to achieve more comprehensive and reliable optimization of the mixed refrigerant components.

[0005] To achieve the above objectives, one aspect of an embodiment of the present application proposes an optimization method for mixed refrigerant components based on simulation and life cycle, the method comprising:

[0006] By using an exhaustive method or a genetic algorithm, a number of mixed refrigerants with different component mass proportions are generated according to a number of refrigerant single substances;

[0007] Calculating a refrigeration energy efficiency ratio, a heat pump energy efficiency ratio, and a first global warming potential value of the mixed refrigerant;

[0008] The mixed refrigerant is simulated by a mixed refrigerant life cycle carbon emission model, and the life cycle carbon emission of a refrigeration system after the mixed refrigerant is applied is calculated according to the refrigeration energy efficiency ratio and the first global warming potential value;

[0009] Simulating the mixed refrigerant through a flammability model and calculating a flammability calculation factor of the mixed refrigerant;

[0010] According to the objective function, the life cycle carbon emission and the flammability calculation factor are optimized to obtain a target mixed refrigerant.

[0011] In some embodiments, the step of calculating the refrigeration energy efficiency ratio and the heat pump energy efficiency ratio of the mixed refrigerant comprises the following steps:

[0012] Based on the reverse Carnot cycle, a refrigeration energy efficiency model and a heat pump energy efficiency model including a compressor, a condenser, an expansion device and an evaporator are constructed;

[0013] Determining the power consumption of the compressor according to the volumetric efficiency, isentropic efficiency and motor efficiency of the compressor;

[0014] Calculating the refrigeration energy efficiency ratio according to the refrigeration capacity, water circuit heat loss, compressor power consumption, fan energy consumption and water pump energy consumption of the refrigeration energy efficiency model;

[0015] The heat pump energy efficiency ratio is calculated according to the heating capacity and the compressor power consumption of the heat pump energy efficiency model.

[0016] In some embodiments, the step of calculating the first global warming potential of the mixed refrigerant comprises the following steps:

[0017] Calculating the mass fraction of the refrigerant single substance according to the mass of the refrigerant single substance and the total mass of the mixed refrigerant;

[0018] Obtaining a second global warming potential value of each of the refrigerant elements;

[0019] The first global warming potential value of the mixed refrigerant is calculated according to the mass fraction of each refrigerant element in the mixed refrigerant and the second global warming potential value.

[0020] In some embodiments, simulating the mixed refrigerant through the mixed refrigerant life cycle carbon emission model, and calculating the life cycle carbon emissions of the refrigeration system after applying the mixed refrigerant according to the refrigeration energy efficiency ratio and the first global warming potential, includes the following steps:

[0021] Simulating the mixed refrigerant through a mixed refrigerant life cycle carbon emission model;

[0022] Calculate the annual energy consumption of the refrigeration system based on the refrigeration energy efficiency ratio and the refrigeration system power;

[0023] Calculate energy consumption and carbon emissions based on the annual energy consumption, carbon emission factor and service life of the refrigeration system;

[0024] Calculating the carbon emissions of the mixed refrigerant based on the annual leakage of the mixed refrigerant, the leakage of the mixed refrigerant recovery, the first global warming potential, the service life of the refrigeration system and the refrigerant filling amount;

[0025] The life cycle carbon emissions of the refrigeration system after applying the mixed refrigerant are determined according to the mixed refrigerant carbon emissions and the energy consumption carbon emissions.

[0026] In some embodiments, simulating the mixed refrigerant by a flammability model and calculating the flammability calculation factor of the mixed refrigerant includes the following steps:

[0027] Determine the elemental flammability index based on the adiabatic flame temperature and fluorine substitution rate of the elemental refrigerant;

[0028] Integrating and normalizing the single-substance flammability index to obtain a flammability calculation factor of the mixed refrigerant;

[0029] Alternatively, the composite action between the refrigerant elements is simulated to obtain the number of functional groups of the mixed refrigerant;

[0030] The functional group quantity is input into a pre-trained artificial neural network for processing to obtain a flammability calculation factor of the mixed refrigerant.

[0031] In some embodiments, the calculation formula for the life cycle carbon emissions is:

[0032] C tot =C grid +G ref ;

[0033] C grid =E sys ×EF grid ×yr;

[0034] C ref =(yr×leak yr +leak re )×GWP×m ref ;

[0035] Among them, C tot represents life cycle carbon emissions; C grid Represents energy consumption and carbon emissions; C ref Represents the carbon emissions of mixed refrigerants; E sys Indicates the annual energy consumption of the refrigeration system; EF grid represents the carbon emission factor; yr represents the service life of the refrigeration system; leak yr Indicates the amount of mixed refrigerant recovery leakage; re represents the annual leakage of mixed refrigerants; GWP represents the first global warming potential; m ref Indicates the refrigerant filling amount.

[0036] In some embodiments, the objective function is expressed as:

[0037] Π<∏ req ;

[0038] min(C tot), or, C tot <C ref0 ;

[0039] Where Π is the flammability calculation factor, Π req is the flammability standard; C tot is the life cycle carbon emission of the refrigeration system after the mixed refrigerant is applied, C ref0 It is the total carbon emissions of the original refrigerant used in the refrigeration system.

[0040] To achieve the above objectives, another aspect of the embodiment of the present application provides an optimization system for mixed refrigerant components based on simulation and life cycle, the system comprising:

[0041] The first module is used to generate a plurality of mixed refrigerants with different component mass ratios according to a plurality of refrigerant single substances by an exhaustive method or a genetic algorithm;

[0042] A second module is used to calculate the refrigeration energy efficiency ratio, the heat pump energy efficiency ratio and the first global warming potential value of the mixed refrigerant;

[0043] A third module is used to simulate the mixed refrigerant through a mixed refrigerant life cycle carbon emission model, and calculate the life cycle carbon emission of a refrigeration system after applying the mixed refrigerant according to the refrigeration energy efficiency ratio and the first global warming potential value;

[0044] A fourth module is used to simulate the mixed refrigerant through a flammability model and calculate a flammability calculation factor of the mixed refrigerant;

[0045] The fifth module is used to optimize the components of the life cycle carbon emissions and the flammability calculation factor according to the objective function to obtain a target mixed refrigerant.

[0046] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above-mentioned method when executing the computer program.

[0047] To achieve the above objective, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0048] The embodiments of the present application include at least the following beneficial effects: the present application provides a method and system for optimizing the components of mixed refrigerants based on simulation and life cycle, which generates several mixed refrigerants with different component mass ratios according to several refrigerant single substances through exhaustive method or genetic algorithm; calculates the refrigeration energy efficiency ratio, heat pump energy efficiency ratio and first global warming potential of the mixed refrigerant; simulates the mixed refrigerant through the mixed refrigerant life cycle carbon emission model, and calculates the life cycle carbon emission of the refrigeration system after applying the mixed refrigerant according to the refrigeration energy efficiency ratio and the first global warming potential; simulates the mixed refrigerant through the flammability model, and calculates the flammability calculation factor of the mixed refrigerant; according to the objective function, the components of the life cycle carbon emission and the flammability calculation factor are optimized to obtain the target mixed refrigerant. The overall steps of the method combine the system simulation and the calculation results of the life cycle carbon emission, which is conducive to the comprehensive and comprehensive analysis of the carbon emission and flammability of various component combinations of the mixed refrigerant, and is conducive to more quickly and reliably determining the appropriate mixed refrigerant for different refrigeration system use requirements. In addition, the simulation method is conducive to saving a lot of development resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are used to provide further understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0050] Figure 1 is a flow chart of a method for optimizing mixed refrigerant components based on simulation and life cycle provided in an embodiment of the present application;

[0051] Figure 2 is a schematic diagram of a refrigeration energy efficiency model and a heat pump energy efficiency model provided in an embodiment of the present application;

[0052] Figure 3 It is a schematic diagram of the structure of the artificial neural network provided in the embodiment of the present application;

[0053] Figure 4 It is a module schematic diagram of an optimization system for mixed refrigerant components based on simulation and life cycle provided in an embodiment of the present application;

[0054] Figure 5 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0056] Although the functional modules are divided in the system schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first / S100", "second / S200", etc. in the specification, claims and the above drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0057] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0058] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0059] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0061] Before describing the embodiments of the present application in detail, some nouns and terms involved in the embodiments of the present application are first described. The nouns and terms involved in the embodiments of the present application are subject to the following explanations.

[0062] (1) GWP: Global Warming Potential. GWP is a value used to evaluate the greenhouse effect of refrigerants, based on the greenhouse effect of carbon dioxide. That is, the GWP of carbon dioxide is 1. Most third-generation refrigerants have a GWP greater than 1000. The current goal is to control the GWP of new-generation refrigerants to less than 150.

[0063] (2) R134a: 1,1,1,2-tetrafluoroethane;

[0064] (3) R410A: Refrigerant used in household split air conditioners, a mixture of R125 and R32;

[0065] (4) R125: pentafluoroethane;

[0066] (5) R32: difluoromethane;

[0067] (6) R1234yf: 2,3,3,3-tetrafluoropropylene;

[0068] (7) R1234ze(E): 1,3,3,3-tetrafluoropropene;

[0069] (8) R227ea: heptafluoropropane;

[0070] (9) R152a: 1,1-difluoroethane;

[0071] At present, there are various components of mixed refrigerants, which expands the selection range from dozens of refrigerants to tens of thousands. In view of different systems and operating conditions, it is necessary to select appropriate refrigerant components. When determining the components of mixed refrigerants, the relevant technology only analyzes and selects based on the thermodynamic cycle, which has certain limitations.

[0072] In view of this, an optimization method and system for mixed refrigerant components based on simulation and life cycle are provided in an embodiment of the present application. This scheme calculates the energy efficiency, flammability calculation factor, and life cycle carbon emissions of the refrigerant through a general model based on the mechanism, thereby optimizing the issues of safety, energy efficiency, and carbon emissions, and screening out the optimal mixed refrigerant components.

[0073] The optimization method of mixed refrigerant components based on simulation and life cycle provided in the embodiment of the present application relates to the field of computer technology. The optimization method of mixed refrigerant components based on simulation and life cycle provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server, and can also be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a car terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, and can also be configured to provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms and other basic cloud computing services. The server can also be a node server in a blockchain network; the software can be an application that implements the optimization method of mixed refrigerant components based on simulation and life cycle, etc., but is not limited to the above forms.

[0074] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0075] Figure 1 is an optional flow chart of a method for optimizing mixed refrigerant components based on simulation and life cycle provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S100 to S500.

[0076] Step S100, generating a plurality of mixed refrigerants with different component mass ratios according to a plurality of refrigerant single substances by an exhaustive method or a genetic algorithm.

[0077] Step S200, calculating the refrigeration energy efficiency ratio, heat pump energy efficiency ratio and first global warming potential value of the mixed refrigerant.

[0078] Step S300, simulating the mixed refrigerant through a mixed refrigerant life cycle carbon emission model, and calculating the life cycle carbon emissions of a refrigeration system after applying the mixed refrigerant according to the refrigeration energy efficiency ratio and the first global warming potential.

[0079] Step S400: simulating the mixed refrigerant through a flammability model and calculating a flammability calculation factor of the mixed refrigerant.

[0080] Step S500: Optimizing the components of the lifecycle carbon emission and the flammability calculation factor according to the objective function to obtain a target mixed refrigerant.

[0081] Steps S100 to S500 shown in the embodiment of the present application combine the system simulation and the calculation results of life cycle carbon emissions, which is conducive to comprehensively analyzing the carbon emissions and flammability of various refrigerant elements in the mixed refrigerant, and is conducive to more quickly and reliably determining the appropriate mass ratio of the mixed refrigerant for different refrigeration system usage requirements. In addition, the simulation method is also conducive to saving a lot of development resources.

[0082] In some embodiments, step S200 may include but is not limited to steps S210 to S240 of calculating the refrigeration energy efficiency ratio and heat pump energy efficiency ratio of the mixed refrigerant:

[0083] Step S210, based on the reverse Carnot cycle, construct a refrigeration energy efficiency model and a heat pump energy efficiency model including a compressor, a condenser, an expansion device and an evaporator.

[0084] Step S220, determining the power consumption of the compressor according to the volumetric efficiency, isentropic efficiency and motor efficiency of the compressor.

[0085] Step S230, calculating the refrigeration energy efficiency ratio according to the refrigeration capacity, water circuit heat loss, compressor power consumption, fan energy consumption and water pump energy consumption of the refrigeration energy efficiency model.

[0086] Step S240: calculating the heat pump energy efficiency ratio according to the heating capacity and the compressor power consumption of the heat pump energy efficiency model.

[0087] In some embodiments, step S200 may also include but is not limited to steps S250 to S270 of calculating the first global warming potential value as follows:

[0088] Step S250: Calculate the mass fraction of the refrigerant single substance according to the mass of the refrigerant single substance and the total mass of the mixed refrigerant.

[0089] Step S260, obtaining a second global warming potential value of each of the refrigerant elements.

[0090] Step S270: calculating a first global warming potential value of the mixed refrigerant according to the mass fraction of each refrigerant element in the mixed refrigerant and the second global warming potential value.

[0091] In some embodiments, step S300 includes but is not limited to the following steps S310 to S350:

[0092] Step S310: simulating the mixed refrigerant through a mixed refrigerant life cycle carbon emission model.

[0093] Step S320: Calculate the annual energy consumption of the refrigeration system according to the refrigeration energy efficiency ratio and the refrigeration system power.

[0094] Step S330, calculating energy consumption carbon emissions according to the annual energy consumption of the refrigeration system, the carbon emission factor and the service life of the refrigeration system.

[0095] Step S340, calculating the carbon emission of the mixed refrigerant according to the annual leakage of the mixed refrigerant, the recovered leakage of the mixed refrigerant, the first global warming potential, the service life of the refrigeration system and the refrigerant filling amount.

[0096] Step S350: determining the life cycle carbon emissions of the refrigeration system after applying the mixed refrigerant according to the mixed refrigerant carbon emissions and the energy consumption carbon emissions.

[0097] In step S350 of some embodiments, the calculation formula of life cycle carbon emissions is:

[0098] C tot =C grid +C ref ;

[0099] C grid =E sys ×EF grid ×yr;

[0100] C ref =(yr×leak yr +leak re )×GWP×m ref ;

[0101] Among them, C tot represents life cycle carbon emissions; C grid Represents energy consumption and carbon emissions; C ref Represents the carbon emissions of mixed refrigerants; E sys Indicates the annual energy consumption of the refrigeration system; EF grid represents the carbon emission factor; yr represents the service life of the refrigeration system; leak yr Indicates the amount of mixed refrigerant recovery leakage; rerepresents the annual leakage of mixed refrigerants; GWP represents the first global warming potential; m ref Indicates the refrigerant filling amount.

[0102] In some embodiments, the step of calculating the flammability calculation factor in step S400 includes but is not limited to the following steps S410 to S420 or steps S430 to S440:

[0103] Step S410, determining the elemental flammability index according to the adiabatic flame temperature and fluorine substitution rate of the elemental refrigerant.

[0104] Step S420, integrating and normalizing the single-substance flammability index to obtain a flammability calculation factor of the mixed refrigerant.

[0105] Alternatively, in step S430, a composite action between the refrigerant elements is simulated to obtain the number of functional groups of the mixed refrigerant.

[0106] Step S440: input the number of functional groups into a pre-trained artificial neural network for processing to obtain a flammability calculation factor of the mixed refrigerant.

[0107] In step S500 of some embodiments, the expression of the objective function is:

[0108] ∏<∏ req ;

[0109] min(C tot ), or, C tot <C ref0 ;

[0110] Where Π is the flammability calculation factor, Π req is the flammability standard; C tot is the life cycle carbon emission of the refrigeration system after the mixed refrigerant is applied, C ref0 It is the total carbon emissions of the original refrigerant used in the refrigeration system.

[0111] Below, in conjunction with the accompanying drawings and specific examples of mixed refrigerant optimization application scenarios, the scheme of the embodiment of the present application is described in detail and explained:

[0112] In the embodiment of the present application, a method for optimizing the mixed refrigerant components based on simulation and life cycle is provided. The method can be applied to comprehensively and reliably optimize the mixed refrigerant components. Taking the refrigeration system as an air conditioning system as an example, it is necessary to reduce carbon emissions as much as possible while meeting safety requirements. That is, the performance requirements (objective function) of the refrigeration system can be set as:

[0113] Meet the flammability requirements: Π<Π req ;

[0114] Meet the minimum carbon emission: min(C tot ).

[0115] In order to consider other factors, such as the cost of refrigerant components, the condition of minimum carbon emission can be replaced by a condition of reduced carbon emission, that is, C tot <C ref0 .

[0116] Where Π is the calculation factor of flammability, Π req is the required flammability (in Π req =0 satisfies level 1, Π req =5 satisfies the 2L standard, or Π req =35 meets the Level 2 standard) as an example.

[0117] C tot is the life cycle carbon emission of the refrigeration system, C ref0 is the carbon emission of the original (replaced) refrigerant (ref0).

[0118] Here, the carbon emission reduction factor can be considered

[0119] Based on this, an exhaustive method or a genetic algorithm can be used to generate several component combinations of mixed refrigerants. Specifically, when there are fewer components to consider, an exhaustive method can be used. First, all refrigerant single substances (candidate components) ref1, ref2, ..., refn are listed, and exhaustive enumeration is performed based on all its components (including binary combinations, ternary combinations, etc.) and all mass fractions (percentages are precision). The method of the embodiment of the present application has a faster calculation speed, and can be used to screen reliable components based on historical experience. An ordinary computer can be used to quickly complete the exhaustive calculation to obtain several component combinations.

[0120] If there are many components to consider, it is necessary to use genetic algorithms to optimize the selection. Genetic algorithms are an optimization algorithm that imitates the natural evolution process and gradually approaches the optimal solution through operations such as selection, crossover, and mutation. In the process of optimizing component selection, the genetic algorithm first generates a set of initial solutions, which can be regarded as different combinations of candidate components. In each generation, the algorithm evaluates the fitness of these candidate solutions according to the objective function (such as life cycle carbon emissions, flammability, etc.), and then selects individuals with higher fitness for crossover and mutation operations to generate a new generation of candidate solutions. The crossover operation simulates the process of genetic recombination in nature, increasing the diversity of solutions by randomly changing part of the components of a candidate solution.

[0121] As the number of evolutionary generations increases, the average fitness of candidate solutions gradually increases, thus approaching the optimal solution. However, genetic algorithms may also fall into local optimality, that is, the solution found is not the global optimal solution. In order to solve this problem, some improvement strategies can be introduced, such as increasing the mutation rate, introducing an elite retention mechanism, using multiple selection strategies, etc., to improve the algorithm's ability to jump out of the local optimality.

[0122] The combination of components optimized by genetic algorithms can obtain a set of near-optimal solutions in a short time to meet the various performance requirements of the system. For example, when dealing with complex multi-fluid systems, genetic algorithms can effectively reduce computing time, improve computing efficiency, and find more reliable and efficient component combinations, but this may fall into local optimality.

[0123] Table 1 shows some calculation examples provided in the embodiments of the present application, showing two different scenarios ("one household air conditioner to multiple units, located in City A" and "car air conditioner, located in City B"), and optimizes the selection of refrigerants R410A and R134a currently used in these air conditioners, and finds some optimized configurations.

[0124] Table 1

[0125]

[0126]

[0127] This application constructs five models to simulate and calculate various indicators of mixed refrigerants, which is conducive to comprehensive and reliable evaluation of the component combination of mixed refrigerants, thereby screening out the optimal component solution that meets the performance requirements of the refrigeration system.

[0128] Further, the introduction of each model is as follows:

[0129] (1) Refrigeration energy efficiency model.

[0130] Reference Figure 2 , refrigeration is a reverse Carnot cycle, which can be described as a combination of four major components: compressor, condenser, expansion device, and evaporator.

[0131] The reverse Carnot cycle is used to calculate the refrigeration energy efficiency ratio, and the calculation expression is:

[0132]

[0133] Among them, Q evap is the cooling capacity, that is, the heat exchange of the evaporator; W comp is the power consumption of the compressor; COP is the refrigeration energy efficiency ratio.

[0134] (2) Heat pump energy efficiency model.

[0135] The heat pump is also a reverse Carnot cycle and can also be described as a combination of the four major components mentioned above.

[0136] The reverse Carnot cycle is used to calculate the heat pump energy efficiency ratio, and the calculation expression is:

[0137]

[0138] Where HPF is the energy efficiency ratio of the heat pump; Q cond is the heating capacity, that is, the heat exchange of the condenser; W comp is the power consumption of the compressor.

[0139] For the models (1) and (2), considering the fan (W fan )、Water pump(W pump ) and other energy consumption. When calculating the energy efficiency ratio, these items may need to be added to the denominator. Similarly, for a refrigeration system with chilled water and cooling water, the heat loss of the water circuit (Q loss ) is to be subtracted from the numerator.

[0140] Taking the calculation of refrigeration energy efficiency ratio as an example, the optimization formula is:

[0141]

[0142] Here, the summation symbol indicates that there is more than one evaporator, pipe loss, compressor, electronic fan, and water pump in the system.

[0143] Q loss Generally, it can be ignored as zero. If it cannot be ignored, after performing finite element difference on the refrigeration system pipeline, thermal balance analysis and fluid mechanics analysis are carried out by modeling each section of the pipeline. This method is similar to the heat exchanger calculation method, which can be referred to as the heat exchanger calculation.

[0144] Compressor power W comp The calculation involves compressor analysis and the three efficiencies of the compressor: volumetric efficiency (η v ), isentropic efficiency (η s ), motor efficiency (η m ). Any efficiency can be considered as a function of the inlet and outlet pressures:

[0145]

[0146] Among them, a, n1, n2 are fitting parameters, η is the above three efficiencies, P dis is the compressor discharge pressure, P suc is the compressor suction pressure, and ω is the rotational speed.

[0147] From the above efficiency, the compressor power can be calculated:

[0148] W comp =η v ωV d ρ suc (h dis -h suc );

[0149] Among them, V d is the compressor displacement, ρ suc is the compressor suction density, h dis is the exhaust gas specific enthalpy, h suc is the specific enthalpy of inspiration.

[0150] For the heat exchange of the evaporator, that is, the cooling capacity (Q evap ), or the heating capacity, that is, the heat exchange capacity of the condenser (Q cond ), or the heat loss of the pipeline (Q loss ), the heat exchanger or the connecting pipeline needs to be differentiated. In some embodiments, the calculation accuracy can be guaranteed by differentiating the small pipeline within 15mm, that is, each differential unit needs to be smaller than 15mm to ensure the calculation accuracy.

[0151] For each unit, the refrigerant and heat transfer medium (usually water, ethylene glycol aqueous solution, or air) can be simulated using ∈-NTU.

[0152] (3) GWP calculation model (global warming potential calculation model).

[0153] The GWP of a mixed refrigerant is the weighted number of the mass fractions of its component refrigerants, that is:

[0154]

[0155] GWP mixture is the GWP of the mixed refrigerant, w i is the mass of the refrigerant element i, w tot is the total mass of the mixed refrigerant, is the mass fraction of refrigerant element i, GWP i is the GWP of the refrigerant element i. The value of GWP should refer to the latest Intergovernmental Panel on Climate Change (IPCC) report or the corresponding national standard for refrigerants.

[0156] (4) Carbon emission model of mixed refrigerant life cycle.

[0157] The expression of this model is: C tot =C grid +C ref ;

[0158] First, it is necessary to perform statistical simulation on the use of the refrigeration system. For example, for cooling and heating air conditioners, it is necessary to calculate the cooling and heating loads of the air conditioner for a whole year through meteorological data (typical meteorological year), and then calculate the COP and power of the air conditioner through meteorological data and load. Then, the data for one year is accumulated to obtain the energy consumption of the air conditioner for one year (E sys ).

[0159] For example, for an industrial refrigeration system, the COP and power should be calculated based on the production schedule and the cooling capacity of each shift, and then the energy consumption (E sys ).

[0160] According to the carbon emission factor (EF grid ), calculate energy consumption and carbon emissions (C grid ): C geid =E sys ×EF grid ×yr.

[0161] The carbon emission factor should be calculated with reference to the latest official data; yr is the service life of the system.

[0162] Another important part of carbon emissions is the carbon emissions of refrigerants. ref Generally speaking, refrigerant carbon emissions have two parts, annual leakage and recycling leakage.

[0163] C ref =(yr×leak yr +leak re )×GWP×m ref ;

[0164] Among them, leak yr It is the annual leakage of the system, which is generally around 2-6%, depending on the refrigeration system. re It is the recovery leakage, generally 15-100%, generally depending on the proficiency of the operator. GWP is the carbon emission potential of the mixed refrigerant. ref It is the refrigerant filling amount of the system, which depends on the refrigeration system. Generally, each refrigeration system has its corresponding recommended value.

[0165] (5) Flammability model.

[0166] The flammability of a mixed refrigerant can be determined by the flammability of the components themselves or by the flammability interaction between the components.

[0167] In some embodiments, the flammability calculation factor can be calculated by the flammability of the component itself. Each component, as a single substance, can be simply quantified as Π. By calculating the adiabatic flame temperature and fluorine substitution rate of each component, the flammability index can be calculated, the flammability index is integrated and normalized, and finally the flammability calculation factor Π can be obtained.

[0168] In some embodiments, the flammability calculation factor can be calculated by calculating the flammability influence between components. In order to consider the composite effect between components, the embodiment of the present application performs simulation based on the functional groups of the molecule. Specifically, the number of each functional group is counted and then input into the artificial neural network for calculation, such as Figure 3 Shown is an artificial neural network structure.

[0169] First, collect and prepare a training set containing the number of functional groups and their corresponding flammability data for various mixed refrigerants. This data can be obtained through experimental measurements or references. The input layer includes the number of each functional group in each refrigerant mixture. For example, if functional groups such as fluorine, chlorine, and hydrocarbons are considered, the input layer should have corresponding nodes, each of which represents the number of a certain functional group. Select an appropriate number of hidden layers and the number of neurons in each layer. The number of hidden layers and the number of neurons need to be determined experimentally to find the best network structure. A common practice is to determine them through cross-validation and hyperparameter optimization. The output layer usually has only one node, which is used to predict the total flammability of the mixed refrigerant. This node outputs a flammability index (Π), which represents the overall flammability level of the mixed refrigerant. Use the validation set to evaluate the model performance to ensure that it has good generalization ability. Adjust the model structure and parameters based on the validation results. Finally, use the test set to evaluate the final performance of the model. The trained neural network model can be used to predict the flammability of new refrigerant mixtures. Input the number of each functional group, and the neural network outputs the predicted flammability index. Through the above steps, artificial neural networks can effectively simulate and predict the flammability complex effects between components in mixed refrigerants, thereby providing an important reference for the safety assessment and formulation optimization of refrigerants.

[0170] For example, the number of functional groups such as CO, C=O, CH, CF, C-Br, OH, etc. is used as input to calculate the composite combustible effect Π. According to the analysis, when Π is less than 0, it is non-flammable and meets the ASHRAE Class 1 standard; when Π is less than or equal to 5, it is slightly flammable and meets the ASHRAE Class 2L standard; when Π is less than or equal to 35, it is flammable and meets the ASHRAE Class 2 standard; when Π is greater than 35, it is flammable and is at ASHRAE Class 3.

[0171] In summary, the embodiments of the present application have at least the following beneficial effects:

[0172] 1. Combining the system simulation and life cycle carbon emission calculation results, it is conducive to a comprehensive analysis of the carbon emissions and flammability of various component combinations of mixed refrigerants, and is conducive to determining the appropriate mixed refrigerant more quickly and reliably according to different refrigeration system usage requirements.

[0173] 2. Simulation can help save a lot of development resources.

[0174] See also Figure 4 The embodiment of the present application also provides an optimization system for mixed refrigerant components based on simulation and life cycle, which can implement the above-mentioned optimization method for mixed refrigerant components based on simulation and life cycle, and the system includes:

[0175] The first module 101 is used to generate a plurality of mixed refrigerants with different component mass ratios according to a plurality of refrigerant single substances by an exhaustive method or a genetic algorithm;

[0176] The second module 102 is used to calculate the refrigeration energy efficiency ratio, the heat pump energy efficiency ratio and the first global warming potential value of the mixed refrigerant;

[0177] The third module 103 is used to simulate the mixed refrigerant through a mixed refrigerant life cycle carbon emission model, and calculate the life cycle carbon emission of a refrigeration system after applying the mixed refrigerant according to the refrigeration energy efficiency ratio and the first global warming potential value;

[0178] The fourth module 104 is used to simulate the mixed refrigerant through a flammability model and calculate a flammability calculation factor of the mixed refrigerant;

[0179] The fifth module 105 is used to optimize the components of the life cycle carbon emission and the flammability calculation factor according to the objective function to obtain a target mixed refrigerant.

[0180] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0181] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned optimization method of mixed refrigerant components based on simulation and life cycle when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0182] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0183] See also Figure 5 , Figure 5 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0184] The processor 201 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0185] The memory 202 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 202 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 202, and the processor 201 calls and executes the optimization method of the mixed refrigerant component based on simulation and life cycle in the embodiment of this application;

[0186] Input / output interface 203, used to implement information input and output;

[0187] The communication interface 204 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0188] Bus 205 , which transmits information between various components of the device (e.g., processor 201 , memory 202 , input / output interface 203 , and communication interface 204 );

[0189] The processor 201 , the memory 202 , the input / output interface 203 and the communication interface 204 are connected to each other in communication within the device via the bus 205 .

[0190] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned optimization method for mixed refrigerant components based on simulation and life cycle is implemented.

[0191] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0192] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0193] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0194] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0195] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0196] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0197] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0198] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "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 mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0199] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0200] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0201] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0202] If the integrated unit 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 application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0203] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A simulation and life cycle based optimization method for mixed refrigerant components, characterized in that: The following steps are involved: By using an exhaustive method or a genetic algorithm, a number of mixed refrigerants with different component mass proportions are generated according to a number of refrigerant single substances; Calculating a refrigeration energy efficiency ratio, a heat pump energy efficiency ratio, and a first global warming potential value of the mixed refrigerant; The mixed refrigerant is simulated by a mixed refrigerant life cycle carbon emission model, and the life cycle carbon emission of a refrigeration system after the mixed refrigerant is applied is calculated according to the refrigeration energy efficiency ratio and the first global warming potential value; Simulating the mixed refrigerant through a flammability model and calculating a flammability calculation factor of the mixed refrigerant; According to the objective function, the life cycle carbon emission and the flammability calculation factor are optimized to obtain a target mixed refrigerant.

2. The method according to claim 1, characterized in that The step of calculating the refrigeration energy efficiency ratio and the heat pump energy efficiency ratio of the mixed refrigerant comprises the following steps: Based on the reverse Carnot cycle, a refrigeration energy efficiency model and a heat pump energy efficiency model including a compressor, a condenser, an expansion device and an evaporator are constructed; Determining the power consumption of the compressor according to the volumetric efficiency, isentropic efficiency and motor efficiency of the compressor; Calculating the refrigeration energy efficiency ratio according to the refrigeration capacity, water circuit heat loss, compressor power consumption, fan energy consumption and water pump energy consumption of the refrigeration energy efficiency model; The heat pump energy efficiency ratio is calculated according to the heating capacity and the compressor power consumption of the heat pump energy efficiency model.

3. The method according to claim 1, characterized in that The step of calculating a first global warming potential of the mixed refrigerant comprises the following steps: Calculating the mass fraction of the refrigerant single substance according to the mass of the refrigerant single substance and the total mass of the mixed refrigerant; Obtaining a second global warming potential value of each of the refrigerant elements; The first global warming potential value of the mixed refrigerant is calculated according to the mass fraction of each refrigerant element in the mixed refrigerant and the second global warming potential value.

4. The method according to claim 1, characterized in that: The method of simulating the mixed refrigerant by using the mixed refrigerant life cycle carbon emission model and calculating the life cycle carbon emission of a refrigeration system after applying the mixed refrigerant according to the refrigeration energy efficiency ratio and the first global warming potential value comprises the following steps: Simulating the mixed refrigerant through a mixed refrigerant life cycle carbon emission model; Calculate the annual energy consumption of the refrigeration system according to the refrigeration energy efficiency ratio and the power of the refrigeration system; Calculate energy consumption and carbon emissions based on the annual energy consumption, carbon emission factor and service life of the refrigeration system; Calculating the carbon emissions of the mixed refrigerant based on the annual leakage of the mixed refrigerant, the leakage of the mixed refrigerant recovery, the first global warming potential, the service life of the refrigeration system and the refrigerant filling amount; The life cycle carbon emissions of the refrigeration system after applying the mixed refrigerant are determined according to the mixed refrigerant carbon emissions and the energy consumption carbon emissions.

5. The method according to claim 1, characterized in that The simulating the mixed refrigerant by using a flammability model and calculating the flammability calculation factor of the mixed refrigerant includes the following steps: Determine the elemental flammability index based on the adiabatic flame temperature and fluorine substitution rate of the elemental refrigerant; Integrating and normalizing the single-substance flammability index to obtain a flammability calculation factor of the mixed refrigerant; Alternatively, the composite action between the refrigerant elements is simulated to obtain the number of functional groups of the mixed refrigerant; The functional group quantity is input into a pre-trained artificial neural network for processing to obtain a flammability calculation factor of the mixed refrigerant.

6. The method according to claim 1, characterized in that The calculation formula for the life cycle carbon emissions is: C tot =C grid +C ref ; C grid =And sys ×EF grid ×yr; C ref =(yr×leak yr +leak re )×GWP×m ref ; Among them, C tot represents life cycle carbon emissions; C grid Represents energy consumption and carbon emissions; C ref Represents the carbon emissions of mixed refrigerants; E sys Indicates the annual energy consumption of the refrigeration system; EF grid represents the carbon emission factor; yr represents the service life of the refrigeration system; leak yr Indicates the amount of mixed refrigerant recovery leakage; re represents the annual leakage of mixed refrigerants; GWP represents the first global warming potential; m ref Indicates the refrigerant filling amount.

7. The method according to claim 1, characterized in that The expression of the objective function is: P<P req ; min(C tot ), or, C tot <C ref0 ; Where Π is the flammability calculation factor, Π req is the flammability standard; C tot is the life cycle carbon emission of the refrigeration system after the mixed refrigerant is applied, C ref0 It is the total carbon emissions of the original refrigerant used in the refrigeration system.

8. A simulation and life cycle based optimization system for mixed refrigerant components, characterized in that, include: The first module is used to generate a plurality of mixed refrigerants with different component mass ratios according to a plurality of refrigerant single substances by an exhaustive method or a genetic algorithm; A second module is used to calculate the refrigeration energy efficiency ratio, the heat pump energy efficiency ratio and the first global warming potential value of the mixed refrigerant; A third module is used to simulate the mixed refrigerant through a mixed refrigerant life cycle carbon emission model, and calculate the life cycle carbon emission of a refrigeration system after applying the mixed refrigerant according to the refrigeration energy efficiency ratio and the first global warming potential value; A fourth module is used to simulate the mixed refrigerant through a flammability model and calculate a flammability calculation factor of the mixed refrigerant; The fifth module is used to optimize the components of the life cycle carbon emissions and the flammability calculation factor according to the objective function to obtain a target mixed refrigerant.

9. An electronic device, characterized in that: including a processor and a memory; The memory is used to store programs; The processor executes the program to implement the method according to any one of claims 1 to 7.

10. A computer storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the method according to any one of claims 1 to 7 when executed by the processor.

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