An industry technology-based pollution and carbon reduction synergistic path optimization method and system

Abstract

The application provides a pollution reduction and carbon reduction synergistic path optimization method and system based on industry technology, and the method comprises the following steps: selecting one or more production processes or technical improvement technologies of any one industry in pollution reduction and carbon reduction synergistic technology data of each industry; determining one of the production processes of each industry selected as a reference production process; solving the optimal activity level of each technology based on linear programming under the condition of meeting each constraint; calculating the cost required for reducing one unit of emission; calculating the total emission reduction amount of each technology under the condition of the optimal activity level of each technology; and constructing a marginal emission reduction cost curve to obtain the priority order of the application of pollution reduction and carbon reduction technologies among industries and within industries. The application has the advantages that: the selection of various emissions under multiple constraint conditions and the quantification of the activity level of the lowest emission reduction cost target are realized; the complexity of model operation is effectively reduced, and the system operation efficiency is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of carbon emission reduction and air pollution control, and specifically relates to a pollution reduction and carbon reduction collaborative path optimization method and system based on industry technology. BACKGROUND

[0002] Currently, the coordinated promotion of pollution reduction and carbon reduction has become an inevitable choice for the development of green economy in various countries. Among them, clear optimization of technical paths is an important way to achieve the coordinated development of pollution reduction and carbon reduction. In order to promote the coordinated development of pollution reduction and carbon reduction, various enterprises and research institutions have proposed numerous pollution reduction and carbon reduction collaborative technologies, and some of the technologies have been applied or demonstrated. However, due to the involvement of numerous industries, the complexity of the technology types, and the high cost of transformation, it is necessary to optimize carbon emission reduction and carbon sink measures that have coordinated space in terms of technology, economy, and environmental characteristics in order to achieve the coordinated development of pollution reduction and carbon reduction in the most optimal way.

[0003] Currently, various models have been developed at home and abroad to analyze the carbon or pollutant emission reduction technology path of different industries, such as MESSAGEix, TIMEs, and GGAM. However, such models have the following shortcomings: (1) Such models have a high learning cost, involving a large number of parameters, formulas, and codes, and it is difficult to understand the calculation method and process of the model in a short period of time. (2) Such models have a high running cost, requiring certain computer software and hardware foundation, and the operation is relatively complex. (3) Such models require a large amount of basic data support, and it is difficult to quickly achieve industry pollution reduction and carbon reduction technology path analysis.

[0004] The Chinese invention patent with publication number CN 118396239A, "A pollution reduction and carbon reduction effect evaluation method for power plants", discloses an evaluation method, which specifically includes: first, obtaining the change correlation index of each two kinds of emissions according to the correlation of the change characteristics of the emission parameters of each two kinds of emissions before and after improvement; second, obtaining the overall deviation standard correlation index of each kind of emission according to the deviation standard correlation index of each kind of emission and all other emissions; then adjusting the initial weight according to the overall change correlation index and the overall deviation standard correlation index of each kind of emission to obtain the corrected weight of each kind of emission; finally, evaluating the effect of pollution reduction and carbon reduction.

[0005] The invention patent is an evaluation of the effect of pollution reduction and carbon reduction related technologies in the power industry, and cannot be applied to the evaluation of the effect of pollution reduction and carbon reduction related technologies in other industries. At the same time, the invention patent cannot prioritize the application of various technologies based on the evaluation results, so it cannot clearly determine the application path of various pollution reduction and carbon reduction technologies in the power and other industries at the optimal activity level. SUMMARY

[0006] The present application aims to overcome the defects of the prior art, which is difficult to implement and requires a large amount of basic data support.

[0007] To achieve the above-mentioned purpose, the present application provides a pollution reduction and carbon reduction synergistic path optimization method based on industry technology, comprising:

[0008] Step S1: selecting one or more production processes or technical improvement technologies of any industry in the pollution reduction and carbon reduction synergistic technology data of each industry; for each selected production process of an industry, determining one of the production processes as a benchmark production process;

[0009] Step S2: solving the optimal activity level of each technology based on linear programming;

[0010] Step S3: calculating the cost required for each unit of emission reduction;

[0011] Step S4: calculating the total emission reduction of each technology under the optimal activity level of each technology;

[0012] Step S5: constructing a marginal emission reduction cost curve to obtain the priority order of the application of pollution reduction and carbon reduction technologies among industries and within industries.

[0013] As an improvement of the above method, the pollution reduction and carbon reduction synergistic technology data of each industry includes two types of technology, i.e. production process and technical improvement technology, and four types of parameters, i.e. benchmark information, cost information, emission reduction information and operation information;

[0014] Among them, the emission factors of production processes and the emission reduction potentials of technical improvement technologies include information of 5 types of emissions, i.e. CO2, particulate matter, SO2, NOx and VOCs.

[0015] As an improvement of the above method, the formula of the linear programming solution is:

[0016]

[0017] Among them, x i,t is the activity level of technology t of industry i; a i,t and b i,t are the lower limit and upper limit of the activity level of technology t of industry i, respectively; C i,t is the unit total cost of technology t of industry i; Demand i is the total demand of industry i; R i,t,e is the unit emission reduction potential of technology t of industry i for emission type e; target e is the emission reduction target of the emission.

[0018] As an improvement of the above method, the calculating the cost of reducing one unit of emission includes:

[0019] AC i,t,e = C i,t / R i,t,e

[0020] Wherein, AC i,t,e is the cost of reducing one unit of emission of the technology t of the industry i; C i,t is the total cost of the technology t of the industry i; R i,t,e is the potential of reducing one unit of emission of the technology t of the industry i.

[0021] As an improvement of the above method, the calculating the total emission reduction of each technology under the optimal activity level of each technology includes:

[0022] TR i,t,e = x i,t ·R i,t,e

[0023] Wherein, TR i,t,e is the total emission reduction of the technology t of the industry i; R i,t,e is the potential of reducing one unit of emission of the technology t of the industry i; x i,t is the activity level of the technology t of the industry i.

[0024] As an improvement of the above method, the constructing the marginal emission reduction cost curve to obtain the priority order of the application of the emission reduction and carbon reduction technologies between industries and within industries includes:

[0025] Based on the total emission reduction potential TR i,t,e and the unit emission reduction cost AC i,t,e of each technology, a marginal emission reduction cost curve is constructed; the horizontal coordinate of the marginal emission reduction cost curve is the emission reduction potential, and the vertical coordinate is the unit emission reduction cost;

[0026] Each technology forms a column based on its total emission reduction potential TR i,t,e and the unit emission reduction cost AC i,t,e , and the columns of all technologies are arranged from low to high according to the unit emission reduction cost AC i,t,e . A continuous marginal emission reduction cost curve is obtained by fitting the midpoints of the upper ends of all columns using a linear, quadratic or exponential function.

[0027] Based on the marginal abatement cost curve, the priority order of the application of pollution reduction and carbon reduction technologies among industries and within an industry is determined: under the abatement target, the industry with lower marginal abatement cost is given priority to carry out pollution reduction and carbon reduction, and when the marginal abatement cost of the industry exceeds that of other industries, the pollution reduction and carbon reduction of other industries is carried out; for an industry, the technology with the lowest unit abatement cost is given priority to be applied, and other technologies with higher unit abatement cost are gradually applied.

[0028] As an improvement of the above method, before step S2, the following step is further included: checking whether it can be solved in a linear programming manner:

[0029] checking whether the upper limit of the total activity level of the selected technology in the industry is greater than or equal to the total demand of the industry;

[0030] checking whether the abatement target of the emission is greater than or equal to 0; and

[0031] checking whether the total abatement potential of each type of emission of the selected technology under the upper limit of its activity level is greater than the abatement target of the emission.

[0032] The application also provides a pollution reduction and carbon reduction collaborative path optimization system based on industry technology, which is realized based on the above method, and the system comprises:

[0033] a database module for storing pollution reduction and carbon reduction collaborative technology data of each industry;

[0034] a data screening module for selecting one or more production processes or technical improvement technologies of any industry in the pollution reduction and carbon reduction collaborative technology data of each industry; for each selected production process of an industry, one of the production processes is determined as a reference production process;

[0035] a module for determining the optimal activity level for determining the optimal activity level of each technology based on linear programming manner under the condition of meeting each constraint;

[0036] a module for calculating the unit emission cost for calculating the cost required for reducing one unit of emission;

[0037] a module for calculating the total abatement amount of each technology for calculating the total abatement amount of each technology under the condition of the optimal activity level of each technology;

[0038] a module for obtaining the application order of pollution reduction and carbon reduction technologies for constructing a marginal abatement cost curve to obtain the priority order of the application of pollution reduction and carbon reduction technologies among industries and within an industry.

[0039] Compared with the prior art, the application has the following advantages:

[0040] 1. This invention establishes a comprehensive collaborative path optimization method based on multi-industry pollution reduction and carbon reduction technologies. By optimizing multi-industry technologies, it realizes the quantification of various technology selections and activity levels for various emissions under multiple constraints and the goal of minimum emission reduction costs.

[0041] 2. This application provides 442 technical data from more than ten industries in China by constructing a database module, significantly reducing the cost of data collection and providing basic data support for the analysis of pollution reduction and carbon reduction technology pathways.

[0042] 3. This application takes into account the CO2 emission reduction of the technology and the emission reduction of four types of emissions: particulate matter, SO2, NOx, and VOCs. It not only constructs the marginal emission reduction cost curve of carbon, but also constructs the marginal emission reduction cost curves of the four types of pollutants.

[0043] 4. The path optimization module of this application selects three core constraints in the existing path optimization system, effectively reducing the complexity of model operation and improving system operation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 Shown is a flow chart of the collaborative path optimization method for pollution reduction and carbon reduction based on industry technology;

[0045] Figure 2 The figure shows the marginal emission reduction cost curve;

[0046] Figure 3 Shown is the architecture diagram of the collaborative path optimization system for pollution reduction and carbon reduction based on industry technology. DETAILED DESCRIPTION

[0047] The technical solution of this application is described in detail below with reference to the accompanying drawings.

[0048] Example 1

[0049] like Figure 1 As shown, the present invention provides a pollution reduction and carbon reduction collaborative path optimization method based on industry technology, which is used to find the optimal way to achieve the pollution reduction and carbon reduction collaborative development path. The method utilizes the pollution reduction and carbon reduction collaborative technology data of various industries and adopts a linear programming method to determine the optimal technology path combination under the corresponding emission reduction target.

[0050] Data on collaborative technologies for pollution reduction and carbon reduction across various industries includes two technology types: production processes and technological transformation technologies, and four parameter types: benchmark information, cost information, emission reduction information, and operational information. Production processes refer to the entire process of producing a specific product, such as coal-fired power generation and blast furnace ironmaking. Mechanical transformation technologies refer to mechanical modifications within a specific production process, such as waste heat recovery and utilization technologies.

[0051] The production process includes 10 parameters, i.e., time benchmark, scale benchmark, investment cost, fixed cost, variable cost, emission factor, operation life, utilization rate, popularization rate and standard coal consumption. The emission factor of the production process and the emission reduction potential of the technical improvement technology include information of 5 types of emissions, i.e., CO2 and particulate matter, SO2, NOx and VOCs, thereby providing support for the analysis of the pollution reduction and carbon reduction collaborative technology; the emission factor refers to the emission amount of CO2, particulate matter, SO2, NOx and VOCs per unit production of the technology; the fixed cost refers to the annual fixed cost in the unit scale production of the technology, such as fixed equipment maintenance cost, employee salary cost and the like, also referred to as operation cost; the variable cost refers to the cost required for purchasing raw materials, fuel and the like in the unit scale production; the operation life refers to the service life of the technology; the utilization rate refers to the ratio of the time that the technology can be operated in a year to the whole year; the popularization rate refers to the application ratio of the technologies producing the same product in China; and the standard coal consumption refers to the energy consumed for producing one unit of product, which is converted into standard coal consumption;

[0052] The technical improvement technology includes 7 parameters, i.e., time benchmark, scale benchmark, investment cost, emission reduction potential, energy saving potential, operation life and popularization rate. The time benchmark refers to the time when the technical parameters are collected or the technology is applied; the scale benchmark refers to the annual production scale corresponding to the technical parameters; the investment cost refers to the investment amount of the unit scale of the technology; the emission reduction potential refers to the emission reduction amount of CO2, particulate matter, SO2, NOx and VOCs per unit product produced after the application of the technology; and the energy saving potential refers to the energy saving amount per unit product produced after the application of the technology.

[0053] The pollution reduction and carbon reduction collaborative path optimization method based on the industry technology includes the following steps:

[0054] Step 1: Technology selection. One or more production processes or technical improvement technologies of any industry in the pollution reduction and carbon reduction collaborative technology data are selected. Meanwhile, one of the production processes of each industry selected needs to be determined as a benchmark production process. The emission factor of the benchmark production process will be used as the benchmark of the other production processes of the industry to calculate the emission reduction potential of the other production processes.

[0055] Step 2: Confirmation of technical parameters. The default technical parameters of the selected technology are confirmed. The modifiable parameters of the production process include 5 parameters, i.e., investment cost, fixed cost, variable cost, emission factor (including the emission factor of 5 types of emissions, i.e., CO2 and particulate matter, SO2, NOx and VOCs) and operation life. The modifiable parameters of the technical improvement technology include 4 parameters, i.e., investment cost, fixed cost, emission reduction potential (including the emission reduction potential of 5 types of emissions, i.e., CO2 and particulate matter, SO2, NOx and VOCs) and operation life.

[0056] Step 3: Determine the constraints. Determine the three constraints required for technical optimization:

[0057] Constraint 1: For any technology, its output should be within a range, that is, there is a maximum and minimum output. Therefore, it is necessary to impose upper and lower limits on the output of the technology, namely the lower limit and upper limit of the activity level. The minimum lower limit of the activity level is 0, the maximum upper limit of the activity level is infinity, and the upper limit of the activity level should be greater than or equal to the lower limit of the activity level. The formula is as follows:

[0058] ACT i,t,min ≤ACT i,t ≤ACT i,t,max #(1)

[0059] Among them, ACT i,t is the activity level of technology t in industry i; ACT i,t,min The lower limit of the activity level of the technology; ACT i,t,max is the upper limit of the activity level of this technology.

[0060] Constraint 2: For an industry, the output of each technology should meet the industry's total demand level. Therefore, it is necessary to impose an industry total output constraint, that is, a demand level constraint. The formula is as follows:

[0061]

[0062] Among them, Demand i is the total demand for products produced by industry i.

[0063] Constraint 3: To achieve pollution reduction and carbon reduction, the selected technology should achieve a certain degree of carbon and pollutant emission reduction. Therefore, it is necessary to impose emission reduction target constraints. The formula is as follows:

[0064]

[0065] Among them, Target e It is the emission reduction target of carbon or pollutant e. i,t,e is the emission reduction potential of each technology t for emission e in industry i.

[0066] Step 4: Preliminary check of solvability. To ensure that the benchmark technology, parameters, and constraints set after steps 1 to 3 can achieve the linear programming optimization in the subsequent steps, this step will conduct a preliminary check on the benchmark technology, parameters, and constraints set. A total of 3 checks are performed:

[0067] Check 1: If a production process is selected for an industry, check whether a baseline production process has been set for that industry. If no baseline production process has been set, an error will be reported.

[0068] Check 2: Check the upper limit of the total activity level of the selected technology in an industry, that is, ∑ i,t ACT i,t,max , is it greater than or equal to the total demand of the industry? i If it is less than the total demand of the industry, an error will be reported.

[0069] Check 3: Check the emission reduction target Pollution_reduction e Is it greater than or equal to 0? If it is less than 0, an error is reported.

[0070] Step 5: Calculation of emission reduction potential of production process unit. For production process, its emission reduction potential is calculated using the following formula:

[0071] R i,t,e =(EF i,baseline,e -EF i,t,e )#(4)

[0072] Among them, R i,t,e EF is the unit emission reduction potential of technology t in industry i for emission type e. i,baseline,e EF is the emission factor of the emissions involved in the benchmark production process of the industry; i,t,e Emission factors for emissions involved in the production processes selected for the industry.

[0073] Step 6: Secondary check of solvability: To ensure that the emission reduction potential calculated in Step 5 can be used to achieve the linear programming optimization in the subsequent steps, this step will check the emission reduction potential of the selected technology and the constraints in Step 3.

[0074] A total of 1 inspection was performed:

[0075] Check 1: Check whether the total emission reduction potential of the selected technology (including production process and machine modification technology) for various types of emissions under the upper limit of its activity level is greater than the emission reduction target, that is, to determine:

[0076]

[0077] If the total emission reduction potential of the selected technology for each type of emission under the upper limit of its activity level is less than the emission reduction target, an error is reported.

[0078] Step 7: Calculate the total unit cost. The total unit cost here refers to the total cost required to produce one unit of product. The total unit cost equals the annualized investment cost plus fixed cost plus variable cost. The formula for calculating the annualized investment cost is:

[0079] ACC i,t =CRF×IC i,t #(6)

[0080] CRF = r x (r + 1) y / [(r + 1) y - 1]# (7)

[0081] Where, ACC i,t is the annualized investment cost of technology t for industry i. IC i,t is the investment cost of the technology. CRF is the capital recovery factor. y is the life of the technology. r is the discount rate, which is 7% by default, but can be changed to any value.

[0082] The formula for the total cost per unit of technology t for industry i is:

[0083] C i,t = ACC i,t + FC i,t + VC i,t # (8)

[0084] Where, C i,t is the total cost per unit of technology t for industry i. FC i,t is the fixed cost of the technology. VC i,t is the variable cost of the technology.

[0085] Step 8: Linear programming solution. The optimal activity levels of each technology that meet all the constraints can be solved by linear programming based on the total cost per unit from equation (8) and the constraints from equations (1) to (3). The theoretical mathematical model is:

[0086]

[0087] Where, x i,t is the activity level of technology t for industry i. a i,t and b i,t are the lower and upper limits of the activity level of the technology, respectively.

[0088] Step 9: Calculate the cost of emission reduction per unit. The cost of emission reduction per unit refers to the cost required to reduce one unit of emissions. The calculation formula is:

[0089] AC i,t,e = C i,t / R i,t,e # (10)

[0090] Where, AC i,t,e is the cost of emission reduction per unit of technology t for industry i for emissions e.

[0091] Step 10: Calculate the total emission reduction potential of the technology. The total emission reduction potential refers to the total emission reduction of each technology under the activity level obtained from equation (9). The calculation formula is:

[0092] TR i,t,e = x i,t · R i,t,e #(11)

[0093] wherein, TR i,t,e is the total emission reduction potential of technology t for industry i.

[0094] Step eleven: constructing the marginal emission reduction cost curve. Based on the total emission reduction potential TR i,t,e and the unit emission reduction cost AC i,t,e , the marginal emission reduction cost curve is constructed. The horizontal coordinate is the emission reduction potential, and the vertical coordinate is the unit emission reduction cost. Each technology can form a column based on its total emission reduction potential TR i,t,e and the unit emission reduction cost AC i,t,e . Arranging the columns of all technologies from low to high according to the unit emission reduction cost AC i,t,e can form a marginal emission reduction cost curve, that is, as the degree of pollution reduction and carbon reduction deepens, the marginal emission reduction cost rises. On this basis, the upper end midpoint of all columns can be fitted by a linear, quadratic, exponential function, etc., to obtain a continuous marginal emission reduction cost curve, as shown in Figure 2 .

[0095] Based on the marginal emission reduction cost, the priority order of pollution reduction and carbon reduction technology application among industries and within industries can be determined. Under a certain emission reduction target, industries with lower marginal emission reduction costs should be given priority to carry out pollution reduction and carbon reduction (industry A), and when the marginal emission reduction cost of this industry exceeds that of other industries (point a), pollution reduction and carbon reduction in other industries (industry B) can be carried out. Figure 2 For industries, technologies with lower unit emission reduction costs should be given priority, and other technologies with higher unit emission reduction costs should be gradually applied. Figure 2 Figure 2 For industries, technologies with lower unit emission reduction costs should be given priority, and other technologies with higher unit emission reduction costs should be gradually applied.

[0096] Embodiment 2

[0097] The application also provides a pollution reduction and carbon reduction coordination path optimization system based on industry technology, which is realized based on the above method. The system comprises:

[0098] a database module for storing pollution reduction and carbon reduction coordination technology data of each industry;

[0099] a data filtering module for selecting one or more production processes or technical improvement technologies of any industry in the pollution reduction and carbon reduction coordination technology data of each industry; for each selected production process of an industry, determining one of the production processes as a reference production process;

[0100] ​A module for determining optimal activity level is configured to solve the optimal activity level of each technology based on linear programming method under the condition of meeting each constraint.

[0101] A module for calculating unit emission cost is configured to calculate the cost required for reducing one unit of emission.

[0102] A module for calculating total emission reduction of each technology is configured to calculate the total emission reduction of each technology under the condition of optimal activity level of each technology.

[0103] A module for obtaining the application sequence of pollution reduction and carbon reduction technology is configured to construct a marginal emission reduction cost curve to obtain the priority sequence of the application of pollution reduction and carbon reduction technology among industries and within industries.

[0104] The present application can also provide a computer device, comprising at least one processor, memory, at least one network interface and user interface. Each component in the device is coupled together through a bus system. It can be understood that the bus system is used to realize the connection communication between the components. In addition to the data bus, the bus system also includes power bus, control bus and state signal bus.

[0105] The user interface can include a display, a keyboard or a pointing device. For example, a mouse, a trackball, a touchpad or a touch screen, etc.

[0106] It can be appreciated that the memory in the embodiments disclosed in the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (Read-Only Memory, ROM), a programmable read-only memory (Programmable ROM, PROM), an erasable programmable read-only memory (Erasable PROM, EPROM), an electrically erasable programmable read-only memory (Electrically EPROM, EEPROM) or a flash memory. The volatile memory can be a random access memory (Random Access Memory, RAM) used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM), synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (Synchlink DRAM, SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DRRAM). The memory described herein is intended to include but not limited to these and any other suitable types of memory.

[0107] In some embodiments, the memory stores elements, executable modules or data structures, or a subset thereof, or an extended set thereof: an operating system and an application program.

[0108] Among them, the operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application program includes various application programs, such as a media player (Media Player), a browser (Browser), etc., for implementing various application services. The program for implementing the method of the embodiments of the present disclosure can be included in the application program.

[0109] In the above-described embodiments, the processor can be configured to perform the steps of the above-described method by invoking the program or instructions stored in the memory, in particular, the program or instructions stored in the application program.

[0110] performing the steps of the above-described method.

[0111] The method can be applied to a processor or implemented by the processor. The processor can be an integrated circuit chip having a signal processing capability. In implementation process, the steps of the method can be completed by hardware integrated logic circuit or by software form of instruction in the processor. The processor can be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic device, discrete hardware component. The methods disclosed above can be implemented or executed by the processor. The general purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed above can be directly embodied as a hardware code executed by the processor or a combination of hardware and software modules in the processor. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register, or other mature storage medium in the art. The storage medium is located in the storage memory, and the processor reads information in the storage memory and combines the hardware to complete the steps of the method.

[0112] It can be understood that the embodiments described in the present application can be realized by hardware, software, firmware, middleware, microcode or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field-Programmable Gate Arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for executing the functions described in the present application, or a combination thereof.

[0113] For software implementation, the functions of the present application can be implemented by executing the functional modules (such as processes, functions, etc.) of the present application. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0114] The application further provides a nonvolatile storage medium for storing the computer program. When the computer program is executed by a processor, each step in the above method embodiment can be implemented.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application is described in detail with reference to the embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the present application, and all of them should be covered in the scope of the claims of the present application.

Claims

1. A collaborative path optimization method for pollution reduction and carbon reduction based on industry technologies, including: Step S1: Select one or more production processes or technological transformation technologies of any industry in the collaborative technology data on pollution reduction and carbon reduction in various industries; For each industry's selected production process, determine one of the production processes as the benchmark production process; Step S2: solving the optimal activity level of each technology based on satisfying various constraints based on a linear programming method; Step S3: Calculate the cost required to reduce emissions by one unit; Step S4: Calculate the total emission reduction of each technology under the optimal activity level conditions of each technology; Step S5: construct marginal emission reduction cost curves to obtain the priority of pollution reduction and carbon reduction technology application between and within industries; The linear programming solution is: Among them, x i,t is the activity level of technology t in industry i; a i,t and b i,t are the lower limit and upper limit of the activity level of technology t in industry i; C i,t is the total unit cost of technology t in industry i; demand i is the total demand of industry i; R i,t,e target is the unit emission reduction potential of technology t in industry i for emission type e; e To set emission reduction targets; The calculation of the cost required to reduce emissions by one unit includes: AC i,t,e =C i,t / R i,t,e Among them, AC i,t,e C is the unit emission reduction cost of technology t for industry i for emission e; i,t is the total unit cost of technology t in industry i, expressed as: C i,t =ACC i,t +FC i,t +VC i,t Among them, FC i,t is the fixed cost of the technology; VC i,t is the variable cost of the technology; ACC i,t is the annualized investment cost of technology t in industry i, expressed as: ACC i,t =CRF×IC i,t CRF=r×(r+1) y / [(r+1) y -1] Among them, IC i,t is the investment cost of the technology; CRF is the capital recovery factor; y is the service life of the technology; r is the discount rate; R i,t,e is the unit emission reduction potential of technology t in industry i for emission type e, expressed as: R i,t,e =(EF i,baseline,e -EF i,t,e ) Among them, EF i,baseline,e EF is the emission factor of the emissions involved in the benchmark production process of the industry; i,t,e Emission factors for emissions involved in the production processes selected for the industry; The calculations above include the total emission reductions for each technology under the optimal activity level conditions of each technology, including: TR i,t,e =x i,t ·R i,t,e Among them, TR i,t,e is the total emission reduction of emission e by technology t in industry i; R i,t,e is the unit emission reduction potential of technology t in industry i for emission type e; x i,t is the activity level of technology t belonging to industry i; The marginal emission reduction cost curve is constructed to obtain the priority of pollution reduction and carbon reduction technology application between and within industries, including: Total emission reduction potential TR based on each technology i,t,e and AC per unit emission reduction i,t,e Constructing a marginal emission reduction cost curve, wherein the horizontal axis of the marginal emission reduction cost curve is emission reduction potential and the vertical axis is unit emission reduction cost; Each technology is based on its total emission reduction potential TR i,t,e and AC per unit emission reduction i,t,e Form a column and divide the columns of each technology into AC according to the unit emission reduction consumption i,t,e Arrange from low to high, and use a linear, quadratic or exponential function to fit the upper midpoints of all the columns to obtain a continuous marginal emission reduction cost curve; Based on the marginal emission reduction cost curve, the priority of applying pollution reduction and carbon reduction technologies between and within industries is clarified: under the emission reduction target, priority is given to promoting pollution reduction and carbon reduction in industries with lower marginal emission reduction costs. When the marginal emission reduction cost of an industry exceeds that of other industries, pollution reduction and carbon reduction in other industries will be switched; within an industry, priority is given to applying the technology with the lowest unit emission reduction cost, and then gradually applying other technologies with higher unit emission reduction costs.

2. The method for optimizing the coordinated path of pollution reduction and carbon reduction based on industry technology according to claim 1 is characterized in that: The data on collaborative technologies for pollution reduction and carbon reduction in various industries include two types of technologies: production processes and technological transformation technologies, and four types of parameters: benchmark information, cost information, emission reduction information, and operational information. Among them, the emission factors of the production process and the emission reduction potential of the technical transformation technology include information on five types of emissions: CO2, particulate matter, SO2, NOx and VOCs.

3. The method for optimizing the coordinated path of pollution reduction and carbon reduction based on industry technology according to claim 1 is characterized in that: Before step S2, the method further includes: checking whether a linear programming method can be used to solve the problem: Check whether the upper limit of the total activity level of the selected technology in the industry is greater than or equal to the total demand of the industry; Checking whether the emission reduction target is greater than or equal to 0; and Check whether the total emission reduction potential of the selected technology for each type of emission under the upper limit of its activity level is greater than the emission reduction target.

4. The pollution reduction and carbon reduction collaborative path optimization system based on industry technology according to claim 1 is implemented based on the method according to any one of claims 1 to 3, characterized in that: The system comprises: A database module for storing data on collaborative technologies for pollution reduction and carbon reduction in various industries; The data screening module is used to select one or more production processes or technological transformation technologies from any industry in the pollution reduction and carbon reduction collaborative technology data of various industries; for each industry's selected production process, one of the production processes is determined as the benchmark production process; Determine the optimal activity level module, which is used to solve the optimal activity level of each technology based on satisfying various constraints based on linear programming; The module for calculating the unit emission cost is used to calculate the cost required for reducing one unit of emission; A module for calculating the total emission reductions for each technology, which is used to calculate the total emission reductions for each technology under the conditions of its optimal activity level; and A pollution reduction and carbon reduction technology application sequence module is obtained to construct a marginal emission reduction cost curve and obtain the priority of pollution reduction and carbon reduction technology application between and within industries.

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