Carbon emission management method suitable for distributed energy

Abstract

The invention relates to the technical field of data analysis, in particular to a carbon emission management method suitable for distributed energy, and the method comprises the steps: estimating the theoretical carbon emission of a production department, calculating the actual carbon emission according to production data, and calculating the carbon emission progress according to the theoretical carbon emission and the actual carbon emission; calculating a task progress according to the production task and the production data, carrying out data analysis on a carbon emission progress and the task progress, adding identifiers to production departments, integrating processes of the production departments under the same identifier to obtain process information, extracting process characteristics of the process information, and carrying out data analysis on the process characteristics; the flow characteristics under different identifiers are analyzed, the management model is generated, the production department is managed based on the management model, the management mode of the distributed production department is optimized, the intelligent management effect is improved, and the purposes of emission reduction and efficiency improvement of enterprise development are achieved.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a carbon emission management method applicable to distributed energy. Background Art

[0002] Distributed energy is a way of energy supply at the user end. It can operate independently or in conjunction with the grid. It integrates and optimizes the resource allocation conditions of multiple user ends to maximize benefits. In the development of an enterprise, carbon emissions are a key factor in measuring the rationality of resource utilization. When an enterprise has several different production departments, each production department can be regarded as a user end of electricity resources. Several production departments as user ends of electricity resources meet the needs of distributed energy management. Through the distributed management of electricity resources, the company's carbon emissions can be reduced, the goal of reducing emissions and increasing efficiency can be achieved, and the company's long-term and green development can be realized.

[0003] In the existing technology, due to the different production models and production processes among different production departments, there are great differences in the use of electricity resources. Due to problems with production-related equipment and staff, the task progress of the production department and the progress of carbon emissions caused by energy consumption are not unified, making centralized management difficult. As a result, carbon emissions easily exceed the standards and do not meet green and sustainable development requirements. Summary of the invention

[0004] The purpose of the present invention is to solve the problems in the background technology and to propose a carbon emission management method suitable for distributed energy.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solution: a carbon emission management method applicable to distributed energy, comprising the following steps:

[0006] S1. Obtain the production plan of the enterprise, assign production tasks to the production department according to the production plan, and evaluate the theoretical total carbon emissions of the production department when completing the production tasks;

[0007] S2. Obtain production data from the production department and calculate the actual carbon emissions of the department;

[0008] S3. Calculate the carbon emission progress of the production department based on theoretical carbon emissions and actual carbon emissions, calculate the task progress of the production department based on production data and production tasks, evaluate the production performance indicators of the department, and add classification labels to the production department based on the production performance indicators;

[0009] S4, obtaining the production processes of different production departments in the same classification identification, integrating the process information of the production processes of different production departments, and extracting the process characteristics of the process information;

[0010] S5. Obtain process characteristics of production process information under different classification identifiers, analyze the process characteristics, obtain the difference characteristics between different process characteristics, generate a management model according to the difference characteristics, and manage the production department based on the management model.

[0011] As a further solution of the present invention, a method for evaluating the theoretical total carbon emissions of a production department in completing a production task is as follows:

[0012] Obtain the procurement parameters and production process parameters required for the production task, obtain the power consumption parameters and quality control parameters of the production department, and use the evaluation formula The theoretical total carbon emissions LTi of the production department completing the production task is calculated; CGi is the procurement parameter, TPi is the unit procurement, SCi is the production process parameter, GHi is the power consumption parameter, and PKi is the quality control parameter; F(CGi) is the carbon emission standard quantification function of the procurement parameter CGi; i is the production department number, i is a positive integer; T is the production cycle.

[0013] As a further solution of the present invention, the consumption parameters and production time of the production department are obtained, and the actual carbon emissions are calculated by the formula The actual carbon emission SJi is calculated; XHi is the consumption parameter.

[0014] As a further solution of the present invention, the method for adding classification identification to the production department is:

[0015] Through the task progress formula The task progress RJi of the production department is calculated, and the carbon emission progress TJi is calculated by calculating the ratio of the actual carbon emissions to the theoretical carbon emissions. The production performance index calculation model is established based on the task progress RJi and the carbon emission progress TJi;

[0016] The expression of the production performance index calculation model is:

[0017] SZi is the production performance index of the production department;

[0018] Perform data analysis on the production performance index SZi. If the production performance index SZi is not less than 1, it is marked as a high-performance index; if the production performance index SZi is greater than 1, it is marked as a low-performance index;

[0019] An efficient production department identification is added to the production department corresponding to the production performance indicator marked with a high-performance indicator, and an inefficient production department identification is added to the production department corresponding to the production performance indicator marked with a performance indicator.

[0020] As a further solution of the present invention, a method for extracting process features of process information is:

[0021] Obtain the process steps in the same production process in the process information, divide the production process into several process links according to the process steps, and use the estimated capacity calculation formula The estimated capacity HYj of the process link is calculated; ZSj is the number of online equipment in the production process link, ZRj is the number of online employees, ZGj is the online working hours, αj is the processing difficulty coefficient in the process link, S t is the unit processing time; j is the process link number, j is a positive integer, j∈[1, N], N is the total number of process links;

[0022] Analysis formula through links The capacity analysis value FXj of the process link is calculated, the maximum value of the capacity analysis values ​​FXj corresponding to several process links in the same production process is obtained, and the corresponding process link is marked as the target process link.

[0023] As a further solution of the present invention, the number of online devices ZSj in the target process link is calculated by ratio with the number of required devices XSj to obtain a first proportional parameter of the production process, and the number of online employees ZRj in the target process link is calculated by ratio with the number of required employees XRj to obtain a second proportional parameter of the production process;

[0024] The mean values ​​of several first proportion parameters and second proportion parameters of different production processes in the same process information are calculated respectively, and the mean calculation result of the first proportion parameters is used as the first feature P of the process information, and the mean calculation result of the second proportion parameters is used as the second feature Q of the process information. The first feature P and the second feature Q are combined to obtain the process feature {P, Q} of the process information.

[0025] As a further solution of the present invention, the process feature identified with the efficient production department is marked as the reference feature CK{P1, Q1}, and the process feature identified with the inefficient production department is marked as the adjustment feature TZ{P2, Q2};

[0026] The method to obtain the difference characteristics between different process characteristics is:

[0027] The reference feature CK{P1, Q1} and the adjustment feature TZ{P2, Q2} are calculated by difference to obtain the difference feature CY{P3, Q3}, wherein P3 is calculated by the first difference formula P3=P1-P2-Px, and Px is the first difference threshold; Q3 is calculated by the second difference formula Q3=Q1-Q2-Qx, and Qx is the second difference threshold;

[0028] Generate a management model based on the difference characteristics CY{P3, Q3}.

[0029] As a further solution of the present invention, the expression of the management model is:

[0030] Gb is the management number;

[0031] If the management number Gb is 1, the online equipment and the number of online employees of the department marked as having inefficient production are managed simultaneously;

[0032] If the management number Gb is 2, the online equipment of the department marked with inefficient production is managed;

[0033] If the management number Gb is 3, the number of online employees in the department marked as having inefficient production will be managed;

[0034] If the management number Gb is 4, the production process of the department marked as having inefficient production is managed.

[0035] Preferably, the carbon emission management method applicable to distributed energy also includes:

[0036] Obtain the application information of the enterprise's distributed energy, and build an energy level association diagram of the distributed energy based on the application information;

[0037] Construct an energy management diagram based on the enterprise’s distributed energy monitoring data and energy level association diagram;

[0038] Obtain the energy usage information of each production process in each production task of each production department of the enterprise, and based on the obtained energy usage information, construct an energy loss correspondence table of each production process in each production task of each production department;

[0039] Based on the current production operation status of each production workshop of the enterprise, a production thread simulation diagram guided by the timeline is constructed;

[0040] Generate annotation data based on the simulated output data of the production thread simulation diagram and the energy use data determined by querying the energy loss corresponding table and annotate it to the energy management diagram to form a visual energy management diagram;

[0041] Convert the energy usage data in the visual energy management diagram into carbon emission data to form a visual carbon emission management diagram;

[0042] Analyze the energy level correlation diagram to determine the energy level correlation relationship and correlation ratio;

[0043] Analyze the labeled data in the visual energy management diagram to determine the energy demand;

[0044] Based on the energy demand situation, energy level correlation and correlation ratio, determine the demand and use of the dominant energy of distributed energy;

[0045] Based on the energy usage data in the energy management diagram, determine the actual usage of the dominant energy of the distributed energy;

[0046] Based on the demand usage and actual usage, the energy utilization of the dominant energy is calculated; the energy utilization includes: the utilization rate of each energy and the total utilization score; the calculation formula of the total utilization score is as follows:

[0047]

[0048] In the formula, ZP represents the total score; P i is the utilization rate of the i-th dominant energy, M Si is the actual usage of the i-th dominant energy; M Hi is the demand for the i-th dominant energy; n represents the total number of dominant energy items; α i is the preset weight coefficient corresponding to the ith dominant energy source; C i is the utilization rate and score conversion coefficient of the preset i-th dominant energy source;

[0049] Based on the demand usage, actual usage, and energy utilization of the dominant energy, a display dashboard is generated and displayed in a floating manner at a preset position of the visual carbon emission management diagram;

[0050] Among them, based on the energy demand situation, energy level correlation relationship and correlation ratio, the demand and use of the dominant energy of distributed energy is determined, including:

[0051] Extract the energy with energy level correlation in the energy demand situation as the grouped energy to be analyzed.

[0052] According to the demand and correlation ratio of the lower-level energy in the grouped energy to be analyzed, the demand of the upper-level energy is derived;

[0053] Statistics are collected on the demand for superior energy and the demand for energy not included in the grouped energy to be analyzed, and the demand and usage of the dominant energy of distributed energy is generated.

[0054] Preferably, the carbon emission management method applicable to distributed energy also includes:

[0055] Parse the simulation output data of the production thread simulation diagram, query the energy loss correspondence table to determine the energy usage data, and obtain the energy demand forecast data;

[0056] Determine the demand forecast data of the dominant energy of distributed energy based on the energy demand forecast data, energy level correlation relationship and correlation ratio;

[0057] Generate energy control plans based on the demand forecast data of the dominant energy of distributed energy and the actual current energy usage, and adjust the energy control plans according to the historical records of energy utilization;

[0058] Among them, the adjustment steps for the energy regulation plan are as follows:

[0059] The historical records are sorted in ascending order according to the time difference from the current time, and the energy utilization rate in the historical records with a preset number of digits before the sorting is extracted to calculate the average value;

[0060] The volatility adjustment value is determined by comprehensively analyzing all historical records. The calculation formula of the volatility adjustment value is as follows:

[0061]

[0062] Where B represents the fluctuation adjustment value, b 0 is the pre-configured initial value; μ is the pre-configured fine-tuning amplitude; N 1 N is the number of times in the historical records that the utilization is greater than or equal to the estimated utilization corresponding to the control value; 2 b is the number of times in the historical records that the utilization rate is less than the estimated utilization rate corresponding to the control value; b min , b max are pre-configured lower and upper limits respectively;

[0063] Based on the average value, fluctuation adjustment value and the scheme value in the energy control scheme, the control value is calculated. The calculation formula is as follows:

[0064]

[0065] Wherein, T represents the control value; F represents the scheme value; and J represents the average value.

[0066] Compared with the existing technology, the advantages of the present invention are: by performing data analysis on the carbon emission progress and task progress, adding labels to the production departments, integrating the processes of the production departments under the same label to obtain process information, extracting the process characteristics of the process information, analyzing the process characteristics under different labels and generating a management model, managing the production departments based on the management model, optimizing the management method of distributed production departments, improving the intelligent management effect, and achieving the goal of reducing emissions and increasing efficiency in enterprise development. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 is a flow chart of the present invention;

[0068] Figure 2 is an energy level correlation diagram in an embodiment of the present invention;

[0069] Figure 3 It is a simulation diagram of a production thread in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0071] Reference Figure 1 , a carbon emission management method applicable to distributed energy, comprising the following steps:

[0072] S1. Obtain the production plan of the enterprise, assign production tasks to the production department according to the production plan, and evaluate the theoretical total carbon emissions of the production department when completing the production tasks;

[0073] S2. Obtain production data from the production department and calculate the actual carbon emissions of the department;

[0074] S3. Calculate the carbon emission progress of the production department based on theoretical carbon emissions and actual carbon emissions, calculate the task progress of the production department based on production data and production tasks, evaluate the production performance indicators of the department, and add classification labels to the production department based on the production performance indicators;

[0075] S4, obtaining the production processes of different production departments in the same classification identification, integrating the process information of the production processes of different production departments, and extracting the process characteristics of the process information;

[0076] S5. Obtain process characteristics of production process information under different classification identifiers, analyze the process characteristics, obtain the difference characteristics between different process characteristics, generate a management model according to the difference characteristics, and manage the production department based on the management model.

[0077] The method for evaluating the theoretical total carbon emissions of the production department to complete production tasks is:

[0078] Obtain the procurement parameters and production process parameters required for the production task, obtain the power consumption parameters and quality control parameters of the production department, and use the evaluation formula The total theoretical carbon emission LTi of the production department completing the production task is calculated; CGi is the procurement parameter, TPi is the unit procurement, SCi is the production process parameter, GHi is the power consumption parameter, and PKi is the quality control parameter; F(CGi) is the carbon emission standard quantification function of the procurement parameter CGi; i is the production department number, i is a positive integer; T is the production cycle, the unit is day; the procurement parameter CGI is calculated by the procurement parameter calculation formula CGi=k1×A1+k2×A2+k3×A3+k4×A4, where A1 to A4 and k1 to k4 refer to the raw material procurement volume, processing auxiliary material procurement volume, production equipment procurement volume, related system procurement volume and the corresponding parameter coefficients respectively;

[0079] The production process parameter SCi is calculated by the production process parameter calculation formula SCi = w1 × B1 + w2 × B2 + w3 × B3, where B1 to B3 and w1 to w3 refer to the average online equipment quantity, average online number of employees, average online working hours and corresponding parameter coefficients in a production cycle T respectively;

[0080] The power consumption parameter GHi is calculated based on the average daily power consumption of the production department's historical production tasks; the quality control parameter pki is calculated based on the average pass rate of the production department's historical production tasks;

[0081] The method for calculating the actual carbon emissions of the sector is:

[0082] Obtain the consumption parameters and production time of the production department, and calculate the actual carbon emissions through the formula The actual carbon emission SJi is calculated; XHi is the consumption parameter, and its calculation formula is XHi=k1×C1+k2×C2+k3×C3+k4×C4, where C1 to C4 are the consumption corresponding to the purchase volume; SPi is the actual qualified rate, and t is the production time in days;

[0083] The method to add classification identification to the production department is:

[0084] Through the task progress formula The task progress RJi of the production department is calculated, and the carbon emission progress TJi is calculated by calculating the ratio of the actual carbon emissions to the theoretical carbon emissions. The production performance index calculation model is established based on the task progress RJi and the carbon emission progress TJi;

[0085] The expression of the production performance index calculation model is:

[0086] SZi is the production performance index of the production department;

[0087] Perform data analysis on the production performance index SZi. If the production performance index SZi is not less than 1, it is marked as a high-performance index; if the production performance index SZi is greater than 1, it is marked as a low-performance index;

[0088] Add a high-efficiency production department mark to the production department corresponding to the production performance indicator marked with a high-performance indicator, and add an inefficient production department mark to the production department corresponding to the production performance indicator marked with a performance indicator;

[0089] The method for extracting process features of process information is:

[0090] Obtain the process steps in the same production process in the process information, divide the production process into several process links according to the process steps, and use the estimated capacity calculation formula The estimated capacity HYj of the process link is calculated; ZSj is the number of online equipment in the production process link, ZRj is the number of online employees, ZGj is the online working hours, αj is the processing difficulty coefficient in the process link, S t is the unit processing time; j is the process link number, j is a positive integer, j∈[1,N], N is the total number of process links; the processing difficulty coefficient αj is calculated by the difficulty coefficient calculation formula αj=k×XSj×XRj, XSj is the number of required devices based on unit processing time, XRj is the number of required people based on unit processing time, and k is the proportional coefficient; it should be noted that online equipment refers to equipment that can work completely normally, and any hardware and system problems of the equipment cannot be considered as online equipment;

[0091] Analysis formula through links Calculate the capacity analysis value FXj of the process link, obtain the maximum value of the capacity analysis values ​​FXj corresponding to several process links in the same production process, and mark the corresponding process link as the target process link;

[0092] The first proportional parameter of the production process is obtained by calculating the ratio of the number of online devices ZSj in the target process link to the number of required devices XSj, and the second proportional parameter of the production process is obtained by calculating the ratio of the number of online employees ZRj in the target process link to the number of required employees XRj;

[0093] Calculate the mean of several first proportion parameters and second proportion parameters of different production processes in the same process information respectively, use the mean calculation result of the first proportion parameters as the first feature P of the process information, use the mean calculation result of the second proportion parameters as the second feature Q of the process information, and combine the first feature P and the second feature Q to obtain the process feature {P, Q} of the process information;

[0094] The process characteristics identified with efficient production departments are marked as reference characteristics CK{P1, Q1}, and the process characteristics identified with inefficient production departments are marked as adjustment characteristics TZ{P2, Q2};

[0095] The method to obtain the difference characteristics between different process characteristics is:

[0096] The reference feature CK{P1, Q1} and the adjustment feature TZ{P2, Q2} are calculated by difference to obtain the difference feature CY{P3, Q3}, wherein P3 is calculated by the first difference formula P3=P1-P2-Px, and Px is the first difference threshold; Q3 is calculated by the second difference formula Q3=Q1-Q2-Qx, and Qx is the second difference threshold;

[0097] Generate a management model based on the difference characteristics CY{P3, Q3};

[0098] The expression of the management model is:

[0099] Gb is the management number;

[0100] If the management number Gb is 1, the online equipment and the number of online employees of the department marked as having inefficient production are managed simultaneously;

[0101] If the management number Gb is 2, the online equipment of the department marked with inefficient production is managed;

[0102] If the management number Gb is 3, the number of online employees in the department marked as having inefficient production will be managed;

[0103] If the management number Gb is 4, the production process of the inefficient production department is managed; the management method of online equipment can be to repair equipment, upgrade equipment, adjust equipment parameters or increase the number of online equipment, the purpose is to improve the processing efficiency of the equipment, avoid low processing efficiency due to equipment reasons, increase energy consumption, and increase carbon emissions; the management method of the number of online employees can be to increase the number of online employees, replace online employees with experienced employees or increase employee reward mechanisms, the purpose is to improve the overall work efficiency of employees, avoid low work efficiency due to lack of manpower, lack of experience or low work motivation, increase working hours, and increase carbon emissions; the management method of production process can be to adjust the process sequence, eliminate redundant processes or integrate processes, the purpose is to optimize the production process and avoid increased carbon emissions caused by unreasonable production processes;

[0104] By estimating the theoretical carbon emissions of the production department and calculating the actual carbon emissions based on the production data, calculating the carbon emission progress based on the theoretical carbon emissions and the actual carbon emissions, calculating the task progress based on the production tasks and production data, performing data analysis on the carbon emission progress and task progress, adding labels to the production departments, integrating the processes of the production departments under the same label to obtain process information, extracting the process characteristics of the process information, analyzing the process characteristics under different labels and generating a management model, and managing the production departments based on the management model, we have optimized the management method of distributed production departments, improved the effect of intelligent management, and achieved the goal of reducing emissions and increasing efficiency in enterprise development.

[0105] In one embodiment, the carbon emission management method applicable to distributed energy sources further includes:

[0106] Obtain the application information of the enterprise's distributed energy, and build an energy level association diagram of the distributed energy based on the application information; Figure 2The energy level association diagram in an actual application example is shown in Figure 1. The distributed energy used by the enterprise includes: energy a, energy b, energy c, energy d and energy e. Energy a is configured as electricity generated by photovoltaics; energy d is configured as wind power; energy b is configured as nitrogen produced by a nitrogen generator driven by photovoltaic power and wind power; energy e is configured as steam generated by heating water with photovoltaic power; energy c is configured as power supply from the distribution network. The relationship between each distributed energy source can be intuitively seen from the energy level association diagram.

[0107] Based on the enterprise's distributed energy monitoring data and energy level association diagram, an energy management diagram is constructed; the monitoring data is the current usage data of each energy source, and the usage data is marked next to the icon of each energy source to form an energy management diagram;

[0108] Obtain the energy usage information of each production process in each production task of each production department of the enterprise, and build an energy loss correspondence table of each production process in each production task of each production department based on the obtained energy usage information; the energy loss correspondence table indicates the amount of each energy required to produce a unit number of products in the production process; for example: if the unit number is 200 pieces per piece, the energy consumption c is TM, the energy consumption b is TB, and the energy consumption e is TE;

[0109] Based on the current production operation status of each production workshop of the enterprise, a production thread simulation diagram guided by the timeline is constructed; Figure 3 It is a simulation diagram of production threads of a production process in the constructed production workshop; the specific production situation can be obtained from the simulation diagrams of all production threads in the production workshop;

[0110] Based on the simulated output data of the production thread simulation diagram and the energy usage data determined by querying the energy loss corresponding table, the annotation data is generated and annotated to the energy management diagram to form a visual energy management diagram; the specific production process and the output of the corresponding production process can be obtained by statistics on the simulated output data, and the specific energy demand usage data can be obtained by querying the energy loss table, which is annotated next to the icon representing the enterprise's production;

[0111] The energy usage data in the visualized energy management diagram is converted into carbon emission data to form a visualized carbon emission management diagram; the carbon emission data is converted using a pre-configured conversion coefficient; that is, the value of the energy usage data is multiplied by the pre-configured conversion coefficient to obtain the value of the carbon emission data;

[0112] Analyze the energy level correlation diagram to determine the energy level correlation relationship and correlation ratio; the correlation ratio is a non-explicit attribute of the energy level correlation diagram. Figure 2There are two groups with energy level correlation, one group is energy a and energy e, and the other group is energy a, energy b and energy d; among them, the correlation ratio of the first group is how many cubic meters of energy e corresponds to each degree of energy a, that is, 1:X; the correlation ratio of the second group is 1:1:Y or 1.5:0.5:Y, etc., that is, one degree of energy a plus one degree of energy d can produce Y cubic meters of nitrogen;

[0113] Analyze the labeled data in the visual energy management diagram to determine the energy demand situation; the energy demand situation includes energy demand usage data;

[0114] Based on the energy demand, energy level correlation and correlation ratio, determine the demand and use of the dominant energy of distributed energy; the dominant energy is the energy at the top of the energy level correlation and the energy that has no energy level correlation with other energy sources;

[0115] Based on the energy usage data in the energy management diagram, determine the actual usage of the dominant energy of the distributed energy;

[0116] Based on the demand usage and actual usage, the energy utilization of the dominant energy is calculated; the energy utilization includes: the utilization rate of each dominant energy and the total utilization score; the calculation formula of the total utilization score is as follows:

[0117]

[0118] In the formula, ZP represents the total score; P i is the utilization rate of the i-th dominant energy, M Si is the actual usage of the ith dominant energy source; M Hi is the demand for the i-th dominant energy; n represents the total number of energy items; α i is the preset weight coefficient corresponding to the ith dominant energy source; C i is the utilization rate and score conversion coefficient of the preset i-th dominant energy source;

[0119] Based on the demand usage, actual usage, and energy utilization of the dominant energy, a display dashboard is generated and displayed in a floating manner at a preset position of the visual carbon emission management diagram;

[0120] Among them, based on the energy demand situation, energy level correlation relationship and correlation ratio, the demand and use of the dominant energy of distributed energy is determined, including:

[0121] Extract the energy with energy level correlation in the energy demand situation as the grouped energy to be analyzed.

[0122] According to the demand and correlation ratio of the lower-level energy in the grouped energy to be analyzed, the demand of the upper-level energy is derived;

[0123] Statistics are collected on the demand for superior energy and the demand for energy not included in the grouped energy to be analyzed, and the demand and usage of the dominant energy of distributed energy is generated.

[0124] In order to achieve precise control of the energy use of enterprises, the carbon emission management methods applicable to distributed energy also include:

[0125] Parse the simulation output data of the production thread simulation diagram, query the energy loss correspondence table to determine the energy usage data, and obtain the energy demand forecast data;

[0126] Determine the demand forecast data of the dominant energy of distributed energy based on the energy demand forecast data, energy level correlation relationship and correlation ratio;

[0127] Generate energy control plans based on the demand forecast data of the dominant energy of distributed energy and the actual current energy usage, and adjust the energy control plans according to the historical records of energy utilization;

[0128] Among them, the adjustment steps for the energy regulation plan are as follows:

[0129] The historical records are sorted in ascending order according to the time difference from the current time, and the energy utilization rate in the historical records with a preset number of digits before the sorting is extracted to calculate the average value;

[0130] The volatility adjustment value is determined by comprehensively analyzing all historical records. The calculation formula of the volatility adjustment value is as follows:

[0131]

[0132] Where B represents the fluctuation adjustment value, b 0 is the pre-configured initial value; μ is the pre-configured fine-tuning amplitude; N 1 N is the number of times in the historical records that the utilization is greater than or equal to the estimated utilization corresponding to the control value; 2 b is the number of times in the historical records that the utilization rate is less than the estimated utilization rate corresponding to the control value; b min 、b max are pre-configured lower and upper limits respectively;

[0133] Based on the average value, fluctuation adjustment value and the scheme value in the energy control scheme, the control value is calculated. The calculation formula is as follows:

[0134]

[0135] Wherein, T represents the control value; F represents the scheme value; and J represents the average value.

[0136] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A carbon emission management method applicable to distributed energy, characterized in that: The following steps are involved: S1. Obtain the production plan of the enterprise, assign production tasks to the production department according to the production plan, and evaluate the theoretical total carbon emissions of the production department when completing the production tasks; S2. Obtain production data from the production department and calculate the actual carbon emissions of the department; S3. Calculate the carbon emission progress of the production department based on theoretical carbon emissions and actual carbon emissions, calculate the task progress of the production department based on production data and production tasks, evaluate the production performance indicators of the department, and add classification labels to the production department based on the production performance indicators; S4, obtaining the production processes of different production departments in the same classification identification, integrating the process information of the production processes of different production departments, and extracting the process characteristics of the process information; S5. Obtain process characteristics of production process information under different classification identifiers, analyze the process characteristics, obtain the difference characteristics between different process characteristics, generate a management model according to the difference characteristics, and manage the production department based on the management model.

2. A carbon emission management method applicable to distributed energy according to claim 1, characterized in that: The method for evaluating the theoretical total carbon emissions of the production department to complete production tasks is: Obtain the procurement parameters and production process parameters required for the production task, obtain the power consumption parameters and quality control parameters of the production department, and use the evaluation formula The theoretical total carbon emissions LTi of the production department completing the production task is calculated; CGi is the procurement parameter, TPi is the unit procurement, SCi is the production process parameter, GHi is the power consumption parameter, and PKi is the quality control parameter; F(CGi) is the carbon emission standard quantification function of the procurement parameter CGi; i is the production department number, i is a positive integer; T is the production cycle.

3. A carbon emission management method applicable to distributed energy according to claim 2, characterized in that: Obtain the consumption parameters and production time of the production department, and calculate the actual carbon emissions through the formula The actual carbon emission SJi is calculated; XHi is the consumption parameter.

4. A carbon emission management method applicable to distributed energy according to claim 3, characterized in that: The method to add classification identification to the production department is: By task progress formula The task progress RJi of the production department is calculated, and the carbon emission progress TJi is calculated by calculating the ratio of the actual carbon emissions to the theoretical carbon emissions. The production performance index calculation model is established based on the task progress RJi and the carbon emission progress TJi; The expression of the production performance index calculation model is: SZi is the production performance index of the production department; Perform data analysis on the production performance index SZi. If the production performance index SZi is not less than 1, it is marked as a high-performance index; if the production performance index SZi is greater than 1, it is marked as a low-performance index; An efficient production department identification is added to the production department corresponding to the production performance indicator marked with a high-performance indicator, and an inefficient production department identification is added to the production department corresponding to the production performance indicator marked with a performance indicator.

5. A carbon emission management method applicable to distributed energy according to claim 4, characterized in that: The method for extracting process features of process information is: Obtain the process steps in the same production process in the process information, divide the production process into several process links according to the process steps, and use the estimated capacity calculation formula The estimated capacity HYj of the process link is calculated; ZSj is the number of online equipment in the production process link, ZRj is the number of online employees, ZGj is the online working hours, αj is the processing difficulty coefficient in the process link, S t is the unit processing time; j is the process link number, j is a positive integer, j∈[1,N], N is the total number of process links; Analysis formula through links The capacity analysis value FXj of the process link is calculated, the maximum value of the capacity analysis values ​​FXj corresponding to several process links in the same production process is obtained, and the corresponding process link is marked as the target process link.

6. A carbon emission management method applicable to distributed energy according to claim 5, characterized in that: The first proportional parameter of the production process is obtained by calculating the ratio of the number of online devices ZSj in the target process link to the number of required devices XSj, and the second proportional parameter of the production process is obtained by calculating the ratio of the number of online employees ZRj in the target process link to the number of required employees XRj; The mean values ​​of several first proportion parameters and second proportion parameters of different production processes in the same process information are calculated respectively, and the mean calculation result of the first proportion parameters is used as the first feature P of the process information, and the mean calculation result of the second proportion parameters is used as the second feature Q of the process information. The first feature P and the second feature Q are combined to obtain the process feature {P, Q} of the process information.

7. A carbon emission management method applicable to distributed energy according to claim 6, characterized in that: The process characteristics identified with efficient production departments are marked as reference characteristics CK{P1, Q1}, and the process characteristics identified with inefficient production departments are marked as adjustment characteristics TZ{P2, Q2}; The method to obtain the difference characteristics between different process characteristics is: The reference feature CK{P1, Q1} and the adjustment feature TZ{P2, Q2} are calculated by difference to obtain the difference feature CY{P3, Q3}, wherein P3 is calculated by the first difference formula P3=P1-P2-Px, and Px is the first difference threshold; Q3 is calculated by the second difference formula Q3=Q1-Q2-Qx, and Qx is the second difference threshold; Generate a management model based on the difference characteristics CY{P3, Q3}.

8. A carbon emission management method applicable to distributed energy according to claim 7, characterized in that: The expression of the management model is: Gb is the management number; If the management number Gb is 1, the online equipment and the number of online employees of the department marked as having inefficient production are managed simultaneously; If the management number Gb is 2, the online equipment of the department marked with inefficient production is managed; If the management number Gb is 3, the number of online employees in the department marked as having inefficient production will be managed; If the management number Gb is 4, the production process of the department marked as having inefficient production is managed.

9. The carbon emission management method applicable to distributed energy according to claim 1, characterized in that: Also includes: Obtain the application information of the enterprise's distributed energy, and build an energy level association diagram of the distributed energy based on the application information; Construct an energy management diagram based on the enterprise’s distributed energy monitoring data and energy level association diagram; Obtain the energy usage information of each production process in each production task of each production department of the enterprise, and based on the obtained energy usage information, construct an energy loss correspondence table of each production process in each production task of each production department; Based on the current production operation status of each production workshop of the enterprise, a production thread simulation diagram guided by the timeline is constructed; Generate annotation data based on the simulated output data of the production thread simulation diagram and the energy use data determined by querying the energy loss corresponding table and annotate it to the energy management diagram to form a visual energy management diagram; Convert the energy usage data in the visual energy management diagram into carbon emission data to form a visual carbon emission management diagram; Analyze the energy level correlation diagram to determine the energy level correlation relationship and correlation ratio; Analyze the labeled data in the visual energy management diagram to determine the energy demand; Based on the energy demand situation, energy level correlation and correlation ratio, determine the demand and use of the dominant energy of distributed energy; Based on the energy usage data in the energy management diagram, determine the actual usage of the dominant energy of the distributed energy; Based on the demand usage and actual usage, the energy utilization of the dominant energy is calculated; the energy utilization includes: the utilization rate of each dominant energy and the total utilization score; the calculation formula of the total utilization score is as follows: In the formula, ZP represents the total score; P i is the utilization rate of the i-th dominant energy, M Si is the actual usage of the i-th dominant energy; M Hi is the demand for the i-th dominant energy; n represents the total number of dominant energy items; α i is the preset weight coefficient corresponding to the ith dominant energy source; C i is the utilization rate and score conversion coefficient of the preset i-th dominant energy source; Based on the demand and usage of the dominant energy, actual usage, and energy utilization, a display dashboard is generated and displayed in a floating manner at a preset position of the visual carbon emission management diagram; Among them, based on the energy demand situation, energy level correlation relationship and correlation ratio, the demand and use of the dominant energy of distributed energy is determined, including: Extract the energy with energy level correlation in the energy demand situation as the grouped energy to be analyzed. According to the demand and correlation ratio of the lower-level energy in the grouped energy to be analyzed, the demand of the upper-level energy is derived; Statistics are collected on the demand for superior energy and the demand for energy not included in the grouped energy to be analyzed, and the demand and usage of the dominant energy of distributed energy is generated.

10. The carbon emission management method applicable to distributed energy according to claim 1, characterized in that: Also includes: Parse the simulation output data of the production thread simulation diagram, query the energy loss correspondence table to determine the energy usage data, and obtain the energy demand forecast data; Determine the demand forecast data of the dominant energy of distributed energy based on the energy demand forecast data, energy level correlation relationship and correlation ratio; Generate energy control plans based on the demand forecast data of the dominant energy of distributed energy and the actual current energy usage, and adjust the energy control plans according to the historical records of energy utilization; Among them, the adjustment steps for the energy regulation plan are as follows: The historical records are sorted in ascending order according to the time difference from the current time, and the energy utilization rate in the historical records with a preset number of digits before the sorting is extracted to calculate the average value; The volatility adjustment value is determined by comprehensively analyzing all historical records. The calculation formula of the volatility adjustment value is as follows: Where B represents the fluctuation adjustment value, b0 is the pre-configured initial value; μ is the pre-configured fine-tuning amplitude; N1 is the number of times in the historical records that the utilization rate is greater than or equal to the estimated utilization rate corresponding to the control value; N2 is the number of times in the historical records that the utilization rate is less than the estimated utilization rate corresponding to the control value; b min , b max are pre-configured lower and upper limits respectively; Based on the average value, fluctuation adjustment value and the scheme value in the energy control scheme, the control value is calculated. The calculation formula is as follows: In the formula, T represents the control value; F is the solution value; J is the average value.

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