Enterprise low-carbon development trend assessment, optimization method and system based on power data

Abstract

An enterprise low-carbon development trend assessment, optimization method and system based on power data, the assessment method first constructs an enterprise electricity and carbon emissions coupling model based on the enterprise's historical energy data, then calculates the enterprise's carbon emissions and low-carbon development factor in real time based on the enterprise electricity and carbon emissions coupling model, and obtains the enterprise's benchmark development trend curve, and then evaluates the enterprise's low-carbon development trend based on the enterprise's carbon emissions, the enterprise's low-carbon development factor and the enterprise's benchmark development trend curve. The optimization method determines the enterprise's low-carbon development optimization strategy based on the enterprise's low-carbon development trend assessment results. The present invention utilizes the characteristics of strong real-time and high accuracy of power data, not only realizing real-time and accurate evaluation of the enterprise's own low-carbon development trend during its development process, but also providing an enterprise low-carbon development optimization strategy.

Description

Technical Field

[0001] The present invention belongs to the field of electric power technology, and specifically relates to a method and system for evaluating and optimizing the low-carbon development situation of an enterprise based on electric power data. Background Art

[0002] Currently, developing a low-carbon economy has become the trend and direction of global economic development, and clean, low-carbon transformation has become the key to sustainable and high-quality development for enterprises. Assessing the low-carbon development status of enterprises and enhancing their ability to adapt to green, low-carbon transformation and upgrading will not only help enterprises find their proper position in low-carbon development, adjust their low-carbon development paths in a timely manner, and enhance their market competitiveness, but will also help promote the comprehensive green transformation of economic and social development.

[0003] The existing enterprise low-carbon level evaluation index system is lagging and relatively general. It is not only unable to achieve real-time assessment of its own low-carbon development trends, but also unable to reflect the green and low-carbon development level of the enterprise in its industry. It affects the practicality and reliability of the enterprise low-carbon level assessment in transformation decision-making, and is not conducive to enterprises to timely adjust and optimize the low-carbon transformation technology route according to development conditions. Summary of the Invention

[0004] The purpose of the present invention is to address the above-mentioned problems existing in the prior art and to provide a method and system for evaluating and optimizing the low-carbon development trend of an enterprise based on power data.

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

[0006] In a first aspect, the present invention proposes a method for evaluating the low-carbon development status of an enterprise based on power data, comprising:

[0007] S1. Build a coupling model of enterprise electricity consumption and carbon emissions based on the enterprise's historical energy data;

[0008] S2. Calculate the company's carbon emissions and low-carbon development factor in real time based on the coupling model of the company's electricity consumption and carbon emissions, and obtain the company's baseline development trend curve;

[0009] S3. Evaluate the low-carbon development trend of the enterprise based on its carbon emissions, low-carbon development factor and its benchmark development trend curve.

[0010] In S2, the low-carbon development factor of the enterprise is calculated based on the following formula:

[0011]

[0012] In the above formula, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, Q n,j 、P n,jare the output and unit price of the enterprise on the jth day of the nth year, and CEF n,j is the carbon emissions of the enterprise on the jth day of year n;

[0013] The company's baseline development trend curve is:

[0014] f(Q n,j P n,j )=IAC n-1 Q n,j P n,j

[0015] In the above formula, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, IAC n-1 It is the carbon emission intensity of the industry in which the enterprise is located in the n-1th year.

[0016] The S3 includes:

[0017] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are higher than the industry level;

[0018] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are lower than the industry level;

[0019] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emissions are higher than the industry level;

[0020] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emission level is lower than the industry level;

[0021] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emission level is higher than the industry level;

[0022] like And CEF n,j <f(Q n,j P n,j), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emissions are lower than the industry level;

[0023] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emission level is higher than the industry level;

[0024] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emissions are lower than the industry level;

[0025] in, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, Q n,j 、P n,j are the output and unit price of the company's products on the jth day of the nth year respectively.

[0026] Said S1 comprises:

[0027] S11. Calculate the company's historical carbon emissions based on its historical energy data:

[0028]

[0029] In the above formula, CEF n is the carbon emissions of the enterprise in the nth year, CF n,m 、CC n,m , OC n,m are the consumption, carbon content, and carbon oxidation rate of the mth fossil fuel of the enterprise in year n, respectively. n EF n are the net purchased electricity and net purchased heat of the enterprise in year n, EI n 、EH n are the average electricity carbon emission factor and heat emission factor of the grid node where the enterprise is located in the nth year, CEP n is the carbon emissions from the industrial production process of the enterprise in year n, and M is the number of types of fossil fuels;

[0030] S12. Based on the historical carbon emissions of enterprises, the following coupling model of enterprise electricity consumption and carbon emissions is constructed using the autoregressive distributed lag model:

[0031]

[0032] In the above formula, c0 is the basic influence constant, α i , β i , γ i is the influence coefficient, r, s, q are the lag orders, EE n-i is the net purchased electricity of the enterprise in year ni, Q n-i The output of the industry in the nith year.

[0033] In a second aspect, the present invention proposes a method for optimizing enterprise low-carbon development based on power data, comprising:

[0034] A. Use the aforementioned assessment method to assess the company's low-carbon development trends;

[0035] B. Determine the company's low-carbon development optimization strategy based on the company's low-carbon development situation assessment results, including:

[0036] If the company is in a trend of increasing carbon emissions, it should adopt an optimization strategy of building new energy to reduce carbon emissions during the production process of its products.

[0037] In the optimization strategy of building new energy to reduce carbon emissions in the production process, the minimum capacity of building new energy is G min Calculated based on the following conditions:

[0038]

[0039] In the above formula, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, G is the capacity of the enterprise to build new energy, h n,j is the number of hours of utilization of new energy power generation equipment on the jth day of the nth year, EI n,j is the average electricity carbon emission factor of the grid node where the enterprise is located on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, U n,j is the cost of renewable energy electricity for the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise.

[0040] In a third aspect, the present invention proposes an enterprise low-carbon development trend assessment system based on power data, comprising a coupling model construction module, a low-carbon development factor calculation module, a benchmark development trend curve acquisition module, and an assessment module;

[0041] The coupling model building module is used to build a coupling model of enterprise electricity and carbon emissions based on the enterprise's historical energy data;

[0042] The low-carbon development factor calculation module is used to calculate the carbon emissions and low-carbon development factors of the enterprise in real time based on the enterprise electricity and carbon emissions coupling model;

[0043] The benchmark development trend curve acquisition module is used to obtain the benchmark development trend curve of the enterprise;

[0044] The evaluation module is used to evaluate the low-carbon development trend of an enterprise based on the enterprise's carbon emissions, the enterprise's low-carbon development factor, and the enterprise's benchmark development trend curve.

[0045] The low-carbon development factor calculation module calculates the low-carbon development factor of an enterprise based on the following formula:

[0046]

[0047] In the above formula, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, and CEF n,j is the carbon emissions of the enterprise on the jth day of year n;

[0048] The baseline development trend curve of the enterprise is:

[0049] f(Q n,j P n,j )=IAC n-1 Q n,j P n,j

[0050] In the above formula, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, IAC n-1 The carbon emission intensity of the enterprise's industry in year n-1;

[0051] The assessment module evaluates the low-carbon development trend of enterprises based on the following principles:

[0052] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are higher than the industry level;

[0053] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are lower than the industry level;

[0054] like And CEFn,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emissions are higher than the industry level;

[0055] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emission level is lower than the industry level;

[0056] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emission level is higher than the industry level;

[0057] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emissions are lower than the industry level;

[0058] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emission level is higher than the industry level;

[0059] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emissions are lower than the industry level;

[0060] in, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, Q n,j 、P n,j are the output and unit price of the company's products on the jth day of the nth year respectively.

[0061] In a fourth aspect, the present invention proposes an enterprise low-carbon development optimization system based on power data, comprising the aforementioned enterprise low-carbon development situation assessment system and an optimization strategy determination module;

[0062] The optimization strategy determination module is used to determine the enterprise low-carbon development optimization strategy based on the evaluation results obtained by the enterprise low-carbon development trend evaluation system, specifically including:

[0063] If the company is in a trend of increasing carbon emissions, it should adopt an optimization strategy of building new energy to reduce carbon emissions during the production process of its products.

[0064] In the optimization strategy of building new energy to reduce carbon emissions in the production process, the minimum capacity of building new energy is G min Calculated based on the following conditions:

[0065]

[0066] In the above formula, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, G is the capacity of the enterprise to build new energy, h n,j is the number of hours of utilization of new energy power generation equipment on the jth day of the nth year, EI n,j is the average electricity carbon emission factor of the grid node where the enterprise is located on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, U n,j is the cost of renewable energy electricity for the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise.

[0067] Compared with the prior art, the present invention has the following beneficial effects:

[0068] 1. The present invention proposes a method for evaluating the low-carbon development trend of an enterprise based on electricity data, including constructing a coupling model of enterprise electricity and carbon emissions based on the enterprise's historical energy data, calculating the enterprise's carbon emissions and low-carbon development factor in real time according to the coupling model of enterprise electricity and carbon emissions, and obtaining the enterprise's benchmark development trend curve, and evaluating the enterprise's low-carbon development trend based on the enterprise's carbon emissions, the enterprise's low-carbon development factor and the enterprise's benchmark development trend curve. This method utilizes the characteristics of strong real-time and high accuracy of electricity data to achieve real-time and accurate evaluation of the enterprise's own low-carbon development trend during its development process.

[0069] 2. The present invention proposes a method for optimizing enterprise low-carbon development based on power data. The method determines the enterprise low-carbon development optimization strategy according to the evaluation results of the enterprise's low-carbon development situation, including the optimization strategy of building new energy to reduce carbon emissions of products during the production process when the enterprise is in a trend of increasing carbon, and obtains the minimum capacity for building new energy, thus providing the enterprise low-carbon development optimization strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 This is an overall flow chart of the evaluation method described in Example 1.

[0071] Figure 2This is an overall flow chart of the optimization method described in Example 2.

[0072] Figure 3 This is a structural diagram of the evaluation system described in Example 3.

[0073] Figure 4 This is a structural diagram of the optimization system described in Example 4. DETAILED DESCRIPTION

[0074] The present invention will be further described in detail below with reference to specific embodiments and the accompanying drawings.

[0075] Example 1:

[0076] like Figure 1 As shown in FIG, a method for evaluating the low-carbon development trend of an enterprise based on power data is carried out in the following steps:

[0077] 1. Based on the company's historical energy data, including the company's annual fossil fuel consumption, net purchased electricity and heat data, the company's historical carbon emissions are calculated using the following formula:

[0078]

[0079] In the above formula, CEF n is the carbon emissions of the enterprise in the nth year, CF n,m 、CC n,m , OC n,m are the consumption, carbon content, and carbon oxidation rate of the mth fossil fuel of the enterprise in year n, respectively. n EF n are the net purchased electricity and net purchased heat of the enterprise in year n, EI n 、EH n are the average electricity carbon emission factor and heat emission factor of the grid node where the enterprise is located in the nth year, CEP n is the carbon emissions from the enterprise’s industrial production process in year n, and M is the number of fossil fuel types.

[0080] Typical energy accounting parameters of this embodiment are shown in Table 1:

[0081] Table 1 Typical energy carbon emission accounting parameters

[0082]

[0083] 2. Use the Autoregressive Distributed Lag (ARDL) model to construct the following enterprise electricity consumption and carbon emissions coupling model, and determine the coefficients in the model based on the enterprise's historical carbon emissions:

[0084]

[0085] In the above formula, c0 is the basic influence constant, α i , β i , γ i is the influence coefficient, r, s, q are the lag orders, EE n-i is the net purchased electricity of the enterprise in year ni, Q n-i The output of the industry in the nith year.

[0086] 3. Obtain enterprise electricity consumption data in real time and calculate the enterprise's carbon emissions CEF on the jth day of the nth year in real time based on the following enterprise electricity and carbon emissions coupling model: n,j :

[0087]

[0088] 4. Collect the company’s daily output Q n,j and product unit price P n,j , forming the enterprise information data set of the jth day of the nth year {(CEF n，j , Q n，j P n，j )}.

[0089] 5. Calculate the enterprise's low-carbon development factor based on the enterprise's information data set on day j of year n:

[0090]

[0091] In the above formula, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, and CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year.

[0092] 6. Based on the energy and economic data of the enterprise's industry in the n-1th year, the enterprise's baseline development trend curve is obtained:

[0093] f(Q n,j P n,j )=IAC n-1 Q n,j P n,j

[0094]

[0095] In the above formula, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, IAC n-1 , IEC n-1 , IGP n-1 They are respectively the carbon emission intensity, total carbon emissions and total output value of the industry in which the enterprise is located in the n-1th year.

[0096] 7. Evaluate the company's low-carbon development trend based on its carbon emissions, low-carbon development factor, and its benchmark development trend curve, including:

[0097] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are higher than the industry level;

[0098] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are lower than the industry level;

[0099] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emissions are higher than the industry level;

[0100] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emission level is lower than the industry level;

[0101] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emission level is higher than the industry level;

[0102] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emissions are lower than the industry level;

[0103] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emission level is higher than the industry level;

[0104] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emissions are lower than the industry level;

[0105] in, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, respectively.

[0106] Example 2:

[0107] like Figure 2 As shown, a method for optimizing enterprise low-carbon development based on electricity data includes:

[0108] A. Use steps 1-7 in Example 1 to evaluate the low-carbon development trend of the enterprise.

[0109] B. Determine the company's low-carbon development optimization strategy based on the company's low-carbon development situation assessment results, including:

[0110] If the company is on a carbon-increasing trend, it should adopt an optimization strategy of developing new energy sources to reduce carbon emissions during the production process;

[0111] If the company's emissions are higher than the industry average, it can adopt the development of low-carbon production technologies based on external learning;

[0112] If the company's emissions are lower than the industry average, it can adopt internal innovation to develop low-carbon production technologies;

[0113] If an enterprise is in the process of reducing production, it can enhance the added value of its products.

[0114] Among them, in the optimization strategy of building new energy to reduce carbon emissions in the production process, the minimum capacity of building new energy is G min Calculated based on the following conditions:

[0115]

[0116] In the above formula, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, G is the capacity of the enterprise to build new energy, h n,j is the number of hours of utilization of new energy power generation equipment on the jth day of the nth year, EI n,j is the average electricity carbon emission factor of the grid node where the enterprise is located on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, U n,j is the cost of renewable energy electricity for the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise.

[0117] Example 3:

[0118] like Figure 3As shown, a low-carbon development trend assessment system for enterprises based on power data includes a coupling model construction module, a low-carbon development factor calculation module, a benchmark development trend curve acquisition module, and an assessment module.

[0119] The coupling model building module is used to build the following enterprise electricity and carbon emissions coupling model based on the enterprise's historical energy data:

[0120]

[0121] In the above formula, CEF n is the carbon emissions of the enterprise in the nth year, c0 is the basic impact constant, α i , β i , γ i is the influence coefficient, r, s, q are the lag orders, EE n-i is the net purchased electricity of the enterprise in year ni, Q n-i The output of the industry in the nith year, CEF n Calculated based on the following formula:

[0122]

[0123] In the above formula, CEF n is the carbon emissions of the enterprise in the nth year, CF n,m 、CC n,m , OC n,m are the consumption, carbon content, and carbon oxidation rate of the mth fossil fuel of the enterprise in year n, respectively. n EF n are the net purchased electricity and net purchased heat of the enterprise in year n, EI n 、EH n are the average electricity carbon emission factor and heat emission factor of the grid node where the enterprise is located in the nth year, CEP n is the carbon emissions from the enterprise’s industrial production process in year n, and M is the number of fossil fuel types.

[0124] The low-carbon development factor calculation module is used to calculate the enterprise's carbon emissions and low-carbon development factor in real time based on the enterprise's electricity and carbon emissions coupling model. The calculation formula of the low-carbon development factor is as follows:

[0125]

[0126] In the above formula, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, and CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year.

[0127] The benchmark development trend curve acquisition module is used to obtain the benchmark development trend curve of the enterprise based on the energy and economic data of the industry in which the enterprise is located in the n-1th year:

[0128] f(Q n,j P n,j )=IAC n-1 Q n,j P n,j

[0129]

[0130] In the above formula, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, IAC n-1 , IEC n-1 , IGP n-1 They are respectively the carbon emission intensity, total carbon emissions and total output value of the industry in which the enterprise is located in the n-1th year.

[0131] The evaluation module is used to evaluate the low-carbon development trend of an enterprise based on its carbon emissions, its low-carbon development factor, and its benchmark development trend curve, including:

[0132] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are higher than the industry level;

[0133] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are lower than the industry level;

[0134] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emissions are higher than the industry level;

[0135] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emission level is lower than the industry level;

[0136] like And CEF n,j ≥f(Q n,j P n,j), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emission level is higher than the industry level;

[0137] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emissions are lower than the industry level;

[0138] like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emission level is higher than the industry level;

[0139] like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emissions are lower than the industry level.

[0140] Example 4:

[0141] like Figure 4 As shown, a low-carbon development optimization system for enterprises based on power data includes the enterprise low-carbon development situation assessment system and the optimization strategy determination module described in Example 3.

[0142] The optimization strategy determination module is used to determine the enterprise's low-carbon development optimization strategy based on the evaluation results obtained by the enterprise low-carbon development trend evaluation system, including: if the enterprise is in a carbon-increasing trend, then adopt an optimization strategy of building new energy to reduce carbon emissions in the production process of products. In this strategy, the minimum capacity of building new energy is G min Calculated based on the following conditions:

[0143]

[0144] In the above formula, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, G is the capacity of the enterprise to build new energy, h n,j is the number of hours of utilization of new energy power generation equipment on the jth day of the nth year, EI n,j is the average electricity carbon emission factor of the grid node where the enterprise is located on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, U n,j is the cost of renewable energy electricity for the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise.

Claims

1. A method for evaluating the low-carbon development trend of an enterprise based on power data, characterized in that: The evaluation method includes: S1. Build a coupling model of enterprise electricity consumption and carbon emissions based on the enterprise's historical energy data, including: S11. Calculate the company's historical carbon emissions based on its historical energy data: In the above formula, CEF n is the carbon emissions of the enterprise in the nth year, CF n,m 、CC n,m , OC n,m are the consumption, carbon content, and carbon oxidation rate of the mth fossil fuel of the enterprise in year n, respectively. n EF n are the net purchased electricity and net purchased heat of the enterprise in year n, EI n 、EH n are the average electricity carbon emission factor and heat emission factor of the grid node where the enterprise is located in the nth year, CEP n is the carbon emissions from the industrial production process of the enterprise in year n, and M is the number of types of fossil fuels; S12. Based on the historical carbon emissions of enterprises, the following coupling model of enterprise electricity consumption and carbon emissions is constructed using the autoregressive distributed lag model: In the above formula, c0 is the basic influence constant, α i , β i , γ i is the influence coefficient, r, s, q are the lag orders, EE n-i is the net purchased electricity of the enterprise in year ni, Q n-i is the output of the enterprise in year ni; S2. Calculate the company's carbon emissions and low-carbon development factor in real time based on the coupled model of the company's electricity consumption and carbon emissions, and obtain the company's baseline development trend curve. The company's low-carbon development factor is calculated based on the following formula: In the above formula, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, and CEF n,j is the carbon emissions of the enterprise on the jth day of year n; The company's baseline development trend curve is: f(Q n,j P n,j )=IAC n-1 Q n,j P n,j In the above formula, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, IAC n-1 The carbon emission intensity of the enterprise's industry in year n-1; S3. Evaluate the low-carbon development trend of the enterprise based on its carbon emissions, low-carbon development factor and its benchmark development trend curve.

2. The method for evaluating the low-carbon development trend of an enterprise based on power data according to claim 1 is characterized in that: The S3 includes: like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are higher than the industry level; like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are lower than the industry level; like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emissions are higher than the industry level; like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emission level is lower than the industry level; like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emission level is higher than the industry level; like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emissions are lower than the industry level; like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emission level is higher than the industry level; like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emissions are lower than the industry level; in, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, Q n,j 、P n,j are the output and unit price of the company's products on the jth day of the nth year respectively.

3. A method for optimizing enterprise low-carbon development based on power data, characterized in that: The optimization method comprises: A. Use the assessment method described in any one of claims 1-2 to assess the low-carbon development trend of the enterprise; B. Determine the company's low-carbon development optimization strategy based on the company's low-carbon development situation assessment results, including: If the company is in a trend of increasing carbon emissions, it should adopt an optimization strategy of building new energy to reduce carbon emissions during the production process of its products.

4. The enterprise low-carbon development optimization method based on power data according to claim 3 is characterized in that: In the optimization strategy of building new energy to reduce carbon emissions in the production process, the minimum capacity of building new energy is G min Calculated based on the following conditions: In the above formula, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, G is the capacity of the enterprise to build new energy, h n,j is the number of hours of utilization of new energy power generation equipment on the jth day of the nth year, EI n,j is the average electricity carbon emission factor of the grid node where the enterprise is located on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, U n,j is the cost of renewable energy electricity for the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise.

5. A system for evaluating the low-carbon development trend of enterprises based on power data, characterized in that: The system includes a coupling model construction module, a low-carbon development factor calculation module, a benchmark development situation curve acquisition module, and an evaluation module; The coupling model building module is used to build the following enterprise electricity and carbon emissions coupling model based on the enterprise's historical energy data: In the above formula, CEF n is the carbon emissions of the enterprise in the nth year, c0 is the basic impact constant, α i , β i , γ i is the influence coefficient, r, s, q are the lag orders, EE n-i is the net purchased electricity of the enterprise in year ni, Q n-i is the output of the enterprise in year ni, CEF n Calculated based on the following formula: In the above formula, CEF n is the carbon emissions of the enterprise in the nth year, CF n,m 、CC n,m , OC n,m are the consumption, carbon content, and carbon oxidation rate of the mth fossil fuel of the enterprise in year n, respectively. n EF n are the net purchased electricity and net purchased heat of the enterprise in year n, EI n 、EH n are the average electricity carbon emission factor and heat emission factor of the grid node where the enterprise is located in the nth year, CEP n is the carbon emissions from the industrial production process of the enterprise in year n, and M is the number of types of fossil fuels; The low-carbon development factor calculation module is used to calculate the carbon emissions and low-carbon development factor of the enterprise in real time based on the enterprise electricity and carbon emissions coupling model. The low-carbon development factor of the enterprise is calculated based on the following formula: In the above formula, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, and CEF n,j is the carbon emissions of the enterprise on the jth day of year n; The benchmark development trend curve acquisition module is used to obtain the benchmark development trend curve of the enterprise: f(Q n,j P n,j )=IAC n-1 Q n,j P n,j In the above formula, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, IAC n-1 The carbon emission intensity of the enterprise's industry in year n-1; The evaluation module is used to evaluate the low-carbon development trend of an enterprise based on the enterprise's carbon emissions, the enterprise's low-carbon development factor, and the enterprise's benchmark development trend curve.

6. The enterprise low-carbon development trend assessment system based on power data according to claim 5 is characterized in that: The assessment module evaluates the low-carbon development trend of enterprises based on the following principles: like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are higher than the industry level; like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and carbon emissions, and its emissions are lower than the industry level; like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emissions are higher than the industry level; like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and increasing carbon emissions, and its emission level is lower than the industry level; like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emission level is higher than the industry level; like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of increasing production and reducing carbon emissions, and its emissions are lower than the industry level; like And CEF n,j ≥f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emission level is higher than the industry level; like And CEF n,j <f(Q n,j P n,j ), the enterprise is judged to be in a trend of reducing production and carbon emissions, and its emissions are lower than the industry level; in, are the low-carbon development factors of the enterprise when carbon increases and decreases on the jth day of the nth year, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise, Q n,j 、P n,j are the output and unit price of the company's products on the jth day of the nth year respectively.

7. An enterprise low-carbon development optimization system based on power data, characterized by: The system includes the enterprise low-carbon development situation assessment system and the optimization strategy determination module according to claim 5 or 6; The optimization strategy determination module is used to determine the enterprise low-carbon development optimization strategy based on the evaluation results obtained by the enterprise low-carbon development trend evaluation system, specifically including: If the company is in a trend of increasing carbon emissions, it should adopt an optimization strategy of building new energy to reduce carbon emissions during the production process of its products.

8. The enterprise low-carbon development optimization system based on power data according to claim 7 is characterized in that: In the optimization strategy of building new energy to reduce carbon emissions in the production process, the minimum capacity of building new energy is G min Calculated based on the following conditions: In the above formula, CEF n,j is the carbon emissions of the enterprise on the jth day of the nth year, G is the capacity of the enterprise to build new energy, h n,j is the number of hours of utilization of new energy power generation equipment on the jth day of the nth year, EI n,j is the average electricity carbon emission factor of the grid node where the enterprise is located on the jth day of the nth year, Q n,j 、P n,j are the output and unit price of the enterprise on the jth day of the nth year, U n,j is the cost of renewable energy electricity for the enterprise on the jth day of the nth year, f(Q n,j P n,j ) is the benchmark development trend of the enterprise.

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