A method for generating an emission reduction strategy based on quantitative measurement of carbon emission reduction potential of an enterprise

Abstract

The present application relates to a kind of based on quantitative estimation enterprise carbon emission reduction potential emission reduction strategy generation method, belong to enterprise carbon emission potential analysis technical field, step 1, the energy information of enterprise, economic information and the average data in the field of enterprise are carried out research collection resource;Step 2, by constructing primary energy carbon emission calculation model and the carbon emission conversion model of multiple types of energy, the carbon emission of enterprise is calculated, and the minimum carbon emission reduction potential of enterprise is estimated by indirect method;Step 3, based on the quantitative estimation model of enterprise carbon emission reduction potential constructed, the carbon emission reduction potential of enterprise is calculated;Step 4, clustering and calculating the typical scene under each dimension of enterprise and the carbon emission reduction potential of enterprise under each typical scene are obtained.Step 5, based on the carbon emission reduction potential estimation result of enterprise under each typical scene provides energy-saving and emission-reduction suggestion.

Description

Technical Field

[0001] This invention belongs to the field of enterprise carbon emission potential analysis technology, specifically involving a method for generating emission reduction strategies based on quantitative calculation of enterprise carbon emission reduction potential. Background Technology

[0002] With global warming and the introduction of "dual carbon" targets, climate and environmental governance and the control of greenhouse gas emissions are becoming increasingly important. The concept of green development is gaining widespread acceptance, and energy conservation and carbon reduction by enterprises have become an indispensable part of promoting high-quality development. Government measures such as implementing carbon quotas, promoting the development of carbon markets, and encouraging carbon trading are driving enterprises to upgrade their industries and transition their energy sources. Enterprises are increasing the proportion of clean energy in their energy consumption, saving unnecessary energy inputs, and reducing high-carbon emission energy consumption through a series of methods, including equipment upgrades, technological adjustments, flexible energy use, changes in energy structure, and standardized management. This reduces their overall carbon emissions. In this context, how enterprises calculate and reduce carbon emissions caused by their energy use has become a crucial issue.

[0003] Therefore, at this stage, it is necessary to design a method for generating emission reduction strategies based on quantitative calculation of enterprises' carbon emission reduction potential in order to solve the above problems. Summary of the Invention

[0004] The purpose of this invention is to provide a method for generating emission reduction strategies based on quantitative calculation of an enterprise's carbon emission reduction potential, in order to solve the technical problems existing in the prior art, and to calculate and reduce carbon emissions caused by an enterprise's energy use.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows:

[0006] A method for generating emission reduction strategies based on quantitative assessment of an enterprise's carbon emission reduction potential includes the following steps:

[0007] Step 1: Conduct research and data collection on the company's energy information, economic information, and average data within the company's industry;

[0008] Step 2: Calculate the company's carbon emissions using the constructed primary energy carbon emission calculation model and the carbon emission conversion model for electricity and heat, and estimate the company's minimum carbon emission reduction potential using the indirect method.

[0009] Step 3: Based on the constructed quantitative calculation model of corporate carbon emission reduction potential, combined with corporate energy utilization rate and industry average energy utilization rate, and taking into account other influencing factors, calculate the corporate carbon emission reduction potential.

[0010] Step 4: Based on the enterprise's industry scenario, cluster the enterprises from various dimensions using the K-means clustering method to obtain typical scenarios under each dimension, calculate and analyze the carbon emission reduction potential of the enterprises under each typical scenario;

[0011] Step 5: Based on the analysis of the user's carbon emission monitoring results, identify the enterprise's carbon emission problems and provide the enterprise with energy conservation and emission reduction strategies based on quantitative calculation of carbon emission reduction potential.

[0012] Furthermore, the carbon emission information of enterprises in step 1 includes multi-type energy consumption information, multi-type energy demand information, total energy consumption of enterprises, output value of enterprise users, average energy utilization efficiency of the local enterprise's industry, and energy carbon emission coefficient.

[0013] Furthermore, the primary energy carbon emission calculation model in step 2, the carbon emission conversion model for electricity and heat, the enterprise carbon emission calculation model, and the indirect method for estimating the enterprise's minimum carbon emission reduction potential are detailed below:

[0014] Carbon emission models for primary energy consumption:

[0015]

[0016] In the formula: This indicates the enterprise's standard coal consumption. This represents the consumption of the j-th type of non-standard coal; This represents the consumption of the j-th type of oil. χ represents the consumption of the j-th type of gas; j , χ′ j , χ″ j These represent the conversion coefficients for converting the carbon emissions of coal of the j-th quality to standard coal, the carbon emissions of oilseeds of the j-th quality to standard coal, and the carbon emissions of gas of the j-th quality to standard coal, respectively. These represent the carbon emissions caused by consuming a unit mass of standard coal, a unit mass of j-th type of non-standard coal, a unit mass of j-th type of oil, and a unit mass of j-th type of fuel gas, respectively. These represent the sets of non-standard coal types, oilseed types, and gaseous gas types, respectively; T else This indicates other direct carbon emission sources or emission reductions for the company. A positive value indicates that the company has additional carbon emissions, while a negative value indicates that the company has other emission reduction pathways.

[0017] Carbon emission models for electricity consumption:

[0018]

[0019] Among them, M i (t) represents the carbon emissions of enterprise i during time period t; αF,i Let P be the carbon emission intensity coefficient of enterprise i, and its value is related to the output characteristics of thermal power units and the type of fuel; k,i (t) represents the electricity purchased by company i during time period t; P f (t) represents the total output of thermal power units in the power grid during time period t; P i (t) represents the output of a non-coal-fired power unit that generates carbon emissions during time period t; P E (t) represents the total output of the generator set during time period t; Ω represents the collection of other non-coal power units.

[0020] Carbon emission models based on heat energy consumption:

[0021] The heat energy supply method is to supply hot water. Since the water supply requires the compressor in the pressurization station to work and consume electricity, it will cause carbon emissions. The carbon emissions caused by the target company's heat energy consumption include two parts: carbon emissions generated during the heating process and carbon emissions generated by the water supply.

[0022]

[0023] Q water =c water m water (T supply -T back )

[0024] In the formula: W i (t) represents the carbon emissions of enterprise i during time period t; Q water.s This represents the heat provided by the s-th type of fuel as a heat source; This represents the carbon emissions per unit quantity of the j-th quality fuel of type s; η represents the calorific value of the j-th quality fuel of type s; s P represents the efficiency of the s-th type of heating equipment; compressor (t) represents the power consumption of the compressor during time period t; Q water Indicates total heat supply; c water Indicates the specific heat capacity of water; m water Indicates the mass of hot water; T supply T back These represent the supply water temperature and the return water temperature, respectively.

[0025] The enterprise carbon emission calculation model:

[0026]

[0027] In the formula: T year N represents the total carbon emissions of the target company within one year. t This indicates the number of periods within a year during which electricity carbon emissions are measured.

[0028] Indirect methods are used to estimate a company's minimum carbon emission potential. A company's energy conservation and emission reduction potential refers to its ability to reduce carbon emissions by increasing the proportion of clean energy in its energy consumption, saving unnecessary energy input, and reducing high-carbon emission energy consumption through a series of methods, including equipment upgrades, technological adjustments, flexible energy use, changes in energy structure, and standardized management. The minimum carbon emissions for the target company are calculated, including minimum carbon emissions from primary energy consumption, minimum carbon emissions from secondary energy consumption (electricity), and minimum carbon emissions from the production process. The formula for estimating minimum carbon emissions is as follows:

[0029]

[0030] In the formula: T min Indicates minimum carbon emissions; T e.min Indicates the minimum carbon content per kilowatt-hour; ω c-e ω c-g ω o-e The proportions of coal-to-electricity conversion, coal-to-gas conversion, and oil-to-electricity conversion should be specified separately, with specific figures referring to industry averages or directly calculated based on the energy consumption of the target enterprise; Q c-e Q c-g Q o-e These represent the equivalent electricity and gas volume per unit quantity of coal replaced, and the equivalent electricity volume per unit quantity of oil replaced, respectively, after energy substitution.

[0031] Furthermore, the quantitative calculation model for enterprise carbon emission reduction potential in step 3 includes the enterprise user's energy utilization rate, energy-saving indicators, energy-saving potential, and carbon emission potential; specifically as follows:

[0032] Quantitative calculation model for corporate carbon emission reduction potential:

[0033] The energy utilization rate of enterprise users is calculated. The energy utilization rate of enterprise users is related to the technological benefits of enterprise users. The higher the technological benefits, the higher the energy utilization rate, and vice versa. In essence, it is calculated based on the output value of enterprise users and the total energy consumption of enterprise users.

[0034] ECI N =E N ÷IGDP N

[0035] Where: ECI N E represents the energy utilization rate of enterprise user N; N IGDP represents the total energy consumption of enterprise user N; N This represents the total output value of company N;

[0036] Calculate the energy-saving rate measurement index for the selected enterprise users; the reference standard for the energy-saving rate of enterprise users is the local average energy utilization rate of their industry, which is related to many factors; by comparing the energy utilization rate of enterprise users with the local average energy utilization rate of their industry, the energy-saving rate measurement index of the enterprise can be obtained.

[0037] Q N =1-(ECI) N ÷ECI AV )

[0038] In the formula: Q N Indicates the energy-saving potential of company N; ECI AV This indicates the average energy efficiency of the industry in which the company operates in the local area;

[0039] Calculate the energy-saving potential of an enterprise; estimate the energy-saving potential of enterprise users based on the enterprise's energy-saving rate measurement indicators; known energy-saving rate measurement indicators of an enterprise can be converted into energy-saving potential of enterprise users through coupled calculation relationships.

[0040] E N,save =Q N ×E N

[0041] In the formula: E N,save This represents the energy savings of company N;

[0042] Calculate a company's carbon emission reduction potential; the carbon emission reduction potential of a company's energy-saving space can be calculated based on the energy carbon emission coefficient; through the company's energy-saving space, the amount of energy consumption reduction of the company can be known, and then the carbon emission reduction generated by the company's energy users can be known, that is, the company's carbon emission reduction potential.

[0043] A = E N,save ×δ

[0044] In the formula: A represents the carbon emissions reduced by the enterprise user through energy conservation; δ represents the carbon emission coefficient of energy consumption.

[0045] Furthermore, in step 4, enterprise scenario clustering and enterprise multi-dimensional clustering are used to obtain typical scenarios under each dimension of the enterprise and the carbon emission reduction potential of the enterprise under each typical scenario, and to analyze the carbon emission monitoring results of enterprise users.

[0046] Enterprise scenario clustering: Identify typical scenarios for enterprise users, and cluster them using the K-means clustering method based on the massive number of enterprise user scenarios; assuming each enterprise has N operational characteristics, then an N-dimensional vector can be used to represent the user's operational status; that is, a multi-dimensional vector can be used to describe any enterprise; assuming there are M scenarios in total, then M N-dimensional vectors can be obtained to represent enterprise characteristics; subsequently, K-Means clustering is performed on the M N-dimensional vectors, and the final clustering results are obtained through iterative solutions.

[0047] The execution flow of the K-Means clustering algorithm is as follows:

[0048] 1) Specify the number of clusters K;

[0049] 2) Initialize cluster centers by randomly selecting K points as initial cluster centers;

[0050] 3) Calculate the membership matrix Z;

[0051] 4) Calculate the value function from the membership matrix Z. If it is less than the set threshold or the difference between two consecutive values ​​is less than the set threshold, the algorithm stops.

[0052] 5) Correct the cluster centers based on the previous cluster division, and then return to step 3) to iterate;

[0053] Enterprise multi-dimensional clustering yields typical scenarios under various dimensions of the enterprise; massive amounts of data from various dimensions of the enterprise are collected, and the K-Means mean clustering algorithm is used to divide and cluster the scenario data under various dimensions of the enterprise into different production requirements, different management dimensions, and different time scales, thus obtaining typical scenarios of enterprise users under different situations.

[0054] Calculate the carbon reduction potential of enterprise users in different scenarios; use quantitative calculation methods to calculate the carbon reduction potential of enterprise users in different scenarios.

[0055] This study analyzes the carbon emission monitoring results of enterprise users; combines the calculated carbon reduction potential of enterprise users with the analysis of the carbon emission monitoring results to measure the carbon reduction potential of enterprise users under different production requirements, management dimensions, and time scales; organizes the typical scenarios obtained from clustering, classifies and organizes the electricity consumption, heat consumption, fossil fuel consumption, and enterprise output data of target enterprises under each scenario, quantitatively calculates the carbon reduction potential of enterprises under each scenario, and obtains the carbon reduction potential of enterprises under different typical scenarios, thereby analyzing the carbon emission monitoring results under different scenarios.

[0056] Furthermore, step 5 provides enterprises with energy conservation and emission reduction strategies; specifically as follows:

[0057] Based on the analysis of user carbon emission monitoring results, we will consider providing relevant users with energy conservation and emission reduction strategies based on quantitative calculations of carbon emission reduction potential by optimizing power supply structure, energy storage, and improving integrated energy service methods.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0059] One of the beneficial effects of this solution is that it provides carbon emission monitoring reports: The reports will compile carbon emission monitoring results under different scenarios, serving as a reference for enterprises' energy conservation and emission reduction efforts. The reports will include: the enterprise's consumption and proportion of various energy sources, the carbon emissions generated by each energy consumption, the enterprise's carbon emission potential, a comparison of the enterprise's energy utilization rate with the industry, and will identify areas where the enterprise has potential for energy conservation and emission reduction.

[0060] 2) Analyze the energy consumption of enterprises: Analyze the power supply situation of enterprises under different scenarios. For enterprises with flexible electricity consumption, reduce their electricity consumption during periods of high carbon content per kilowatt-hour and increase their electricity consumption during periods with a higher proportion of clean energy, thus achieving energy shifting. For enterprises that cannot shift electricity but have large-scale energy storage facilities nearby, they can coordinate with external energy storage facilities to purchase electricity from the storage facilities during periods of high carbon content per kilowatt-hour, which can also achieve emission reduction targets.

[0061] 3) Assess the enterprise's production processes: By calculating the carbon reduction potential of enterprises under various scenarios, the production processes of enterprises in each scenario are examined and evaluated to identify equipment or production links with low efficiency, crude energy utilization, or room for optimization, and to carry out targeted upgrades and transformations. Enterprises with heat energy needs, such as thermal power companies, will install steam boilers. Existing heating boilers include coal-fired boilers, gas-fired boilers, and electric boilers. In this case, we should promote the elimination of coal-fired boilers because they not only have high carbon emissions, but also low heating efficiency, inflexible control, large footprint, and the need for coal storage space. Eliminating coal-fired boilers and upgrading to gas-fired or electric boilers can greatly reduce carbon emissions and improve operational flexibility and control effectiveness.

[0062] 4) Improve the energy structure of enterprises: Analyze the actual resource endowment of enterprises, and promote the installation of photovoltaics in industrial parks with large space resources, such as large areas of vacant rooftops and large, open areas, to increase energy self-sufficiency and reduce grid-side electricity consumption, which can effectively reduce the carbon emissions of enterprises. Meanwhile, corresponding agricultural technology parks can rely on their abundant biomass resources, such as manure-to-biogas conversion, and install biomass power generation equipment to achieve the goals of energy self-sufficiency and green, low-carbon development.

[0063] 5) Providing integrated energy services to enterprises: By analyzing enterprises' electricity consumption periods, available space, and financial and technological resources, and targeting enterprises with significant peak-valley differences in electricity consumption, concentrated electricity usage, ample available space, and sufficient financial and technological support, we can promote the construction of user-side energy storage equipment. This allows for the storage of clean electricity such as hydropower and wind power during off-peak hours, replacing thermal power supply during peak hours, thus reducing the carbon emissions of related enterprises' electricity consumption. For industrial parks, power and heat companies, and urban functional areas, we can also promote the construction of gas storage facilities, installing electrolyzers, hydrogen-oxygen fuel cells, and gas turbines. This achieves long-term energy storage and long-distance transportation, and can also replace coal power, realizing the decarbonization of electricity. Simultaneously, these facilities can also participate in the electricity market as flexible resources to obtain additional revenue subsidies. Attached Figure Description

[0064] Figure 1 This is a schematic diagram of the method of the present invention.

[0065] Figure 2 This is a schematic diagram of the carbon emission reduction potential quantitative calculation method of the present invention.

[0066] Figure 3 This is a schematic diagram of the clustering process of the present invention. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention; that is, the described embodiments are merely some embodiments of the invention, and not all embodiments. The components of the embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0068] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0069] A method for generating emission reduction strategies based on quantitative assessment of an enterprise's carbon emission reduction potential includes the following steps:

[0070] Step 1: Conduct research and data collection, focusing on enterprise information such as primary and secondary energy consumption data, enterprise energy utilization rate, etc., and understand the enterprise's production process and industry average energy indicators.

[0071] Step 2: Construct enterprise carbon emission calculation models, including primary energy carbon emission calculation models, multi-type energy carbon emission conversion models, and enterprise carbon emission calculation models, and estimate the minimum carbon emission reduction potential of enterprises through indirect methods;

[0072] Step 3: Construct a quantitative calculation model for the enterprise's carbon emission potential and calculate the enterprise's carbon emission potential;

[0073] Step 4: Multi-dimensional typical scenario clustering analysis. Cluster the enterprise's energy use scenarios from different dimensions, calculate and analyze the carbon emission reduction potential of enterprises in each scenario.

[0074] Step 5: Propose energy conservation and emission reduction strategies. Based on the calculation of the enterprise's carbon emission potential and the analysis of relevant enterprise information, propose targeted strategies.

[0075] refer to Figure 2 , Figure 2 The flowchart of the carbon emission reduction potential quantitative calculation method of the present invention is as follows: 1) Obtain the daily electricity consumption, monthly heat consumption and monthly consumption of other fuels of the enterprise user in the past year, and the total output value of the enterprise; 2) Process the data and calculate the energy utilization rate of the enterprise; 3) Compare with the average energy utilization rate of the industry and region in which the enterprise is located to obtain the enterprise energy saving rate measurement index; 4) Estimate the energy saving space of the enterprise based on the enterprise energy saving rate measurement index; 5) Further calculate the carbon emission reduction potential of the enterprise's energy saving space.

[0076] refer to Figure 3 , Figure 3 This is a schematic diagram of the clustering process of the present invention. Assuming each enterprise has N operational characteristics, its operational status can be represented by an N-dimensional vector. For example, "total output value, electricity consumption, water consumption, net profit, and operation and maintenance costs," meaning any enterprise can be described by a multi-dimensional vector. Assuming there are M scenarios, M N-dimensional vectors can be obtained to represent the enterprise characteristics. Subsequently, K-Means clustering is performed on these M N-dimensional vectors, and the final clustering results are obtained through iterative processing. The specific operation process is as follows: Figure 3 .

[0077] Preferably, the operational method for quantitatively measuring the carbon emission potential of an enterprise and providing emission reduction suggestions in step 1 includes the enterprise's carbon emission information, including the enterprise's multi-type energy consumption information, multi-type energy demand information, the enterprise's total energy consumption, the enterprise's user output value, the average energy utilization efficiency of the local industry in which the enterprise is located, and the energy carbon emission coefficient, etc.

[0078] Preferably, the carbon emission calculation model for primary energy in step 2 includes the carbon emission conversion model for electrical and thermal energy, the model for calculating corporate carbon emissions, and the indirect method for estimating the minimum carbon emission reduction potential of enterprises.

[0079] The carbon emission model for consuming primary energy sources:

[0080]

[0081] In the formula: This indicates the enterprise's standard coal consumption. This represents the consumption of the j-th type of non-standard coal; This represents the consumption of the j-th type of oil. χ represents the consumption of the j-th type of gas; j , χ′ j , χ″ j These represent the conversion coefficients for converting the carbon emissions of coal of the j-th quality to standard coal, the carbon emissions of oilseeds of the j-th quality to standard coal, and the carbon emissions of gas of the j-th quality to standard coal, respectively. These represent the carbon emissions caused by consuming a unit mass of standard coal, a unit mass of j-th type of non-standard coal, a unit mass of j-th type of oil, and a unit mass of j-th type of fuel gas, respectively. These represent the sets of non-standard coal types, oilseed types, and gas types, respectively. T else This indicates other direct carbon emission sources or emission reductions for the company. A positive value indicates that the company has additional carbon emissions, while a negative value indicates that the company has other emission reduction pathways.

[0082] The carbon emission model for the consumption of electrical energy:

[0083]

[0084] Among them, M i (t) represents the carbon emissions of enterprise i during time period t; α F,i Let P be the carbon emission intensity coefficient of enterprise i, and its value is related to the output characteristics of thermal power units and the type of fuel; k,i (t) represents the amount of electricity purchased by company i during time period t. f (t) represents the total output of thermal power units in the power grid during time period t; P i (t) represents the output of a non-coal-fired power unit that generates carbon emissions during time period t; P E (t) represents the total output of the generator set during time period t; Ω represents the collection of other non-coal power units.

[0085] The carbon emission model that consumes thermal energy:

[0086] The heat supply method is hot water supply. Since water supply requires compressors in a booster station to operate, consuming electricity, this results in carbon emissions. The carbon emissions from the target company's heat consumption include both carbon emissions from the heating process and carbon emissions from the water supply.

[0087]

[0088] Q water =c water m water (T supply -T back )

[0089] In the formula: W i (t) represents the carbon emissions of enterprise i during time period t; Q water.s T represents the heat provided by the s-th type of fuel as a heat source; s j This represents the carbon emissions per unit quantity of the j-th quality fuel of type s; η represents the calorific value of the j-th quality fuel of type s; s P represents the efficiency of the s-th type of heating equipment; compressor (t) represents the power consumption of the compressor during time period t; Q water Indicates total heat supply; c water Indicates the specific heat capacity of water; m water Indicates the mass of hot water; T supply T back These represent the supply water temperature and the return water temperature, respectively.

[0090] The enterprise carbon emission calculation model:

[0091]

[0092] In the formula: T year N represents the total carbon emissions of the target company within one year. t This indicates the number of periods within a year during which electricity carbon emissions are measured.

[0093] The indirect method described above estimates a company's minimum carbon emission potential. A company's energy conservation and emission reduction potential refers to its ability to reduce its carbon emissions by increasing the proportion of clean energy in its energy consumption, saving unnecessary energy input, and reducing high-carbon emission energy consumption through a series of methods such as equipment modification, technological adjustment, flexible energy use, changing energy structure, and standardized management. The minimum carbon emissions for the target company are calculated, including the minimum carbon emissions from primary energy consumption, the minimum carbon emissions from secondary energy consumption such as electricity, and the minimum carbon emissions from the production process. The formula for estimating the minimum carbon emissions is as follows:

[0094]

[0095] In the formula: T min Indicates minimum carbon emissions; T e.min Indicates the minimum carbon content per kilowatt-hour; ω c-e ωc-g ω o-e The proportions of coal-to-electricity conversion, coal-to-gas conversion, and oil-to-electricity conversion should be specified separately, with specific figures referring to industry averages or directly calculated based on the energy consumption of the target enterprise; Q c-e Q c-g Q o-e These represent the equivalent electricity and gas volume per unit quantity of coal replaced, and the equivalent electricity volume per unit quantity of oil replaced, respectively, after energy substitution.

[0096] Preferably, the quantitative calculation model for corporate carbon emission reduction potential in step 3 includes the energy utilization rate of corporate users, the energy-saving indicators of corporate users, the energy-saving space of corporate users, and the carbon emission potential of enterprises.

[0097] The quantitative calculation model for the enterprise's carbon emission reduction potential:

[0098] The energy utilization rate of enterprise users is calculated. This rate is related to the enterprise user's technological efficiency; higher technological efficiency results in higher energy utilization, and vice versa. Essentially, it is calculated based on the enterprise user's output value and total energy consumption.

[0099] ECI N =E N ÷IGDP N

[0100] Where: ECI N E represents the energy utilization rate of enterprise user N; N IGDP represents the total energy consumption of enterprise user N; N This represents the total output value of company N.

[0101] The calculation uses energy-saving rate metrics selected from enterprise users. The benchmark for enterprise users' energy-saving rate is the local average energy utilization rate of their industry, which is related to many factors, such as the enterprise's technological level and energy structure. The enterprise's energy-saving rate metric is obtained by comparing the enterprise user's energy utilization rate with the local average energy utilization rate of its industry.

[0102] Q N =1-(ECI) N ÷ECI AV )

[0103] In the formula: Q N Indicates the energy-saving potential of company N; ECI AV This indicates the average energy efficiency of the industry in which the company operates in the local area;

[0104] The calculation involves determining the energy-saving potential of the enterprise. This is done by estimating the energy-saving potential of the enterprise's users based on the enterprise's energy-saving rate metrics. Known energy-saving rate metrics of the enterprise can be converted into energy-saving potential for enterprise users through coupled calculation relationships.

[0105] E N,save =Q N ×E N

[0106] In the formula: E N,save This represents the energy savings potential of company N.

[0107] The calculation of a company's carbon emission reduction potential can be based on the energy carbon emission coefficient. The company's energy-saving potential can be calculated using the energy-saving space obtained above. From the company's energy-saving space, the amount of energy consumption reduction can be determined, and thus the carbon emission reduction resulting from the reduction in energy consumption by the company's users can be determined, i.e., the company's carbon emission reduction potential.

[0108] A = E N,save ×δ

[0109] In the formula: A represents the carbon emissions reduced by the enterprise user through energy conservation; δ represents the carbon emission coefficient of energy consumption.

[0110] Preferably, in step 4, enterprise scenario clustering and enterprise multi-dimensional clustering are used to obtain typical scenarios under each dimension of the enterprise and the carbon emission reduction potential of the enterprise under each typical scenario, and to analyze the carbon emission monitoring results of enterprise users.

[0111] The enterprise scenario clustering described above involves identifying typical scenarios for enterprise users and then using the K-means clustering method to cluster these scenarios based on the massive number of user scenarios. Assuming each enterprise has N operational characteristics, its operational status can be represented by an N-dimensional vector. Examples include "total output value, electricity consumption, water consumption, net profit, and maintenance costs," meaning any enterprise can be described by a multi-dimensional vector. Assuming there are M scenarios, M N-dimensional vectors can be obtained to represent the enterprise characteristics. Subsequently, K-Means clustering is performed on these M N-dimensional vectors, and the final clustering results are obtained through iterative processing.

[0112] The execution flow of the K-Means clustering algorithm is as follows:

[0113] 1) Specify the number of clusters K;

[0114] 2) Initialize cluster centers by randomly selecting K points as initial cluster centers;

[0115] 3) Calculate the membership matrix Z;

[0116] 4) Calculate the value function from the membership matrix Z. If it is less than the set threshold or the difference between two consecutive values ​​is less than the set threshold, the algorithm stops.

[0117] 5) Correct the cluster centers based on the clusters after the previous division, and then return to step 3) to iterate.

[0118] The aforementioned multi-dimensional clustering of enterprises yields typical scenarios under various dimensions. Massive amounts of data from various dimensions of enterprises are collected, and the K-Means clustering algorithm is used to divide and cluster the scenario data under various dimensions, categorizing them into different production requirements (off-season, peak season), different management dimensions (contract energy management, full-service, semi-service, etc.), and different time scales (daily, weekly, monthly, yearly), thus obtaining typical scenarios for enterprise users under different situations.

[0119] The aforementioned method for calculating the carbon reduction potential of enterprise users under different scenarios is used to calculate the carbon reduction potential of enterprise users under different scenarios.

[0120] The analysis focuses on the carbon emission monitoring results of enterprise users. Combining the calculated carbon reduction potential of these users, the analysis measures their carbon reduction potential under different production requirements, management dimensions, and time scales. The analysis also organizes the typical scenarios obtained from the aforementioned clustering, categorizing and organizing data such as electricity consumption, heat consumption, fossil fuel consumption, and enterprise output value for each scenario. Quantitative calculations of the enterprise carbon reduction potential under each scenario are then performed, yielding the carbon reduction potential for different typical scenarios, thus enabling the analysis of carbon emission monitoring results under different scenarios.

[0121] Preferably, step 5 involves providing energy conservation and emission reduction recommendations to enterprises.

[0122] The aforementioned energy conservation and emission reduction recommendations for enterprises, based on the analysis of users' carbon emission monitoring results and the identification of enterprise carbon emission problems, consider optimizing power supply structure, energy storage, and improving integrated energy services, and provide relevant users with energy conservation and emission reduction strategies based on quantitative calculations of carbon emission reduction potential as follows:

[0123] 1) Provide carbon emission monitoring reports: Compile carbon emission monitoring results under different scenarios into reports to serve as a reference for enterprises' energy conservation and emission reduction. The report content includes: the enterprise's consumption and proportion of various energy sources, the carbon emissions generated by various energy consumption, the enterprise's carbon emission potential, a comparison of the enterprise's energy utilization rate with the industry, and points out the areas where the enterprise has potential for energy conservation and emission reduction.

[0124] 2) Analyze the energy consumption of enterprises: Analyze the power supply situation of enterprises under different scenarios. For enterprises with flexible electricity consumption, reduce their electricity consumption during periods of high carbon content per kilowatt-hour and increase their electricity consumption during periods with a higher proportion of clean energy, thus achieving energy shifting. For enterprises that cannot shift electricity but have large-scale energy storage facilities nearby, they can coordinate with external energy storage facilities to purchase electricity from the storage facilities during periods of high carbon content per kilowatt-hour, which can also achieve emission reduction targets.

[0125] 3) Assess the enterprise's production processes: By calculating the carbon reduction potential of enterprises under various scenarios, the production processes of enterprises in each scenario are examined and evaluated to identify equipment or production links with low efficiency, crude energy utilization, or room for optimization, and to carry out targeted upgrades and transformations. Enterprises with heat energy needs, such as thermal power companies, will install steam boilers. Existing heating boilers include coal-fired boilers, gas-fired boilers, and electric boilers. In this case, we should promote the elimination of coal-fired boilers because they not only have high carbon emissions, but also low heating efficiency, inflexible control, large footprint, and the need for coal storage space. Eliminating coal-fired boilers and upgrading to gas-fired or electric boilers can greatly reduce carbon emissions and improve operational flexibility and control effectiveness.

[0126] 4) Improve the energy structure of enterprises: Analyze the actual resource endowment of enterprises, and promote the installation of photovoltaics in industrial parks with large space resources, such as large areas of vacant rooftops and large, open areas, to increase energy self-sufficiency and reduce grid-side electricity consumption, which can effectively reduce the carbon emissions of enterprises. Meanwhile, corresponding agricultural technology parks can rely on their abundant biomass resources, such as manure-to-biogas conversion, and install biomass power generation equipment to achieve the goals of energy self-sufficiency and green, low-carbon development.

[0127] 5) Providing integrated energy services to enterprises: By analyzing enterprises' electricity consumption periods, available space, and financial and technological resources, and targeting enterprises with significant peak-valley differences in electricity consumption, concentrated electricity usage, ample available space, and sufficient financial and technological support, we can promote the construction of user-side energy storage equipment. This allows for the storage of clean electricity such as hydropower and wind power during off-peak hours, replacing thermal power supply during peak hours, thus reducing the carbon emissions of related enterprises' electricity consumption. For industrial parks, power and heat companies, and urban functional areas, we can also promote the construction of gas storage facilities, installing electrolyzers, hydrogen-oxygen fuel cells, and gas turbines. This achieves long-term energy storage and long-distance transportation, and can also replace coal power, realizing the decarbonization of electricity. Simultaneously, these facilities can also participate in the electricity market as flexible resources to obtain additional revenue subsidies.

[0128] The above are preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for generating emission reduction strategies based on quantitatively assessing an enterprise's carbon emission reduction potential, characterized in that, Includes the following steps: Step 1: Conduct research and data collection on the company's energy information, economic information, and average data within the company's industry; Step 2: Calculate the company's carbon emissions using the constructed primary energy carbon emission calculation model and the carbon emission conversion model for electricity and heat, and estimate the company's minimum carbon emission reduction potential using the indirect method. Step 3: Based on the constructed quantitative calculation model of corporate carbon emission reduction potential, combined with corporate energy utilization rate and industry average energy utilization rate, and taking into account other influencing factors, calculate the corporate carbon emission reduction potential. Step 4: Based on the enterprise's industry scenario, cluster the enterprises from various dimensions using the K-means clustering method to obtain typical scenarios under each dimension, calculate and analyze the carbon emission reduction potential of the enterprises under each typical scenario; Step 5: Based on the analysis of the carbon emission monitoring results of users, identify the carbon emission problems of enterprises, and consider providing relevant users with energy-saving and emission-reduction strategies based on quantitative calculation of carbon emission reduction potential by optimizing energy structure, energy storage, and improving integrated energy service methods. The minimum carbon reduction potential of a company, including the estimation of the minimum carbon emissions, is estimated using an indirect method, as shown in the following formula: In the formula: Indicates the minimum carbon emissions; This indicates the minimum carbon content per kilowatt-hour; , , The proportions of coal-to-electricity conversion, coal-to-gas conversion, and oil-to-electricity conversion are calculated separately, with specific figures referring to the industry average or directly calculated based on the energy consumption of the target enterprise. , , These represent the equivalent electricity and gas volume per unit quantity of coal replaced, and the equivalent electricity volume per unit quantity of oil replaced, respectively, after energy substitution. , , These represent the consumption of standard coal per unit mass and the consumption of the first unit mass of coal, respectively. j Oilseeds, unit mass j Carbon emissions from various types of fuels; For enterprises i exist t Carbon emissions from electricity consumption during specific time periods; Step 3, the quantitative calculation model for enterprise carbon emission reduction potential, includes the enterprise user's energy utilization rate, energy-saving indicators, energy-saving potential, and carbon emission potential; specifically as follows: Quantitative calculation model for corporate carbon emission reduction potential: The energy utilization rate of enterprise users is calculated. The energy utilization rate of enterprise users is related to the technological benefits of enterprise users. The higher the technological benefits, the higher the energy utilization rate, and vice versa. Its essence is to calculate based on the enterprise user's output value and the enterprise user's total energy consumption; In the formula: ECI N Enterprise users N Energy utilization rate; E N Enterprise users N Total energy consumption; IGDP N Indicates enterprise N Total output value; Calculate the energy-saving rate measurement index for the selected enterprise users; the reference standard for the energy-saving rate of enterprise users is the local average energy utilization rate of their industry, which is related to many factors; by comparing the energy utilization rate of enterprise users with the local average energy utilization rate of their industry, the energy-saving rate measurement index of the enterprise can be obtained. In the formula: Q N Indicates enterprise N Its energy-saving potential; ECI AV This indicates the average energy efficiency of the industry in which the company operates in the local area; Calculate the energy-saving potential of an enterprise; estimate the energy-saving potential of enterprise users based on the enterprise's energy efficiency measurement indicators; Known energy efficiency metrics for enterprises can be converted into energy-saving potential for enterprise users through coupled calculation relationships; In the formula: represents the enterprise N Energy-saving space; Calculate a company's carbon emission reduction potential; the carbon emission reduction potential of a company's energy-saving space can be calculated based on the energy carbon emission coefficient; through the company's energy-saving space, the amount of energy consumption reduction of the company can be known, and then the carbon emission reduction generated by the company's energy users can be known, that is, the company's carbon emission reduction potential. In the formula: A The amount of carbon emissions reduced by saving energy for enterprise users; This represents the carbon emission coefficient for energy consumption.

2. The method for generating emission reduction strategies based on quantitative calculation of an enterprise's carbon emission reduction potential, as described in claim 1, is characterized in that... The carbon emission information of enterprises in step 1 includes multi-type energy consumption information, multi-type energy demand information, total energy consumption of enterprises, output value of enterprise users, average energy utilization efficiency of the local industry, and energy carbon emission coefficient.

3. The method for generating emission reduction strategies based on quantitative calculation of an enterprise's carbon emission reduction potential, as described in claim 1, is characterized in that... The carbon emission calculation models for primary energy sources in Step 2, including the carbon emission conversion models for electricity and heat, and the enterprise carbon emission calculation models, are as follows: Carbon emission models for primary energy consumption: In the formula: This indicates the enterprise's standard coal consumption. Indicates the first j Consumption of non-standard coal; Indicates the first j Consumption of oilseeds; Indicates the first j Consumption of this type of gas; , , , These represent the consumption of standard coal per unit mass and the consumption of the first unit mass of coal, respectively. j Non-standard coal, unit mass j Oilseeds, unit mass j Carbon emissions from various types of fuels; , , These represent the sets of non-standard coal types, oilseed types, and gas types, respectively. This indicates other direct carbon emission sources or emission reductions for the company. A positive value indicates that the company has additional carbon emissions, while a negative value indicates that the company has other emission reduction pathways. Carbon emission models for electricity consumption: in, For enterprises i exist t Carbon emissions from electricity consumption during specific time periods; For enterprises i The carbon emission intensity coefficient is related to the output characteristics of thermal power units and the type of fuel. For enterprises i exist t Electricity purchased during the specified time period; Indicates in t Total output of thermal power units in the power grid during the specified time period; This refers to a type of non-coal-fired power generation unit that produces carbon emissions. t Efforts during a specific time period; Indicates that the generator set is t Total output over the period; Carbon emission models based on heat energy consumption: The heat energy supply method is to supply hot water. Since the water supply requires the compressor in the pressurization station to work and consume electricity, it will cause carbon emissions. The carbon emissions caused by the target company's heat energy consumption include two parts: carbon emissions generated during the heating process and carbon emissions generated by the water supply. In the formula: Indicates enterprise i exist t Carbon emissions from heat consumption during a given period; Indicates the first s Heat provided by a type of fuel as a heat source; The first unit represents the quantity of the unit. s Class 1 j Carbon emissions of different types of fuel; Indicates the first s Class 1 j The calorific value of a certain quality fuel; Indicates the first s The efficiency of similar heating equipment; Indicates that the compressor is in t Power consumption during a given time period; Indicates the total heat supply; This indicates the specific heat capacity of water; Indicates the quality of hot water; , These represent the supply water temperature and the return water temperature, respectively. The enterprise carbon emission calculation model: In the formula: This represents the target company's total carbon emissions over one year; This indicates the number of periods within a year during which electricity carbon emissions are measured.

4. The method for generating emission reduction strategies based on quantitative calculation of an enterprise's carbon emission reduction potential, as described in claim 1, is characterized in that... In step 4, enterprise scenario clustering and enterprise multi-dimensional clustering are used to obtain typical scenarios under each dimension of the enterprise and the carbon emission reduction potential of the enterprise under each typical scenario, and to analyze the carbon emission monitoring results of enterprise users. Enterprise scenario clustering; Identify typical scenarios for enterprise users, and cluster them using the K-means clustering method based on the massive number of enterprise user scenarios; Assuming each enterprise has N operational characteristics, a user's operational status can be represented by an N-dimensional vector; that is, any enterprise can be described by a multi-dimensional vector; assuming there are M scenarios, M N-dimensional vectors can be obtained to represent enterprise characteristics; subsequently, K-Means clustering is performed on the M N-dimensional vectors, and the final clustering results are obtained through iterative methods. The execution flow of the K-Means clustering algorithm is as follows: 1) Specify the number of clusters K; 2) Initialize cluster centers by randomly selecting K points as initial cluster centers; 3) Calculate the membership matrix Z; 4) Calculate the value function from the membership matrix Z. If it is less than the set threshold or the difference between two consecutive values ​​is less than the set threshold, the algorithm stops. 5) Correct the cluster centers based on the previous cluster division, and then return to step 3) to iterate; Enterprise multi-dimensional clustering yields typical scenarios under various dimensions of the enterprise; massive amounts of data from various dimensions of the enterprise are collected, and the K-Means mean clustering algorithm is used to divide and cluster the scenario data under various dimensions of the enterprise into different production requirements, different management dimensions, and different time scales, thus obtaining typical scenarios of enterprise users under different situations. Calculate the carbon reduction potential of enterprise users in different scenarios; use quantitative calculation methods to calculate the carbon reduction potential of enterprise users in different scenarios. This study analyzes the carbon emission monitoring results of enterprise users; combines the calculated carbon reduction potential of enterprise users with the analysis of the carbon emission monitoring results to measure the carbon reduction potential of enterprise users under different production requirements, management dimensions, and time scales; organizes the typical scenarios obtained from clustering, classifies and organizes the electricity consumption, heat consumption, fossil fuel consumption, and enterprise output data of target enterprises under each scenario, quantitatively calculates the carbon reduction potential of enterprises under each scenario, and obtains the carbon reduction potential of enterprises under different typical scenarios, thereby analyzing the carbon emission monitoring results under different scenarios.

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