Method for depicting marginal carbon reduction cost curve of high-energy-consumption industry

Abstract

A method for depicting a marginal carbon reduction cost curve of a high-energy-consumption industry belongs to the field of low-carbon transformation simulation of the high-energy-consumption industry, and specifically comprises the following steps of: firstly, combining an actual production process and an energy consumption structure of the high-energy-consumption industry, and aiming at five typical high-energy-consumption industries of steel, cement, petrochemical engineering, electric power and coal; 117 energy-saving and emission-reducing technologies with feasibility and economic and environmental benefits are screened by the system; secondly, the marginal carbon reduction cost of each technology is calculated by adopting an expert-based MACC method, and the emission reduction potential and implementation cost of each technology are evaluated in combination with industrial actual carbon emission data; and finally, based on an energy system fitting model of an exponential function, a marginal carbon reduction cost function of the high-energy-consumption industry is constructed, a marginal carbon reduction cost curve of the high-energy-consumption industry is fitted, and the MACC established by the method can visually display the cost-benefit relationship of different technologies, so that the method is suitable for popularization and application. And a theoretical basis and a technical reference are provided for an energy-saving and emission-reducing policy and a green transformation path of the high-energy-consumption industry.

Description

Technical Field

[0001] The present invention belongs to the field of low-carbon transformation simulation of high-energy-consuming industries, and specifically provides a method for characterizing marginal carbon reduction cost curves of high-energy-consuming industries. Background Art

[0003] The implementation of low-carbon technologies not only helps reduce CO2 emissions, but also promotes the efficient use of resources and the rapid development of clean energy. Considering the comprehensive balance between emission reduction costs and economic feasibility, how to further reduce the cost of CO2 emission reduction is of great practical significance for finding the optimal emission reduction plan. The marginal carbon reduction cost reflects the unit cost that an enterprise or industry needs to pay when implementing additional emission reduction measures. It is one of the key parameters for analyzing the effectiveness of emission reduction policies, optimizing emission reduction paths, and building a carbon trading mechanism.

[0004] However, there are still many difficulties in accurately describing the marginal carbon reduction cost curve of high-energy-consuming industries. On the one hand, current research on marginal costs is mainly concentrated at the micro level of enterprises, focusing on the calculation and analysis of the unit emission reduction costs of high-energy-consuming enterprises, and lacks a comprehensive analysis of the entire industry level. On the other hand, although some domestic scholars have focused on the marginal cost research of industries, they only calculate the marginal carbon reduction cost of industries and fit their total emission reduction cost curves in the form of function integration. They do not consider the fitting of the marginal carbon reduction cost curve, and have not conducted in-depth research and analysis on the emission reduction potential of industries. Therefore, when constructing the marginal carbon reduction cost curve of high-energy-consuming industries, it is necessary to fully consider technological progress and scale effects to realize the dynamic changes of marginal costs of different technologies at each emission reduction stage. Summary of the invention

[0005] In order to solve the above technical problems, the present invention proposes a method for characterizing the marginal carbon reduction cost curve of high-energy-consuming industries, which solves the problems in the prior art.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] A method for characterizing marginal carbon reduction cost curves in high energy consumption industries comprises the following steps:

[0008] 1) In combination with the actual production process and energy consumption structure of high-energy-consuming industries, investigate and select relevant energy-saving and emission-reduction technologies from relevant CPCs;

[0009] 2) Based on the list of energy-saving and emission-reduction technologies selected for each high-energy-consuming industry, the expert-based MACC method is used to calculate the unit carbon reduction cost of each emission reduction technology, and a model based on an exponential function is used to fit the marginal carbon reduction cost curve of each high-energy-consuming industry in the corresponding year;

[0010] 3) By comparing and analyzing the marginal carbon reduction costs of various high-energy-consuming industries under different carbon reduction ratios, this paper explores the dynamic changes of the marginal carbon reduction costs of different high-energy-consuming industries and their impact on the achievement of emission reduction targets.

[0011] Further, the expert-based MACC method described in step 1) is as follows:

[0012] The expert-based MACC method is also called the technology cost curve. This method usually relies on the experts' experience and knowledge and prediction of technological development. It quantitatively evaluates the cost and emission reduction potential of specific emission reduction technologies or measures through expert questionnaires, technical consultations and industry data. By sorting the emission reduction costs of various technologies from low to high, the marginal carbon reduction cost curve can be constructed.

[0013] Furthermore, the energy system fitting model based on the exponential function described in step 2) is specifically as follows:

[0014] In order to accurately capture the nonlinear increasing characteristics of marginal costs in different emission reduction stages, which is helpful to achieve accurate fitting of MACC, a model based on exponential function is adopted to fit the MAC of high-energy-consuming industries, so as to achieve quantitative display of MAC of high-energy-consuming industries. In the exponential function model adopted, the MAC and carbon reduction ratio of high-energy-consuming industries are characterized as follows:

[0015] MAC(R)=a·e b·R (1)

[0016] Where: R represents the emission reduction ratio, that is, the ratio of the industry’s emission reduction to the industry’s total CO2 emissions. Assuming that the industry’s total CO2 emissions are A Total , the industry emission reduction is C Total , the unit is 10,000 tons, then the emission reduction ratio can be expressed as C Total / A Total , the unit is %;

[0017] The converted expression of carbon reduction ratio is as follows:

[0018]

[0019] Furthermore, the unit cost calculation method of each emission reduction technology in the high energy consumption industry described in step 3) is as follows:

[0020] The MAC calculation formula for a single technology is as follows:

[0021]

[0022] Where: MAC(T i ) represents the unit emission reduction cost of technology i, that is, the marginal carbon reduction cost, in yuan / ton; INVC irepresents the investment cost of technology i, in ten thousand yuan; AO represents the average investment period of technology, 15 years is taken in the middle; CER i It represents the carbon emission reduction of technology i, in 10,000 tons.

[0023] Furthermore, the method for depicting the marginal carbon reduction cost curve of a high-energy-consuming industry is characterized in that the data and sources of the emission reduction technologies of the high-energy-consuming industry are as follows:

[0024] At present, the main low-carbon emission reduction means in high-energy-consuming industries include energy efficiency improvement, clean energy substitution, production process improvement, etc. Through the comprehensive utilization of various energy-saving and emission reduction technologies, the carbon emissions of high-energy-consuming industries can be effectively reduced, and the green and low-carbon transformation of high-energy-consuming industries can be promoted. The present invention refers to the 2016 and 2017 editions of the National Key Energy-Saving and Low-Carbon Technology Promotion Catalog (Energy-Saving and Emission Reduction Part) issued by the state, and the National Industrial Energy-Saving Technology and Equipment Recommended Catalog (2018-2020), and a total of 117 low-carbon emission reduction technologies are selected to analyze the emission reduction costs of five types of high-energy-consuming industries in 2020.

[0025] Furthermore, the method for depicting the marginal carbon reduction cost curve of a high energy-consuming industry is characterized by comprising:

[0026] Energy-saving and emission-reduction technology library module for high-energy-consuming industries: Based on the actual production processes and energy consumption structure of high-energy-consuming industries, a total of 117 energy-saving and emission-reduction technologies with feasibility, economic and environmental benefits were systematically screened for five typical high-energy-consuming industries, namely steel, cement, petrochemicals, electricity and coal;

[0027] Module for calculating and characterizing marginal carbon reduction costs in energy-intensive industries: The module uses the expert-based MACC method to calculate the marginal carbon reduction costs of various technologies, and combines actual industry data to evaluate the emission reduction potential and implementation costs of each technology; the module uses the exponential function-based model proposed by Nobel Prize winner Nordhaus to fit the marginal carbon reduction cost curves of various energy-intensive industries in 2020;

[0028] In addition, the module for comparative analysis of marginal carbon reduction cost curves of high-energy-consuming industries: by comparatively analyzing the marginal carbon reduction costs of various high-energy-consuming industries under different carbon reduction ratios, this module explores the dynamic changes in marginal carbon reduction costs of different high-energy-consuming industries and their impact on the achievement of emission reduction targets.

[0029] Beneficial effects of the present invention:

[0030] 1. This invention takes into full account a number of emission reduction technologies, policy factors and economic complexity, constructs a marginal carbon reduction cost curve for high-energy-consuming industries, reflects the dynamic changes in the marginal costs of different technologies at each emission reduction stage, and solves the problem that previous models failed to fully consider factors such as technological progress and economies of scale.

[0031] 2. The invention innovatively improves the quantification accuracy of marginal carbon reduction costs, providing an important reference for optimizing resource allocation and improving the investment benefits of emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a framework diagram for analyzing marginal carbon reduction costs in high energy consumption industries of the present invention;

[0033] Figure 2 It is a marginal carbon reduction cost curve fitting model diagram established for the typical high energy consumption industry of steel in the present invention;

[0034] Figure 3 It is a marginal carbon reduction cost curve fitting model diagram established for typical high-energy-consuming industries in petrochemical industry of the present invention;

[0035] Figure 4 It is a marginal carbon reduction cost curve fitting model diagram established for the typical high energy consumption industry of cement in the present invention;

[0036] Figure 5 It is a marginal carbon reduction cost curve fitting model diagram established for a typical high-energy-consuming power industry of the present invention;

[0037] Figure 6 It is a marginal carbon reduction cost curve fitting model diagram established for typical high-energy-consuming coal industries in the present invention. DETAILED DESCRIPTION

[0038] The following is a detailed description of the technical solution of the application in conjunction with the accompanying drawings. The described embodiments are only part of the embodiments involved in this patent. All non-innovative embodiments of other researchers in this field based on this embodiment are within the scope of protection of this patent.

[0039] The flow chart of the present invention is as follows Figure 1 A method for depicting a marginal carbon reduction cost curve for a high energy consumption industry is shown, comprising the following steps:

[0040] S1, combined with the actual production process and energy consumption structure of high-energy-consuming industries, investigated and selected 117 energy-saving and emission-reduction technologies from the National Industrial Energy-Saving Technology and Equipment Recommended Catalogue;

[0041] Refer to the 2016 and 2017 editions of the National Key Energy-Saving and Low-Carbon Technology Promotion Catalogue (Energy-Saving and Emission Reduction Section) and the National Industrial Energy-Saving Technology and Equipment Recommendation Catalogue.

[0042] (2018-2020), a total of 117 low-carbon emission reduction technologies were selected to analyze the emission reduction costs of five high-energy-consuming industries in 2020.

[0043] S2, based on the selected energy-saving and emission reduction technology list of each high-energy-consuming industry, the expert-based MACC method is used to calculate the unit carbon reduction cost of each emission reduction technology.

[0044] This paper takes 2020 as the research node, selects a total of 117 low-carbon emission reduction technologies to construct the MACC of five high-energy-consuming industries: cement, steel, petrochemicals, electricity and coal, and uses the expert MACC method to calculate the MAC of a single technology. The formula is as follows:

[0045]

[0046] Where: MAC(T i ) represents the unit emission reduction cost of technology i, that is, the marginal carbon reduction cost, in yuan / ton; INVC i represents the investment cost of technology i, in ten thousand yuan; AO represents the average investment period of technology (enterprise), which is 15 years in this invention; CER i It represents the carbon emission reduction of technology i, in 10,000 tons.

[0047] The list of emission reduction technologies selected by each industry and the calculated marginal carbon reduction costs are shown in Tables 1 to 5.

[0048] Table 1 List of CO2 emission reduction technologies in China's steel industry

[0049]

[0050]

[0051] Table 2 List of CO2 emission reduction technologies in China's petrochemical industry

[0052]

[0053]

[0054] Table 3 List of CO2 emission reduction technologies in China's cement industry

[0055]

[0056] Table 4 List of CO2 emission reduction technologies in China's power industry

[0057]

[0058]

[0059] Table 5 List of CO2 emission reduction technologies in China's coal industry

[0060]

[0061]

[0062] S3, based on the selected energy-saving and emission reduction technology list of each high-energy-consuming industry and the calculated marginal carbon reduction cost, the expert MACC method is used to arrange them in order from low to high, and then the exponential function-based model proposed by Nobel Prize winner in Economics Nordhaus is used to fit the marginal carbon reduction cost curve of various high-energy-consuming industries in 2020.

[0063] In the exponential function model adopted by the present invention, the MAC and carbon reduction ratio of high energy consumption industries can be characterized as follows:

[0064] MAC(R)=a·e b·R (2)

[0065] Where: R represents the emission reduction ratio, that is, the ratio of the industry’s emission reduction to the industry’s total CO2 emissions. Assuming that the industry’s total CO2 emissions are A Total , the industry emission reduction is C Total , the unit is 10,000 tons, then the emission reduction ratio can be expressed as C Total / A Total , unit is %.

[0066] The converted expression of carbon reduction ratio is as follows:

[0067]

[0068] Based on the above formula, as well as the carbon reduction technology list and marginal carbon cost of each high-energy-consuming industry, a marginal carbon reduction cost curve fitting analysis was conducted on five high-energy-consuming industries: cement, steel, petrochemicals, electricity, and coal. The marginal carbon reduction cost curves of the five high-energy-consuming industries were obtained, as shown in the figure below: Figure 2-Figure 6 shown.

[0069] S4. Based on the established marginal carbon reduction cost curves for the five types of high-energy-consuming industries, a comparative analysis of the marginal carbon reduction costs of each high-energy-consuming industry under different carbon reduction ratios is conducted to explore the dynamic changes in the marginal carbon reduction costs of different high-energy-consuming industries and their impact on the achievement of emission reduction targets.

[0070] Depend on Figure 2-Figure 6 It can be seen that the MAC of each high-energy-consuming industry grows exponentially with the increase in carbon reduction, reflecting that as the amount of carbon reduction increases, emission reduction work is gradually becoming more complex and costly.

[0071] The MACC slope of the steel, petrochemical and power industries has grown slowly, indicating that these three industries have a high degree of maturity in emission reduction technology and can effectively apply existing emission reduction technologies and management measures to achieve relatively low-cost emission reduction. Therefore, it is easier for them to achieve emission reduction targets in the early stages of emission reduction, and when the carbon reduction ratio increases, the required MAC increase is smaller.

[0072] On the contrary, the fitting parameter a of the cement and coal industries is small, the slope increases rapidly, and MAC shows a higher leap when the carbon reduction ratio increases. This trend reflects its limitations in emission reduction technology innovation and production process improvement. Specifically, in the cement production process, the traditional high-energy consumption process makes it difficult to implement carbon reduction measures, resulting in more economic costs to achieve a higher carbon reduction ratio; for the coal industry, its emission reduction technology usually involves higher operating costs; in addition, its economic model relies on lower fuel costs, which makes it face higher economic pressure when reducing emissions. From the perspective of production process improvement and raw material substitution, the production process of the cement industry often relies on high-temperature calcination process, which results in extremely high carbon emissions due to the use of traditional raw materials such as limestone. Although there are some alternative technologies, their maturity and economic feasibility have not yet met the requirements of large-scale application, resulting in limited promotion effect. The coal industry relies on the production model of high-carbon fuels. Although technologies such as CCUS have been applied, the implementation of these technologies often requires long-term operating costs, which poses a challenge to its economic affordability. In addition, the market structure and policy environment of coal generally do not encourage the application of high-cost emission reduction technologies, further increasing the difficulty of emission reduction in the industry. Therefore, when the carbon reduction ratio increases further, the marginal carbon reduction cost of these two industries will show a significant increase.

[0073] In order to effectively compare the changes in MACC of high-energy-consuming industries at the same carbon reduction ratio, the MACC at carbon reduction ratios of 0.5%, 1.0% and 1.5% were selected for analysis. The MACC of each industry is shown in Table 6.

[0074] Table 6 MAC of five high energy-consuming industries under different carbon reduction ratios

[0075]

[0076] The marginal carbon reduction cost model compares and analyzes the marginal cost changes of five types of high-energy-consuming industries when the carbon reduction ratio is 0.5%, 1.0% and 1.5%. The marginal carbon reduction cost of the coal industry jumped from 3.0763 yuan / ton CO2 at 0.5% to 808.1241 yuan / ton CO2 at 1.5%, reflecting that the coal industry needs to overcome the technical barriers of traditional high carbon dependence when increasing the carbon reduction ratio, and also face the dual pressures of diminishing marginal returns of emission reduction and economic challenges. In contrast, although the marginal costs of the electricity and cement industries also increased significantly with the increase in carbon reduction ratio, the increase was relatively slow, which were 64.4 yuan / ton CO2 and 27.0 yuan / ton CO2 respectively at 1.5%, and increased to 4.77 and 17.56 times at 0.5%. Although the growth multiple of cement is relatively high, its marginal cost at a carbon reduction ratio of 0.5% is only 1.53 yuan / ton CO2, so its marginal carbon reduction cost is still relatively low. This shows that although the cement and electricity industries face certain cost increases in the process of promoting emission reduction, their carbon reduction paths have strong technical feasibility and economic affordability, and the cost pressure of emission reduction measures is relatively low. The steel and petrochemical industries showed relatively low growth. The marginal cost of the steel industry was 31.5 yuan / ton CO2 at 1.5%, which increased to 1.83 times at 0.5%, while the marginal cost of the petrochemical industry was 13.94 yuan / ton CO2, which increased by only 1.59% compared with the cost at 0.5%. The relatively low level of marginal cost reflects that the petrochemical and steel industries can more effectively control costs and have a higher cost-effectiveness ratio when increasing the intensity of emission reduction and carbon reduction. By quantifying the marginal cost curves of various industries, we can more accurately capture the nonlinear trend of cost changes, show the economic differences of high-energy-consuming industries under different emission reduction ratios, and provide important quantitative basis for formulating precise carbon reduction policies by industry and stage.

[0077] Example

[0078] This embodiment consists of five typical high-energy-consuming industries, namely cement, steel, petrochemical, power and coal industries. This example analysis can be used to prove the effectiveness of the method proposed in the present invention.

[0079] According to the steps of the present invention, the marginal carbon reduction cost of high-energy-consuming industries is characterized. Taking five typical high-energy-consuming industries as examples, the marginal carbon reduction cost curves are characterized and the marginal carbon reduction costs of high-energy-consuming industries at different carbon reduction ratios are compared and analyzed. The fitting results show that the fitting accuracy of the models of various industries is relatively high, among which the square residual coefficient R of the cement and petrochemical industries is 2Reaching 0.9688 and 0.9824, the reliability and accuracy of the model are fully verified. It can be seen that under different carbon reduction ratios, the MACC of each high-energy-consuming industry is significantly different, which is mainly determined by the industry's technical foundation, energy structure and the economy of emission reduction technology; among them, the coal industry has a sharp rise in MACC at a higher carbon reduction ratio, and faces greater economic challenges when reducing emissions. The cement and petrochemical industries show a relatively slow cost growth, indicating that they have strong technical feasibility and economic adaptability. The present invention can improve the quantitative accuracy of the marginal carbon reduction cost, and provide an important reference for optimizing resource allocation and improving the investment efficiency of emission reduction.

[0080] The above description is only a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any modification or equivalent change made based on the technical essence of the present invention still falls within the scope of protection required by the present invention.

Claims

1. A method for characterizing marginal carbon reduction cost curves in high energy consumption industries, characterized in that: The steps include: 1) In combination with the actual production process and energy consumption structure of high-energy-consuming industries, investigate and select relevant energy-saving and emission-reduction technologies from relevant CPCs; 2) Based on the list of energy-saving and emission-reduction technologies selected for each high-energy-consuming industry, the expert-based MACC method is used to calculate the unit carbon reduction cost of each emission reduction technology, and a model based on an exponential function is used to fit the marginal carbon reduction cost curve of each high-energy-consuming industry in the corresponding year; 3) By comparing and analyzing the marginal carbon reduction costs of various high-energy-consuming industries under different carbon reduction ratios, this paper explores the dynamic changes of the marginal carbon reduction costs of different high-energy-consuming industries and their impact on the achievement of emission reduction targets.

2. The method for depicting marginal carbon reduction cost curve of high energy consumption industries according to claim 1 is characterized by: The expert-based MACC method described in step 1) is as follows: The expert-based MACC method is also called the technology cost curve. This method usually relies on the experts' experience and knowledge and prediction of technological development. It quantitatively evaluates the cost and emission reduction potential of specific emission reduction technologies or measures through expert questionnaires, technical consultations and industry data. By sorting the emission reduction costs of various technologies from low to high, the marginal carbon reduction cost curve can be constructed.

3. The method for depicting marginal carbon reduction cost curve of high energy consumption industries according to claim 1 is characterized by: The energy system fitting model based on exponential function described in step 2) is specifically as follows: In order to accurately capture the nonlinear increasing characteristics of marginal costs in different emission reduction stages, which is helpful to achieve accurate fitting of MACC, a model based on exponential function is adopted to fit the MAC of high-energy-consuming industries, so as to achieve quantitative display of MAC of high-energy-consuming industries. In the exponential function model adopted, the MAC and carbon reduction ratio of high-energy-consuming industries are characterized as follows: MAC(R)=a·e b·R (1) Where: R represents the emission reduction ratio, that is, the ratio of the industry’s emission reduction to the industry’s total CO2 emissions. Assuming that the industry’s total CO2 emissions are A Total , the industry emission reduction is C Total , the unit is 10,000 tons, then the emission reduction ratio can be expressed as C Total / A Total , the unit is %; The converted expression of carbon reduction ratio is as follows:

4. The method for depicting marginal carbon reduction cost curve of high energy consumption industries according to claim 1 is characterized by: The unit cost calculation method of each emission reduction technology in the high energy consumption industry described in step 3) is as follows: The MAC calculation formula for a single technology is as follows: Where: MAC(T i ) represents the unit emission reduction cost of technology i, that is, the marginal carbon reduction cost, in yuan / ton; INVC i represents the investment cost of technology i, in units of 10,000 yuan; AO represents the average investment period of technology, 15 years is taken in the middle; CER i It represents the carbon emission reduction of technology i, in 10,000 tons.

Images