Method and system for calculating cost-efficiency comprehensive index of carbon emission path, and electronic equipment

Abstract

The invention relates to a carbon emission path cost-efficiency comprehensive index calculation method and system, and electronic equipment. A research framework taking industry development requirements, measure policy analysis, coal consumption, carbon dioxide emission and economic benefit analysis as main contents is constructed, the cost-effect comprehensive index of the carbon emission path is calculated through a method of combining top-down and bottom-up, the technical method and parameters can be dynamically adjusted, the estimation method is accurate, and the method is suitable for large-scale popularization and application. The cost-efficiency selection standard is reliable, and decision support is provided for low-carbon development.

Description

Technical Field

[0001] The present invention relates to cost-effectiveness calculation, and in particular to a method, system and electronic equipment for calculating a comprehensive cost-effectiveness index of a carbon emission path. Background Art

[0002] The current carbon emission pathway cost-effectiveness analysis method mainly adopts a top-down comprehensive evaluation model. The model construction is complex, the calculation parameters are difficult to collect, and most of the international forecast data are used. It cannot accurately reflect the development of China's industry, lacks the output of the intermediate calculation process, and does not involve comprehensive judgment of cost-effectiveness analysis. Summary of the invention

[0003] The present invention proposes a method, system and electronic device for calculating the comprehensive cost-effectiveness index of carbon emission paths. A research framework with industry development needs, policy analysis, coal consumption, carbon dioxide emissions and economic benefit analysis as the main contents is constructed. The comprehensive cost-effectiveness index of carbon emission paths is calculated by combining the "top-down" and "bottom-up" methods. The technical methods and parameters can be adjusted dynamically, the estimation method is accurate, and the cost-effectiveness selection criteria are reliable, providing decision-making support for low-carbon development.

[0004] The present invention provides the following technical solution: a method for calculating a comprehensive cost-effectiveness index of a carbon emission path, comprising the following steps:

[0005] (1) The cement and cement clinker production P(s,i), the proportion of measures applied U(s,i,t), and the coal reduction coefficient CRf(s,i,t) (tons of standard coal / tons of clinker) in year i under scenario s were collected; s=1 is the baseline scenario, s=2 is the policy scenario, and s=3 is the enhanced scenario; t=1 is the energy structure adjustment measure, t=2 is the industrial structure optimization measure, t=3 is the energy-saving technology transformation measure, t=4 is the resource recycling measure, and t=5 is the end-of-pipe capture and storage measure; U(s,i,t) and CRf(s,i,t) are from the National Industrial Energy-Saving Technology and Equipment Recommended Catalog (2019-2022) and the National Industrial Energy-Saving Technology Application Guide and Cases (2019-2022); the cement and cement clinker production P(s,i) in 2020 is from the data on the website of the National Bureau of Statistics of China, and the predicted value is obtained through the prediction of experts such as the China Cement Association;

[0006] (2) Based on P(s,i) and U(s,i,t), calculate the clinker production P(s,i,t) (100 million tons) in year i under scenario s and applying measure t;

[0007] (3) Calculate the coal reduction amount CoCED(s,i) (100 million tons of standard coal) in year i by applying measure t under scenario s based on P(s,i,t) and CRf(s,i,t), where t = 1 to 4;

[0008] (4) Calculate the coal consumption of the cement industry in year i under scenario s, CoCE(s,i) (100 million tons of standard coal) based on P(s,i), fco_base and CoCED(s,i);

[0009] fco_base represents the base unit coal consumption coefficient, in tons of standard coal / ton of clinker; it is determined based on the coal consumption level in the base year, i.e. 2020, and is 0.1125 tons of standard coal / ton of clinker;

[0010] (5) Calculate Cd(s,i) based on CoCE(s,i) and EF; calculate Cp(s,i) based on P(s,i), EF_k, P(s,i,t) and CRPf(s,i,t); calculate Ce(s,i) based on P(s,i), El_base, EF_el, P(s,i,t) and CREf(s,i,t);

[0011] Cd(s,i) represents energy-related carbon emissions, in units of 100 million tons of carbon dioxide; EF represents the carbon emission coefficient of coal, which is 2.66 tons of carbon dioxide / ton of standard coal; Cp(s,i) represents the carbon emission of the production process in year i under scenario s, in units of 100 million tons of carbon dioxide; EF_k is the carbon emission factor of raw material k, which mainly refers to the carbon dioxide produced by the decomposition of limestone in the cement industry, which is 0.52 tons of carbon dioxide / ton of clinker; CRPf(s,i,t) is the process emission reduction factor for the application of measure t in year i under scenario s, in units of tons of carbon dioxide / ton of clinker, which is calculated through the China Cement Association obtained through China Cement Association and China Building Materials Research Institute; Ce(s,i) represents the indirect emissions caused by net purchased electricity and heat in year i under scenario s, in billion tons of carbon dioxide; El_base represents the net electricity consumption of the base unit cement clinker, which is 35 kWh / ton of clinker; EF_el represents the average carbon emission factor of purchased electricity, which is 0.56 kg of carbon dioxide / kWh; CREf(s,i,t) is the electricity consumption reduction coefficient of applying measure t in year i under scenario s, in kWh / ton of clinker, obtained through China Cement Association and China Building Materials Research Institute;

[0012] (6) Calculate C based on Cd(s,i), Cp(s,i), Ce(s,i), and Cccs(s,i) CE (s,i);

[0013] Cccs(s,i) represents the carbon dioxide emissions from carbon capture and storage using end-of-pipe capture and storage measures in year i under scenario s, in billion tons of carbon dioxide; C CE (s,i) represents the carbon emissions of the cement industry, in billion tons of carbon dioxide;

[0014] (7) According to C CE (s,2020),C CE(s,i) Calculate ΔC CE (s,i);

[0015] ΔC CE (s,i) is the carbon emission reduction in year i under scenario s, in billion tons; C CE (s,2020) is the carbon emissions in 2020 under scenario s, in billion tons;

[0016] (8) According to ΔC CE (s,i) calculation

[0017] is the normalized carbon emission reduction in year i under scenario s;

[0018] (9) Calculate ΔCoCE(s,i) based on CoCE(s,2020) and CoCE(s,i);

[0019] ΔCoCE(s,i) is the coal reduction in year i under scenario s, in billion tons; CoCE(s,2020) is the coal consumption in 2020 under scenario s, 177.6 million tons;

[0020] (10) Calculated according to ΔCoCE(s,i)

[0021] is the normalized coal reduction in year i under scenario s;

[0022] (11) Calculate Co(s,i) based on Cot(s,i,t), P(s,i,t), Coccs(s,i), and Cccs(s,i);

[0023] Co(s,i) is the investment cost in year i under scenario s, in 100 million yuan; Cot(s,i,t) is the cost of applying measure t in year i under scenario s, in yuan / ton of clinker, obtained through the National Recommended Catalogue of Industrial Energy-Saving Technology and Equipment (2019-2022) and the National Industrial Energy-Saving Technology Application Guide and Case Studies (2019-2022); Coccs(s,i) is the cost of collecting carbon dioxide per unit when t=5, in yuan / ton of carbon dioxide, obtained through the China Cement Association and the China Building Materials Science Research Institute, which is 1,500 yuan / ton of clinker, and a total increase of 500,000 tons from 2021 to 2025;

[0024] (12) According to ΔC CE (s,i), Co(s,i) to calculate PC CE (s,i);

[0025] PC CE (s,i) is the unit cost of carbon emission reduction in year i under scenario s, in tons / yuan;

[0026] (13) Based on PC CE (s,i) calculation

[0027] is the normalized unit cost of carbon reduction in year i under scenario s;

[0028] (14) Calculate PCoCE(s,i) based on ΔCoCE(s,i) and Co(s,i);

[0029] PCoCE(s,i) is the reduction in unit cost of coal in year i under scenario s (tons / yuan);

[0030] (15) Calculated according to PCoCE(s,i)

[0031] is the reduction in normalized unit cost of coal in year i under scenario s;

[0032] (16) Calculate CEP(s,i,p) based on CoCED(s,i), EF_p, ∝_i, i, ibase;

[0033] CEP(s,i,p) is the emission reduction of pollutant p in year i under scenario s, in 10,000 tons; EF_p is the emission coefficient of pollutant p, in kg / ton of standard coal. Pollutants p include SO2, NOx, and PM. The emission coefficients of SO2, NOx, and PM are 0.0030 kg / ton of standard coal, 0.0396 kg / ton of standard coal, and 0.0038 kg / ton of standard coal, respectively. The data are from the China Environmental Statistical Yearbook; ∝_i is the end-of-pipe control improvement rate in year i. The base year ibase is 2000, and its end-of-pipe control improvement rate is 0%, which will increase by 1% every year thereafter;

[0034] (17) Calculate TCEE(s,i) based on CEP(s,i,p) and δ_p;

[0035] TCEE(s,i) represents the pollutant emission reduction in year i under scenario s, in 10,000 tons; δ_p is the pollutant equivalent value of pollutant p, which comes from the Table of Taxable Pollutants and Equivalent Values ​​in the Annex of the Environmental Protection Tax Law of the People's Republic of China. Pollutants p include SO2, NOx, and PM.

[0036] (18) According to TCEE(s,i), ΔC CE (s,i) calculate PTCEE(s,i);

[0037] PTCEE(s,i) is the pollutant synergy reduction per unit carbon reduction in year i under scenario s, expressed in tons per 10,000 tons;

[0038] (19) Calculated according to PTCEE(s,i)

[0039] is the pollutant co-emission reduction per unit of normalized carbon reduction in year i of scenario s;

[0040] (20) According to Calculate the comprehensive cost-effectiveness index CCI(s,i) of carbon emission pathway in year i under scenario s.

[0041] Further,

[0042] In step (2), P(s,i,t)=P(s,i)×U(s,i,t);

[0043] In step (3), CoCED(s,i)=∑ t P(s,i,t)·CRf(s,i,t), where t=1~4;

[0044] In step (4), CoCE(s,i)=P(s,i)×fco_base-CoCED(s,i);

[0045] In step (5),

[0046] Cd(s,i)=CoCE(s,i)·EF; Cp(s,i)=P(s,i)·EF_k-P(s,i,t)·CRPf(s,i,t), where t=4;

[0047] Ce(s,i)=(P(s,i)·El_base·EF_el-P(s,i,t)·CREf(s,i,t)·EF_el) / 1000, where t=3;

[0048] In step (6), C CE (s,i)=Cd(s,i)+Cp(s,i)+Ce(s,i)-Cccs(s,i);

[0049] In step (7), ΔC CE (s,i)=C CE (s,2020)-C CE (s,i);

[0050] In step (8),

[0051] min(ΔC CE (1,i),ΔC CE (2,i),ΔC CE(3,i)) is the minimum carbon emission reduction in year i under each scenario, max(ΔC CE (1,i),ΔC CE (2,i),ΔC CE (3,i)) is the maximum carbon emission reduction in year i under each scenario;

[0052] In step (9), ΔCoCE(s,i)=CoCE(s,2020)-CoCE(s,i);

[0053] In step (10),

[0054]

[0055] min(ΔCoCE(1,i),ΔCoCE(2,i),ΔCoCE(3,i)) is the minimum coal reduction in year i, and max(ΔCoCE(1,i),ΔCoCE(2,i),ΔCoCE(3,i)) is the maximum coal reduction in year i;

[0056] In step (11), Co(s,i)=∑ t Cot(s,i,t)×P(s,i,t)+Coccs(s,i)×Cccs(s,i);

[0057] In step (12), PC CE (s,i)=ΔC CE (s,i) / Co(s,i);

[0058] In step (13),

[0059]

[0060] min(PC CE (1,i),PC CE (2,i),PC CE (3,i)) is the minimum carbon emission reduction per unit cost in year i, max(PC CE (1,i),PC CE (2,i),PC CE (3,i)) is the maximum carbon emission reduction per unit cost in year i;

[0061] In step (14), PCoCE(s,i)=ΔCoCE(s,i) / Co(s,i);

[0062] In step (15),

[0063]

[0064]

[0065] min(PCoCE(1,i),PCoCE(2,i),PCoCE(3,i)) is the minimum reduction of coal unit cost in year i, and max(PCoCE(1,i),PCoCE(2,i),PCoCE(3,i)) is the maximum reduction of coal unit cost in year i;

[0066] In step (16), CEP(s,i,p)=CoCED(s,i)×EF_p×(1-∝_i)^(i-ibase)×1000;

[0067] In step (17), TCEE(s,i)=∑ p CEP(s,i,p) / δ_p;

[0068] In step (18), PTCEE(s,i)=TCEE(s,i) / ΔC CE (s,i);

[0069] In step (19),

[0070]

[0071] min(PTCEE(1,i),PTCEE(2,i),PTCEE(3,i)) is the minimum value of pollutant emission reduction per unit carbon emission reduction in year i, and max(PTCEE(1,i),PTCEE(2,i),PTCEE(3,i)) is the maximum value of pollutant emission reduction per unit carbon emission reduction in year i;

[0072] In step (20),

[0073]

[0074] The system for implementing the above-mentioned method for calculating the comprehensive cost-effectiveness index of carbon emission paths includes at least:

[0075] The collection module is used to collect the cement and cement clinker production P(s,i), the proportion of measures applied U(s,i,t), and the coal reduction coefficient CRf(s,i,t) (tons of standard coal / tons of clinker) in year i under scenario s;

[0076] The first calculation module is used to calculate the clinker production P(s,i,t) (billion tons) of the application of measure t in year i under scenario s according to P(s,i) and U(s,i,t);

[0077] The second calculation module is used to calculate the coal reduction CoCED(s,i) (100 million tons of standard coal) in year i under scenario s by applying measure t according to P(s,i,t) and CRf(s,i,t);

[0078] The third calculation module is used to calculate the coal consumption CoCE(s,i) (100 million tons of standard coal) of the cement industry in year i under scenario s according to P(s,i), fco_base and CoCED(s,i);

[0079] The fourth calculation module is used to calculate Cd(s,i) according to CoCE(s,i), EF; calculate Cp(s,i) according to P(s,i), EF_k, P(s,i,t), CRPf(s,i,t); calculate Ce(s,i) according to P(s,i), El_base, EF_el, P(s,i,t), CREf(s,i,t);

[0080] The fifth calculation module is used to calculate C according to Cd(s,i), Cp(s,i), Ce(s,i), and Cccs(s,i) CE (s,i);

[0081] The sixth calculation module is used to calculate the CE (s,2020),C CE (s,i) Calculate ΔC CE (s,i);

[0082] The seventh calculation module is used to calculate the CE (s,i) calculation

[0083] An eighth calculation module, used to calculate ΔCoCE(s,i) according to CoCE(s,2020) and CoCE(s,i);

[0084] The ninth calculation module is used to calculate according to ΔCoCE(s,i)

[0085] A tenth calculation module, used for calculating Co(s,i) according to Cot(s,i,t), P(s,i,t), Coccs(s,i), and Cccs(s,i);

[0086] The eleventh calculation module is used for ΔC CE (s,i), Co(s,i) calculate PC CE (s,i);

[0087] The twelfth calculation module is used to calculate the CE (s,i) calculation

[0088] A thirteenth calculation module, used for calculating PCoCE(s,i) according to ΔCoCE(s,i) and Co(s,i);

[0089] The fourteenth calculation module is used to calculate according to PCoCE(s,i)

[0090] A fifteenth calculation module is used to calculate CEP(s,i,p) according to CoCED(s,i), EF_p, ∝_i, i, ibase;

[0091] A sixteenth calculation module is used to calculate TCEE(s,i) according to CEP(s,i,p) and δ_p;

[0092] The seventeenth calculation module is used to calculate the CE (s,i) calculate PTCEE(s,i);

[0093] The eighteenth calculation module is used to calculate according to PTCEE(s,i)

[0094] The nineteenth calculation module is used to Calculate the comprehensive cost-effectiveness index CCI(s,i) of carbon emission pathway in year i under scenario s.

[0095] An electronic device, comprising:

[0096] one or more processors;

[0097] A memory for storing one or more programs;

[0098] When the one or more programs are executed by the one or more processors, the one or more processors implement any of the above methods.

[0099] A computer-readable storage medium stores computer instructions, which, when executed by a processor, implement the steps of any of the above methods.

[0100] The beneficial effects of the present invention are:

[0101] (1) A database of five types of measures has been constructed, including energy structure adjustment measures, industrial structure optimization measures, energy-saving technology transformation measures, resource recycling measures, and end-of-pipe capture and storage measures. The database contains important carbon emission reduction measures and revolutionary technologies that are widely used in the industry, have mature technologies, and have great promotion potential. It improves the technical parameters of various aspects such as technology investment, operation, energy conservation, and emission reduction, and can provide data support for model simulation.

[0102] (2) Through bottom-up and top-down modeling methods, the internal connections and constraints of social and economic development, technological development, industry energy consumption and carbon emissions, and cost-effectiveness are characterized. The bottom-up model breaks down the impact of each factor on energy conservation and emission reduction targets from the aspects of raw materials, processes, technologies, and costs within each industry, making the prediction results and the corresponding paths of policy simulation clearer; the top-down method can quantify the macro situation, realize the input-output relationship between industries and the coupling relationship of the industrial chain, and simulate the emission reduction path that meets the target requirements through constraints such as emission reduction targets and cost-effectiveness.

[0103] This method can systematically analyze the emission reduction mechanisms of various key measures in key industries (regions) and optimize the comprehensive system path, supporting the needs of systematic, refined and implemented environmental management systems in key industries (regions) under the guidance of carbon peak and carbon neutrality goals. DETAILED DESCRIPTION

[0104] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0105] This application collects existing basic data through public materials and obtains a comprehensive index of carbon emission path cost-effectiveness through a series of calculations. The prediction results are accurate and have a guiding role in selecting the optimal scenario for carbon emission reduction.

[0106] Example 1

[0107] A method for calculating a comprehensive cost-effectiveness index of a carbon emission path is provided. In this embodiment, 2020 is used as a base year and the method comprises the following steps:

[0108] (1) The cement and cement clinker production P(s,i), the proportion of measures applied U(s,i,t), and the coal reduction coefficient CRf(s,i,t) (tons of standard coal / tons of clinker) in year i under scenario s were collected; s=1 is the baseline scenario, s=2 is the policy scenario, and s=3 is the enhanced scenario; t=1 is the energy structure adjustment measure, t=2 is the industrial structure optimization measure, t=3 is the energy-saving technology transformation measure, t=4 is the resource recycling measure, and t=5 is the end-of-pipe capture and storage measure; U(s,i,t) and CRf(s,i,t) are from the National Industrial Energy-Saving Technology and Equipment Recommended Catalog (2019-2022) and the National Industrial Energy-Saving Technology Application Guide and Cases (2019-2022);

[0109] The 2020 cement and cement clinker production P(s,2020) is derived from data on the website of the National Bureau of Statistics of China, and the forecast value is obtained through forecasts from experts such as the China Cement Association; the 2035 cement and cement clinker production P(s,2035) is approximately 680 million tons to 1.156 billion tons, with the intermediate years (2021-2034) changing at a uniform rate.

[0110] In 2035, the application ratios of energy structure adjustment measures, industrial structure optimization measures, energy-saving technology transformation measures, and resource recycling measures U(s,i,t) range from 50% to 70%, 10% to 15%, 70% to 90%, and 30% to 50%, respectively. The minimum value is taken for the baseline scenario, the maximum value is taken for the enhanced scenario, and the average of the baseline scenario and the enhanced scenario is taken for the policy scenario. The intermediate years (2021-2034) change at a uniform rate. The end-of-pipe capture measures directly act on carbon dioxide emissions and are measured by carbon dioxide capture, without involving U(s,i,t).

[0111] Table 1 Cement and cement clinker production in year i under scenario s P(s,i) (billion tons)

[0112]

[0113]

[0114] Table 2 Proportion of measures applied in year i under scenario s U(s,i,t) (%)

[0115]

[0116] Table 3 Coal reduction coefficient CRf(s,i,t) (tons of standard coal / tons of clinker) in year i under scenario s and applying measure t

[0117]

[0118] Taking the baseline scenario in 2035 as an example, it can be obtained from Tables 1 to 3 that the output of cement and cement clinker P(s,i) is 1.156 billion tons; the application ratios of energy structure adjustment measures, industrial structure optimization measures, energy-saving technology transformation measures, and resource recycling measures U(s,i,t) are 50.0%, 10.0%, 70.0%, and 30.0%, respectively; the coal reduction coefficients CRf(s,i,t) are 0.0045 tons of standard coal / ton of clinker, 0.0600 tons of standard coal / ton of clinker, 0.0020 tons of standard coal / ton of clinker, and 0.0021 tons of standard coal / ton of clinker, respectively;

[0119] (2) Based on P(s,i) and U(s,i,t), calculate the clinker production P(s,i,t) (100 million tons) in year i under scenario s and applying measure t;

[0120] P(1,2035,1)=P(1,2035)×U(1,2035,1)=1.156 billion tons of clinker×50.0%=578.00 million tons of clinker

[0121] P(1,2035,2)=P(1,2035)×U(1,2035,2)=1.156 billion tons of clinker×10.0%=115.60 million tons of clinker

[0122] P(1,2035,3)=P(1,2035)×U(1,2035,3)=1.156 billion tons of clinker×70.0%=809.20 million tons of clinker

[0123] P(1,2035,4) = P(1,2035) × U(1,2035,4) = 1.156 billion tons of clinker × 30.0% = 346.80 million tons of clinker;

[0124] (3) Calculate the coal reduction CoCED(s,i) (100 million tons of standard coal) in year i by applying measure t under scenario s based on P(s,i,t) and CRf(s,i,t);

[0125] Taking the baseline scenario in 2035 as an example, t = 1 to 4:

[0126] CoCED(1,2035)=∑ t P(s,i,t)·CRf(s,i,t)=∑ t P(s,i)×U(s,i,t)·CRf(s,i,t)=11.56

[0127] 100 million tons of clinker × 50.0% × 0.0045 tons of standard coal / ton of clinker + 1.156 billion tons of clinker × 10.0% × 0.060 tons of standard coal / ton of clinker + 1.156 billion tons of clinker × 70.0% × 0.0020 tons of standard coal / ton of clinker + 1.156 billion tons of clinker × 30.0% × 0.0021 tons of standard coal / ton of clinker = 11.88 million tons of standard coal;

[0128] (4) Calculate the coal consumption of the cement industry in year i under scenario s, CoCE(s,i) (100 million tons of standard coal) based on P(s,i), fco_base and CoCED(s,i);

[0129] Under the baseline scenario in 2035:

[0130] CoCE(s,i)=P(s,i)×fco_base-CoCED(s,i)=1.156 billion tons of clinker×0.1125 tons of standard coal / ton of clinker-0.1188 billion tons of standard coal=118.2 million tons of standard coal;

[0131] fco_base represents the base unit coal consumption coefficient, in tons of standard coal / ton of clinker, which is determined based on the coal consumption level in the base year, i.e. 2020, and is 0.1125 tons of standard coal / ton of clinker;

[0132] The results are shown in Table 4:

[0133] Table 4 Coal consumption in cement industry CoCE (s,i) (100 million tons of standard coal)

[0134]

[0135]

[0136] (5) Calculate Cd(s,i) based on CoCE(s,i) and EF; calculate Cp(s,i) based on P(s,i), EF_k, P(s,i,t) and CRPf(s,i,t); calculate Ce(s,i) based on P(s,i), El_base, EF_el, P(s,i,t) and CREf(s,i,t);

[0137] Cd(s,i) represents energy-related carbon emissions, in units of 100 million tons of carbon dioxide; EF represents the carbon emission coefficient of coal, which is 2.66 tons of carbon dioxide / ton of standard coal; Cp(s,i) represents the carbon emission of the production process in year i under scenario s, in units of 100 million tons of carbon dioxide; EF_k is the carbon emission factor of raw material k, which mainly refers to the carbon dioxide produced by the decomposition of limestone in the cement industry, which is 0.52 tons of carbon dioxide / ton of clinker; CRPf(s,i,t) is the process emission reduction factor for the application of measure t in year i under scenario s, in units of tons of carbon dioxide / ton of clinker, which is calculated through the China Cement Association obtained through China Cement Association and China Building Materials Research Institute; Ce(s,i) represents the indirect emissions caused by net purchased electricity and heat in year i under scenario s, in billion tons of carbon dioxide; El_base represents the net electricity consumption of the base unit cement clinker, which is 35 kWh / ton of clinker; EF_el represents the average carbon emission factor of purchased electricity, which is 0.56 kg of carbon dioxide / kWh; CREf(s,i,t) is the electricity consumption reduction coefficient of applying measure t in year i under scenario s, in kWh / ton of clinker, obtained through China Cement Association and China Building Materials Research Institute;

[0138] Taking the 2035 baseline scenario as an example:

[0139] CoCE(s,i) is 118.2 million tons of standard coal, P(s,i) is 1.156 billion tons of clinker, CRPf(s,i,t) is 0.0044 tons of CO2 / ton of clinker, CREf(s,i,t) is 9.5572 kWh / ton of clinker, and Cccs(s,i) is 0.3 million tons of CO2;

[0140] Cd(s,i) = CoCE(s,i) · EF = 118.2 million tons of standard coal × 2.66 tons of carbon dioxide / ton of standard coal = 314.3 million tons of carbon dioxide;

[0141] At t=4, carbon emissions will be generated in the production process, namely Cp(s,i).

[0142] Cp(s,i) = P(s,i) · EF_k - P(s,i,4) · CRPf(s,i,4) = 1.156 billion tons of clinker × 0.52 tons of CO2 / ton of clinker - 346.80 million tons of clinker × 0.0044 tons of CO2 / ton of clinker = 599.6 million tons of CO2;

[0143] Table 5 Process emission reduction factors CRPf(s,i,t) (tons of CO2 / ton of clinker) for year i using measure t under scenario s

[0144] scene Baseline scenario Policy scenarios Enhanced Scenario measure Resource recycling Resource recycling Resource recycling 2020 - - - 2021 0.0044 0.0044 0.0044 2022 0.0044 0.0044 0.0044 2023 0.0044 0.0044 0.0044 2024 0.0044 0.0044 0.0044 2025 0.0044 0.0044 0.0044 2026 0.0044 0.0044 0.0044 2027 0.0044 0.0044 0.0044 2028 0.0044 0.0044 0.0044 2029 0.0044 0.0044 0.0044 2030 0.0044 0.0044 0.0044 2031 0.0044 0.0044 0.0044 2032 0.0044 0.0044 0.0044 2033 0.0044 0.0044 0.0044 2034 0.0044 0.0044 0.0044 2035 0.0044 0.0044 0.0044

[0145] In the case of t=3, there exists Ce(s,i):

[0146] Ce(s,i) = (P(s,i)·El_base·EF_el-P(s,i,t)·CREf(s,i,t)·EF_el) / 1000 = (1.156 billion tons of clinker × 35 kWh / ton of clinker × 0.56 kg of carbon dioxide / kWh-809.20 million tons of clinker × 9.5572 kWh / ton of clinker × 0.56 kg of carbon dioxide / kWh) / 1000 = 18.3 million tons of carbon dioxide;

[0147] Table 6 Electricity consumption reduction coefficient CREf(s,i,t) (kWh / ton clinker) for the application of measure t in year i under scenario s

[0148] scene Baseline scenario Policy scenarios Enhanced Scenario measure Energy-saving technology transformation Energy-saving technology transformation Energy-saving technology transformation 2020 - - - 2021 5.9023 5.9023 5.9023 2022 5.9023 5.9023 5.9023 2023 5.9023 5.9023 5.9023 2024 5.9023 5.9023 5.9023 2025 5.9023 5.9023 5.9023 2026 7.7298 7.7298 7.7298 2027 7.7298 7.7298 7.7298 2028 7.7298 7.7298 7.7298 2029 7.7298 7.7298 7.7298 2030 7.7298 7.7298 7.7298 2031 9.5572 9.5572 9.5572 2032 9.5572 9.5572 9.5572 2033 9.5572 9.5572 9.5572 2034 9.5572 9.5572 9.5572 2035 9.5572 9.5572 9.5572

[0149] (6) Calculate C based on Cd(s,i), Cp(s,i), Ce(s,i), and Cccs(s,i) CE (s,i);

[0150] Cccs(s,i) represents the carbon dioxide emissions from carbon capture and storage using end-of-pipe capture and storage measures in year i under scenario s, in billion tons of carbon dioxide; C CE (s,i) represents the carbon emissions of the cement industry, in billion tons of carbon dioxide;

[0151] Table 7 Carbon dioxide emissions from carbon capture and storage in year i under scenario s Cccs(s,i) (billion tons of carbon dioxide)

[0152]

[0153]

[0154] C CE (s,i) = Cd(s,i) + Cp(s,i) + Ce(s,i) - Cccs(s,i) = 314.3 million tons of carbon dioxide + 599.6 million tons of carbon dioxide + 183 million tons of carbon dioxide - 0.003 million tons of carbon dioxide = 932 million tons of carbon dioxide;

[0155] The results are shown in Table 8:

[0156] Table 8 Carbon emissions C of the cement industry in year i under scenario s CE (s,i)(billion tons of carbon dioxide)

[0157] Baseline scenario Policy scenarios Enhanced Scenario 2020 13.25 13.25 13.25 2021 13.17 13.17 13.16 2022 12.86 12.86 12.86 2023 12.56 12.56 12.55 2024 12.27 12.03 11.73 2025 11.98 11.52 10.95 2026 11.71 11.04 10.23 2027 11.43 10.57 9.55 2028 11.15 10.11 8.91 2029 10.88 9.67 8.30 2030 10.61 9.24 7.73 2031 10.37 8.86 7.23 2032 10.11 8.46 6.72 2033 9.84 8.08 6.25 2034 9.58 7.70 5.80 2035 9.32 7.33 5.38

[0158] (7) According to C CE (s,2020),C CE (s,i) Calculate ΔC CE (s,i);

[0159] ΔC CE (s,i) is the carbon emission reduction in year i under scenario s, in billion tons; C CE (s,2020) is the carbon emissions in 2020 under scenario s, in billion tons;

[0160] ΔC CE (s,i)=C CE (s,2020)-C CE (s,i);

[0161] Taking the 2035 baseline scenario as an example:

[0162] ΔC CE (s,i)=C CE (s,2020)-C CE (s,i) = 1.325 billion tons - 932 billion tons = 393 million tons;

[0163] The results are shown in Table 9:

[0164] Table 9 Carbon emission reduction ΔC in year i under scenario s CE (s,i)(billion tons of carbon dioxide)

[0165] Baseline scenario Baseline scenario Baseline scenario 2020 0 0 0 2021 0.08 0.08 0.08 2022 0.38 0.38 0.39 2023 0.68 0.69 0.69 2024 0.97 1.22 1.52 2025 1.26 1.73 2.30 2026 1.54 2.20 3.01 2027 1.82 2.68 3.70 2028 2.09 3.13 4.34 2029 2.37 3.57 4.94 2030 2.64 4.00 5.51 2031 2.88 4.39 6.02 2032 3.14 4.78 6.52 2033 3.40 5.17 7.00 2034 3.66 5.55 7.44 2035 3.93 5.91 7.87

[0166] (8) According to ΔC CE (s,i) calculation

[0167] is the normalized carbon emission reduction in year i under scenario s;

[0168] In order to fully calculate the comprehensive cost-effectiveness index of the carbon emission path under the carbon emission path, take the 2035 baseline scenario as an example:

[0169]

[0170] min(ΔC CE (1,i),ΔC CE (2,i),ΔC CE (3,i)) is the minimum carbon emission reduction in year i under each scenario, max(ΔC CE (1,i),ΔC CE (2,i),ΔC CE (3,i)) is the maximum carbon emission reduction in year i under each scenario;

[0171] (9) Calculate ΔCoCE(s,i) based on CoCE(s,2020) and CoCE(s,i);

[0172] ΔCoCE(s,i) is the coal reduction in year i under scenario s, in billion tons; CoCE(s,2020) is the coal consumption in 2020 under scenario s, 177.6 million tons;

[0173] ΔCoCE(1,2035)=CoCE(s,2020)-CoCE(s,i)=177.6 million tons-118.2 million tons=59.5 million tons;

[0174] The results are shown in Table 10:

[0175] Table 10 Coal reduction ΔCoCE(s,i) in year i under scenario s (billion tons)

[0176] Coal reduction Baseline scenario Baseline scenario Baseline scenario 2020 0.029 0.029 0.030 2021 0.072 0.073 0.074 2022 0.115 0.116 0.118 2023 0.157 0.190 0.232 2024 0.199 0.262 0.339 2025 0.234 0.325 0.433 2026 0.276 0.392 0.528 2027 0.317 0.457 0.617 2028 0.358 0.520 0.702 2029 0.400 0.583 0.783 2030 0.428 0.630 0.846 2031 0.469 0.689 0.918 2032 0.510 0.746 0.986 2033 0.552 0.803 1.051 2034 0.595 0.860 1.113

[0177] (10) Calculated according to ΔCoCE(s,i)

[0178] is the normalized coal reduction in year i under scenario s;

[0179]

[0180]

[0181] (11) Calculate Co(s,i) based on Cot(s,i,t), P(s,i,t), Coccs(s,i), and Cccs(s,i);

[0182] Co(s,i) is the investment cost in year i under scenario s, in 100 million yuan; Cot(s,i,t) is the cost of applying measure t in year i under scenario s, in yuan / ton of clinker, obtained through the National Recommended Catalogue of Industrial Energy-Saving Technology and Equipment (2019-2022) and the National Industrial Energy-Saving Technology Application Guide and Case Studies (2019-2022); Coccs(s,i) is the unit cost of collecting carbon dioxide when t=5, in yuan / ton of carbon dioxide, obtained through the China Cement Association and China Building Materials Research Institute, which is 1,500 yuan / ton of clinker, with a total increase of 500,000 tons from 2021 to 2025; in order to fully calculate the comprehensive cost-effectiveness index of the carbon emission path under the carbon emission path, taking 2035 under the baseline scenario as an example, t=1~5.

[0183] Co(1,2035)=∑ t Cot(s,i,t)×P(s,i,t)+Coccs(1,2035)×Cccs(s,i)=(107.53 yuan /

[0184] Tons of clinker × 50%) × 1.156 billion tons + (1,171.01 yuan / ton of clinker × 10%) × 1.156 billion tons + (149.66 yuan / ton of clinker × 70%) × 1.156 billion tons + (28.67 yuan / ton of clinker × 30%) × 1.156 billion tons + 1,500 yuan / ton × 300,000 tons / 10,000 = 329.021 billion yuan;

[0185] The results are shown in Table 11:

[0186] Table 11 Investment cost Co(s,i) (100 million yuan)

[0187]

[0188]

[0189] (12) According to ΔC CE (s,i), Co(s,i) calculate PC CE (s,i);

[0190] PC CE (s,i) is the unit cost of carbon emission reduction in year i under scenario s, in tons / yuan;

[0191] Taking the 2035 baseline scenario as an example:

[0192] PC CE (1,i)=ΔC CE (s,i) / Co(s,i)=393 million tons / 329.021 billion yuan=0.00119 tons / yuan;

[0193] (13) Based on PC CE (s,i) calculation

[0194] is the normalized unit cost of carbon reduction in year i under scenario s;

[0195]

[0196] min(PC CE (1,i),PC CE (2,i),PC CE (3,i)) is the minimum carbon emission reduction per unit cost in year i, max(PC CE (1,i),PC CE (2,i),PC CE (3,i)) is the maximum carbon emission reduction per unit cost in year i;

[0197] (14) Calculate PCoCE(s,i) based on ΔCoCE(s,i) and Co(s,i);

[0198] PCoCE(s,i) is the reduction in unit cost of coal in year i under scenario s (tons / yuan);

[0199] PCoCE(1,2035)=ΔCoCE(s,i) / Co(s,i)=0.5947 billion tons / 329.021 billion yuan=0.000181 tons / yuan;

[0200] (15) Calculated according to PCoCE(s,i)

[0201] is the reduction in normalized unit cost of coal in year i under scenario s;

[0202]

[0203] min(PCoCE(1,i),PCoCE(2,i),PCoCE(3,i)) is the minimum reduction of coal unit cost in year i, and max(PCoCE(1,i),PCoCE(2,i),PCoCE(3,i)) is the maximum reduction of coal unit cost in year i;

[0204] (16) Calculate CEP(s,i,p) based on ΔCoCE(s,i), EF_p, ∝_i, i, ibase;

[0205] CEP(s,i,p) is the emission reduction of pollutant p in year i under scenario s, in 10,000 tons; EF_p is the emission coefficient of pollutant p, in kg / ton of standard coal. Pollutant p includes SO2, NOx 、PM,SO2、NO x The emission coefficients of PM2.5, PM3.5 and PM4.5 are 0.003043 kg / t standard coal, 0.0396 kg / t standard coal and 0.0038 kg / t standard coal respectively. The data are from the China Environmental Statistical Yearbook. ∝_i is the end-of-pipe control improvement rate in year i. The base year ibase is 2000, and its end-of-pipe control improvement rate is 0%, which will increase by 1% every year thereafter.

[0206] Take the SO2 emission reduction in 2035 as an example:

[0207] CEP(s,i,p)=ΔCoCE(s,i)×EF_p×(1-∝_i)^(i-ibase)×1000=0.595 billion tons of standard coal×0.003043 kg / ton of standard coal×(1-15%)×1000=153,900 tons;

[0208] (17) Calculate TCEE(s,i) based on CEP(s,i,p) and δ_p;

[0209] Take the emission reduction of three pollutants (SO2, NOx, PM) in 2035 as an example:

[0210] TCEE(s,i)=∑ p CEP(s,i,p) / δ_p=15,390 tons / 9,500 tons+199,980 tons

[0211] / 0.95+1.902 million tons / 2.18=235,400 tons;

[0212] TCEE(s,i) represents the pollutant emission reduction in year i under scenario s, in 10,000 tons; δ_p is the pollutant equivalent value of pollutant p, which comes from the "Taxable Pollutants and Equivalent Value Table" in the Annex of the "Environmental Protection Tax Law of the People's Republic of China". Pollutants p include: SO2, NO x , PM; in this embodiment, the pollutant equivalent value δ_p of SO2 in 2035 is 0.95, the pollutant equivalent value δ_p of NOx is 0.95, and the pollutant equivalent value δ_p of PM is 2.18;

[0213] (18) According to TCEE(s,i), ΔC CE (s,i) calculate PTCEE(s,i);

[0214] Taking the 2035 baseline scenario as an example:

[0215] PTCEE(s,i)=TCEE(s,i) / ΔC CE (s,i) = 235,400 tons / 393 million tons = 6 tons / 10,000 tons;

[0216] PTCEE(s,i) is the pollutant synergy reduction per unit carbon reduction in year i under scenario s, expressed in tons per 10,000 tons;

[0217] (19) Calculated according to PTCEE(s,i)

[0218] Take 2035 as an example:

[0219] is the pollutant co-emission reduction per unit of normalized carbon reduction in year i of scenario s;

[0220]

[0221] min(PTCEE(1,i),PTCEE(2,i),PTCEE(3,i)) is the minimum value of pollutant emission reduction per unit carbon emission reduction in year i, and max(PTCEE(1,i),PTCEE(2,i),PTCEE(3,i)) is the maximum value of pollutant emission reduction per unit carbon emission reduction in year i;

[0222] The results are shown in Table 12:

[0223] Table 12 Indicators under the 2035 scenario

[0224]

[0225] (20) According to Calculate the comprehensive cost-effectiveness index of carbon emission pathway in year i under scenario s (CCI(s,i));

[0226]

[0227] The results are shown in Table 13:

[0228] Table 13 Normalized results of each indicator and comprehensive cost-effectiveness index of carbon emission pathway under scenario 2035

[0229]

[0230]

[0231] Compare the carbon emission path cost-effectiveness comprehensive index under each scenario, and select the scenario with the largest carbon emission path cost-effectiveness comprehensive index as the optimal scenario. After comparison, CCI (3,2035) = 0.800 is the largest, so the enhanced scenario is selected as the optimal scenario.

[0232] Example 2

[0233] An electronic device, comprising:

[0234] one or more processors;

[0235] A memory for storing one or more programs;

[0236] When one or more programs are executed by one or more processors, the one or more processors implement the method described in Example 1.

[0237] A computer-readable storage medium stores computer instructions, which, when executed by a processor, implement the steps of the method described in Example 1.

[0238] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The above-mentioned program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0239] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A method for calculating a comprehensive carbon emission path cost-effectiveness index, characterized in that: The steps include: (1) Collect cement and cement clinker production P(s,i), measure application ratio U(s,i,t), and coal reduction coefficient CRf(s,i,t) (tons of standard coal / tons of clinker) in year i under scenario s; s=1 is the baseline scenario, s=2 is the policy scenario, and s=3 is the enhanced scenario; t=1 is the energy structure adjustment measure, t=2 is the industrial structure optimization measure, t=3 is the energy-saving technology transformation measure, t=4 is the resource recycling measure, and t=5 is the end-of-pipe capture and storage measure; (2) Based on P(s,i) and U(s,i,t), calculate the clinker production P(s,i,t) (100 million tons) in year i under scenario s and applying measure t; (3) Calculate the coal reduction CoCED(s,i) (100 million tons of standard coal) in year i under scenario s by applying measure t based on P(s,i,t) and CRf(s,i,t), where t = 1 to 4; (4) Calculate the coal consumption of the cement industry in year i under scenario s (CoCE(s,i) (100 million tons of standard coal) based on P(s,i), fco_base and CoCED(s,i); fco_base represents the base unit coal consumption coefficient, in tons of standard coal / ton of clinker; (5) Calculate Cd(s,i) based on CoCE(s,i) and EF; calculate Cp(s,i) based on P(s,i), EF_k, P(s,i,t) and CRPf(s,i,t); calculate Ce(s,i) based on P(s,i), El_base, EF_el, P(s,i,t) and CREf(s,i,t); Cd(s,i) represents energy-related carbon emissions, in units of 100 million tons of carbon dioxide; EF represents the carbon emission coefficient of coal; Cp(s,i) represents the carbon emissions of the production process in year i under scenario s, in units of 100 million tons of carbon dioxide; EF_k is the carbon emission factor of raw material k; CRPf(s,i,t) is the process emission reduction factor for the application of measure t in year i under scenario s, in units of tons of carbon dioxide / ton of clinker; Ce(s,i) represents the indirect emissions caused by the net purchased electricity and heat in year i under scenario s, in units of 100 million tons of carbon dioxide; El_base represents the net electricity consumption of the base unit cement clinker; EF_el represents the average carbon emission factor of purchased electricity; CREf(s,i,t) is the electricity consumption reduction coefficient for the application of measure t in year i under scenario s, in units of kilowatt-hours / ton of clinker; (6) Calculate C based on Cd(s,i), Cp(s,i), Ce(s,i), and Cccs(s,i) CE (s,i); Cccs(s,i) represents the carbon dioxide emissions from carbon capture and storage using end-of-pipe capture and storage measures in year i under scenario s, in billion tons of carbon dioxide; C CE (s,i) represents the carbon emissions of the cement industry, in billion tons of carbon dioxide; (7) According to C CE (s,2020),C CE (s,i) Calculate ΔC CE (s,i); ΔC CE (s,i) is the carbon emission reduction in year i under scenario s, in billion tons; C CE (s,2020) is the carbon emissions in 2020 under scenario s, in billion tons; (8) According to ΔC CE (s,i) calculation is the normalized carbon emission reduction in year i under scenario s; (9) Calculate ΔCoCE(s,i) based on CoCE(s,2020) and CoCE(s,i); ΔCoCE(s,i) is the coal reduction in year i under scenario s, in billion tons; CoCE(s,2020) is the coal consumption in 2020 under scenario s; (10) Calculated according to ΔCoCE(s,i) is the normalized coal reduction in year i under scenario s; (11) Calculate Co(s,i) based on Cot(s,i,t), P(s,i,t), Coccs(s,i), and Cccs(s,i); Co(s,i) is the investment cost in year i under scenario s, in RMB 100 million; Cot(s,i,t) is the cost of applying measure t in year i under scenario s, in RMB / ton of clinker; Coccs(s,i) is the cost of collecting carbon dioxide, in RMB / ton of carbon dioxide; (12) According to ΔC CE (s,i), Co(s,i) to calculate PC CE (s,i); PC CE (s,i) is the unit cost of carbon emission reduction in year i under scenario s, in tons / yuan; (13) Based on PC CE (s,i) calculation is the normalized unit cost of carbon reduction in year i under scenario s; (14) Calculate PCoCE(s,i) based on ΔCoCE(s,i) and Co(s,i); PCoCE(s,i) is the reduction in unit cost of coal in year i under scenario s (tons / yuan); (15) Calculated according to PCoCE(s,i) is the reduction in normalized unit cost of coal in year i under scenario s; (16) Calculate CEP(s,i,p) based on CoCED(s,i), EF_p, ∝_i, i, ibase; CEP(s,i,p) is the emission reduction of pollutant p in year i under scenario s, in 10,000 tons; EF_p is the emission coefficient of pollutant p, in kg / ton of standard coal, and pollutants p include SO2, NOx, and PM; ∝_i is the end-of-pipe control improvement rate in year i, the base year ibase is 2000, and its end-of-pipe control improvement rate is 0%, and then increases by 1% every year; (17) Calculate TCEE(s,i) based on CEP(s,i,p) and δ_p; TCEE(s,i) represents the pollutant emission reduction in year i under scenario s, in 10,000 tons; δ_p is the pollutant equivalent value of pollutant p; (18) According to TCEE(s,i), ΔC CE (s,i) calculate PTCEE(s,i); PTCEE(s,i) is the pollutant synergy reduction per unit carbon reduction in year i under scenario s, expressed in tons per 10,000 tons; (19) Calculated based on PTCEE(s,i) is the pollutant co-emission reduction per unit of normalized carbon reduction in year i of scenario s; (20) According to Calculate the carbon emission path cost-effectiveness comprehensive index CCI(s,i) of the carbon emission path in year i under scenario s.

2. The method according to claim 1, characterized in that In step (2), P(s,i,t)=P(s,i)×U(s,i,t); In step (3), CoCED(s,i)=∑ t P(s,i,t)·CRf(s,i,t), where t=1~4; In step (4), CoCE(s,i)=P(s,i)×fco_base-CoCED(s,i); In step (5), Cd(s,i)=CoCE(s,i)·EF; Cp(s,i)=P(s,i)·EF_k-P(s,i,t)·CRPf(s,i,t); Ce(s,i)=(P(s,i)·El_base·EF_el-P(s,i,t)·CREf(s,i,t)·EF_el) / 1000, where t=3; In step (6), C CE (s,i) = Cd(s,i) + Cp(s,i) + Ce(s,i) - Cccs(s,i); In step (7), ΔC CE (s,i)=C CE (s,2020)-C CE (s,i); In step (8), min(ΔC CE (1,i),ΔC CE (2,i),ΔC CE (3,i)) is the minimum carbon emission reduction in year i under each scenario, max(ΔC CE (1,i),ΔC CE (2,i),ΔC CE (3,i)) is the maximum carbon emission reduction in year i under each scenario; In step (9), ΔCoCE(s,i)=CoCE(s,2020)-CoCE(s,i); In step (10), min(ΔCoCE(1,i),ΔCoCE(2,i),ΔCoCE(3,i)) is the minimum coal reduction in year i, and max(ΔCoCE(1,i),ΔCoCE(2,i),ΔCoCE(3,i)) is the maximum coal reduction in year i; In step (11), Co(s,i) = ∑ t Cot(s,i,t) × P(s,i,t) + Coccs(s,i) × Cccs(s,i); In step (12), PC CE (s,i)=ΔC CE (s,i) / Co(s,i); In step (13), min(PC CE (1,i),PC CE (2,i),PC CE (3,i)) is the minimum carbon emission reduction per unit cost in year i, max(PC CE (1,i),PC CE (2,i),PC CE (3,i)) is the maximum carbon emission reduction per unit cost in year i; In step (14), PCoCE(s,i)=ΔCoCE(s,i) / Co(s,i); In step (15), min(PCoCE(1,i),PCoCE(2,i),PCoCE(3,i)) is the minimum reduction of coal unit cost in year i, and max(PCoCE(1,i),PCoCE(2,i),PCoCE(3,i)) is the maximum reduction of coal unit cost in year i; In step (16), CEP(s,i,p)=CoCED(s,i)×EF_p×(1-∝_i)^(i-ibase)×1000; In step (17), TCEE(s,i)=∑ p CEP(s,i,p) / δ_p; In step (18), PTCEE(s,i)=TCEE(s,i) / ΔC CE (s,i); In step (19), min(PTCEE(1,i),PTCEE(2,i),PTCEE(3,i)) is the minimum value of pollutant emission reduction per unit carbon emission reduction in year i, and max(PTCEE(1,i),PTCEE(2,i),PTCEE(3,i)) is the maximum value of pollutant emission reduction per unit carbon emission reduction in year i; In step (20), 3. A system for implementing a method for calculating a carbon emission path cost-effectiveness comprehensive index as claimed in claim 1 or 2, characterized in that: At least: The collection module is used to collect the cement and cement clinker production P(s,i), the proportion of measures applied U(s,i,t), and the coal reduction coefficient CRf(s,i,t) (tons of standard coal / tons of clinker) in year i under scenario s; The first calculation module is used to calculate the clinker production P(s,i,t) (billion tons) of the application of measure t in year i under scenario s according to P(s,i) and U(s,i,t); The second calculation module is used to calculate the coal reduction CoCED(s,i) (100 million tons of standard coal) in year i under scenario s by applying measure t according to P(s,i,t) and CRf(s,i,t); The third calculation module is used to calculate the coal consumption CoCE(s,i) (100 million tons of standard coal) of the cement industry in year i under scenario s according to P(s,i), fco_base and CoCED(s,i); The fourth calculation module is used to calculate Cd(s,i) according to CoCE(s,i), EF; calculate Cp(s,i) according to P(s,i), EF_k, P(s,i,t), CRPf(s,i,t); calculate Ce(s,i) according to P(s,i), El_base, EF_el, P(s,i,t), CREf(s,i,t); The fifth calculation module is used to calculate C according to Cd(s,i), Cp(s,i), Ce(s,i), and Cccs(s,i) CE (s,i); The sixth calculation module is used to calculate the CE (s,2020),C CE (s,i) Calculate ΔC CE (s,i); The seventh calculation module is used to calculate the CE (s,i) calculation An eighth calculation module, used to calculate ΔCoCE(s,i) according to CoCE(s,2020) and CoCE(s,i); The ninth calculation module is used to calculate according to ΔCoCE(s,i) A tenth calculation module, used for calculating Co(s,i) according to Cot(s,i,t), P(s,i,t), Coccs(s,i), and Cccs(s,i); The eleventh calculation module is used for ΔC CE (s,i), Co(s,i) to calculate PC CE (s,i); The twelfth calculation module is used to calculate the CE (s,i) calculation A thirteenth calculation module, used for calculating PCoCE(s,i) according to ΔCoCE(s,i) and Co(s,i); The fourteenth calculation module is used to calculate according to PCoCE(s,i) A fifteenth calculation module is used to calculate CEP(s,i,p) according to CoCED(s,i), EF_p, ∝_i, i, ibase; A sixteenth calculation module is used to calculate TCEE(s,i) according to CEP(s,i,p) and δ_p; The seventeenth calculation module is used to calculate the CE (s,i) calculate PTCEE(s,i); The eighteenth calculation module is used to calculate according to PTCEE(s,i) The nineteenth calculation module is used to Calculate the comprehensive cost-effectiveness index CCI(s,i) of carbon emission pathway in year i under scenario s.

4. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 2.

5. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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