Real-time carbon checking method based on metering support

Abstract

The invention discloses a real-time carbon checking method based on metering support, relates to the technical field of real-time carbon checking, and solves the technical problems that personalized checking time arrangement is neglected according to the specific condition of an enterprise and carbon emission data of the enterprise is difficult to monitor and check in real time in carbon checking. According to the method, the time period and the department area of the enterprise are individually planned, the target data are analyzed to obtain the indirect carbon emission, the direct carbon emission and the indirect carbon emission are integrated into the total carbon emission, and the total characteristic carbon emission of each department in the current time period is obtained based on the total historical carbon emission; the total carbon emission amount of the department in the current time period is extracted, data verification is conducted on the total carbon emission amount based on the characteristic total carbon emission amount, an alarm instruction is sent out, and early warning information is sent out based on the alarm instruction; according to the invention, the intelligent level of enterprise carbon emission management and the real-time check level of carbon emission can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent environmental protection, and relates to real-time carbon verification technology, specifically a real-time carbon verification method based on metering support. Background Art

[0002] As the global climate change problem becomes increasingly serious, countries are actively seeking ways to reduce greenhouse gas emissions. As one of the world's largest carbon emitters, China bears the important responsibility of reducing emissions, which has also given rise to the demand for carbon verification methods. At the same time, with the establishment and improvement of the carbon emission trading market, the verification of carbon emission data has become the basis for market operation and an important link to ensure market fairness, transparency and effectiveness. Carbon emission verification is a complex task that requires comprehensive consideration of various factors, including emission sources, emissions, emission factors, etc. Traditional carbon emission verification methods often require a lot of manpower and time, and the credibility of the verification results is also affected to a certain extent.

[0003] At present, most carbon emission verification methods are usually carried out after the fact, relying on regular manual reports and statistical data. This method is not only time-consuming and inefficient, but also difficult to conduct real-time verification of corporate carbon emissions, and it is difficult to detect and correct emission anomalies in a timely manner; at the same time, in carbon verification, the differentiated and personalized verification time arrangements based on the specific circumstances of the enterprise are neglected, and the establishment of a carbon verification method suitable for each enterprise to improve the accuracy of the verification data is neglected.

[0004] Therefore, the present invention discloses a real-time carbon verification method based on metrology support to solve the above technical problems. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a real-time carbon verification method based on metering support, which is used to solve the technical problems of ignoring the differentiated and personalized verification time arrangements according to the specific circumstances of the enterprise in carbon verification, and the difficulty in real-time monitoring and verification of the enterprise's carbon emission data. The present invention analyzes the target data through personalized planning of the enterprise's time period and department area, combines the direct carbon emissions and the indirect carbon emissions into the total carbon emissions, and obtains the characteristic total carbon emissions of each department in the current time period based on the historical total carbon emissions; extracts the total carbon emissions of the department in the current time period, performs data verification on the total carbon emissions based on the characteristic total carbon emissions and issues an alarm instruction, and issues early warning information based on the alarm instruction to solve the above problems.

[0006] To achieve the above objectives, the first aspect of the present invention provides a real-time carbon verification method based on metrology support, comprising:

[0007] Plan time periods and departmental areas, and obtain basic data based on the time periods and departmental areas; basic data include direct carbon emissions and target data, and target data include electricity consumption, heating volume, and vehicle mileage;

[0008] Analyze the target data to obtain indirect carbon emissions, combine direct carbon emissions and indirect carbon emissions into total carbon emissions, and obtain the characteristic total carbon emissions of each department in the current time period based on the historical total carbon emissions;

[0009] Extract the total carbon emissions of the department in the current time period, perform data verification on the total carbon emissions based on the characteristic total carbon emissions and issue an alarm instruction, and issue a warning message based on the alarm instruction; wherein the alarm instruction includes instruction one, instruction two and instruction three.

[0010] Preferably, the planned time period and department area include:

[0011] A1: Get the company's work schedule and determine whether the current day is a workday. If yes, jump to A2. If no, divide the current day into time periods based on fixed durations and jump to A4. The fixed durations are set manually.

[0012] A2: Extract the non-working time of the current enterprise on working days, integrate the continuous non-working time into a non-working time period, extract the non-working time periods one by one, and determine whether the extracted non-working time periods can be divided into several complete time periods based on a fixed duration; if yes, divide the extracted non-working time periods into several time periods based on a fixed duration; if no, extract the duration NC of the non-working time period and the fixed duration GC, and then calculate the duration NC based on the formula A first division number HL1 is obtained, and the extracted non-working time period is divided into a plurality of time periods based on the first division number HL1; wherein, is the rounding symbol;

[0013] A3: Multiply the fixed duration GC by the proportional adjustment coefficient α to obtain the dynamic duration DC, integrate the continuous working time into a working time period, extract the working time periods one by one, and determine whether the extracted working time period can be divided into several complete time periods based on the dynamic duration DC; if yes, divide the extracted working time period into several time periods based on the dynamic duration DC and jump to A4; if no, extract the duration ZC of the working time period and the dynamic duration DC, and based on the formula A second division number HL2 is obtained, and the extracted non-working time period is divided into a plurality of time periods based on the second division number HL2, and the process jumps to A4; wherein α is a proportional adjustment coefficient, and the value range of α is (0,1];

[0014] A4: Obtain the production area and activity area of ​​the current enterprise, and divide the production area and activity area into departmental areas of each department by manual demarcation.

[0015] Preferably, the basic data is obtained based on time periods and departmental areas, including:

[0016] It is used to measure the concentration of carbon dioxide and the exhaust flow rate in each time period through a high-precision carbon dioxide concentration sensor and a flow meter installed in a fixed position, and obtain the carbon dioxide emission in each time period according to the product of gas concentration and flow rate;

[0017] The electricity consumption and heating capacity of each department area in each time period are obtained from the database; and the mileage of each car used in each department area in the time period is extracted.

[0018] Preferably, the analyzing the target data to obtain the indirect carbon emissions includes:

[0019] The mileage of each car is extracted, and the mileage of each car is classified by type. The mileage of each type is added to obtain the total mileage LCi of each type. The electricity consumption YD and heating volume GN are extracted, and the indirect carbon emissions JCP are obtained based on the formula JCP=YD×DZ+GN×NZ+∑(LCi×LZi); wherein DZ is the electricity emission factor, NZ is the heating emission factor, i is the type number of the car, and LZi is the mileage emission factor of the corresponding type of car.

[0020] Preferably, the direct carbon emissions and indirect carbon emissions are integrated into the total carbon emissions, including:

[0021] Extract direct carbon emissions ZCP and indirect carbon emissions JCP, add direct carbon emissions ZCP and indirect carbon emissions JCP to obtain total carbon emissions CPT; extract the total duration ZC of the current time period, and obtain the total carbon emissions per unit time DSC based on the formula DSC=CPT / ZC; determine whether the total carbon emissions per unit time DSC exceeds the unit carbon emission threshold; if yes, issue an over-limit information for the current time period; if no, do nothing; wherein the unit carbon emission threshold is obtained through experience.

[0022] Preferably, the method of obtaining the characteristic total carbon emissions of each department in the current time period based on the total historical carbon emissions includes:

[0023] Obtain the characteristic values ​​of each department in each time period of the day in turn, extract the date type of the current time period, integrate the characteristic values ​​of the first n dates of the same type in the current time period into the D1 group, and integrate the total carbon emissions of the first n dates of the same type in the current time period into the D2 group; extract the time state of the current time period, integrate the unit time characteristic values ​​of the first m time periods of the same state in the current time period into the D3 group, and integrate the total carbon emissions per unit time DSC of the first m time periods of the same state in the current time period into the D3 group; among them, the date type includes working days and non-working days, and the time state includes working time and non-working time;

[0024] Obtain the standard value of each group, and obtain the characteristic total carbon emissions TCZ of each department in the current time period based on the formula TCZ=DTZ×(β1×BZ1 / BZ2+β2×BZ3 / BZ4); wherein DTZ is the characteristic value of the current time period; β1 and β2 are proportional adjustment coefficients, and the value ranges of β1 and β2 are both [0,1], and β1+β2=1; BZ1 is the standard value of group D1, BZ2 is the standard value of group D2, BZ3 is the standard value of group D3, and BZ4 is the standard value of group D4.

[0025] Preferably, the step of obtaining the characteristic values ​​of each department in each time period of the day includes:

[0026] Extract each department in turn, divide the total carbon emissions of each department into several emission groups according to the time period, obtain the variance of the data in each emission group, and judge in turn whether the variance of each emission group is less than the corresponding variance judgment threshold; if yes, the total carbon emissions of the emission group will be retained; if not, remove the total carbon emissions with the largest difference between the mode of the total carbon emissions in the emission group, and re-judge the variance until the variance of the emission group is less than the corresponding variance judgment threshold, and retain the remaining total carbon emissions of the emission group; wherein the variance judgment threshold is obtained through experience;

[0027] The total carbon emissions retained by each emission group are averaged to obtain the characteristic value of the corresponding time period.

[0028] Preferably, obtaining the standard value of each group includes:

[0029] The maximum eigenvalue ZD1, percentile BS1 and average eigenvalue PZ1 of group D1 are extracted, and the standard value BZ1 of group D1 is obtained based on the formula BZ1=(δ1×ZD1+δ2×BS1+PZ1) / 2; wherein δ1 and δ2 are both proportional adjustment coefficients greater than 0, and δ1+δ2=1, δ1<δ2; the percentile of the percentile is obtained by manual setting;

[0030] The maximum total carbon emission ZD2, percentile BS2 and average total carbon emission PZ2 of group D2 are extracted, and the standard value BZ2 of group D2 is obtained based on the formula BZ2 = (δ1 × ZD2 + δ2 × BS2 + PZ2) / 2;

[0031] The maximum unit time characteristic value ZD3, percentile BS3 and average unit time characteristic value PZ3 of group D3 are extracted, and the standard value BZ3 of group D3 is obtained based on the formula BZ3=(μ1×ZD3+μ2×BS3+PZ3) / 2; wherein μ1 and μ2 are both proportional adjustment coefficients greater than 0, and μ1+μ2=1, μ1<μ2;

[0032] The maximum total carbon emission per unit time ZD4, percentile BS4 and average total carbon emission per unit time PZ4 of group D4 are extracted, and the standard value BZ4 of group D4 is obtained based on the formula BZ4=(μ1×ZD4+μ2×BS4+PZ4) / 2.

[0033] Preferably, the data verification of the total carbon emissions based on the characteristic total carbon emissions and issuing an alarm instruction include:

[0034] E1: Obtain the characteristic total carbon emissions TCZ and total carbon emissions CPT of the current time period, and determine whether the characteristic total carbon emissions TCZ is greater than the total carbon emissions CPT; if yes, obtain the verification anomaly factor YCZ based on the formula YCZ=exp(-σ1×|(TCZ-CPT) / CPT|), and jump to E2; if no, obtain the verification anomaly factor YCZ based on the formula YCZ=exp(-σ2×|(TCZ-CPT) / CPT|), and jump to E3; where σ1 and σ2 are both amplitude adjustment coefficients greater than 0, and σ1>σ2;

[0035] E2: extract the verification abnormality factor YCZ, and determine whether the verification abnormality factor YCZ is less than the definition threshold 1; if yes, issue instruction 1; if no, issue instruction 2; wherein both the definition threshold 1 and the definition threshold 2 are obtained through experience;

[0036] E3: Extract the verification abnormality factor YCZ, and determine whether the verification abnormality factor YCZ is less than the defined threshold value 2; if yes, issue instruction 3; if no, issue instruction 2.

[0037] Preferably, the issuing of warning information based on the alarm instruction includes:

[0038] H1: Extract the operation instruction and determine whether the extracted operation instruction is instruction 1; if yes, issue a warning message that the characteristic total carbon emission TCZ is much greater than the total carbon emission CPT, and perform subtraction calculation on the characteristic total carbon emission TCZ and the total carbon emission CPT to obtain the error value; if no, jump to H2;

[0039] H2: Determine whether the extracted operation instruction is instruction 2; if yes, do not perform the operation; if no, issue a warning message that the characteristic total carbon emissions TCZ is far less than the total carbon emissions CPT, and subtract the characteristic total carbon emissions TCZ from the total carbon emissions CPT to obtain the error value.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] 1. The present invention analyzes the target data to obtain indirect carbon emissions through personalized planning of the time periods and department areas of the enterprise, integrates the direct carbon emissions and indirect carbon emissions into the total carbon emissions, and obtains the characteristic total carbon emissions of each department in the current time period based on the historical total carbon emissions; extracts the total carbon emissions of the department in the current time period, performs data verification on the total carbon emissions based on the characteristic total carbon emissions and issues an alarm instruction, and issues early warning information based on the alarm instruction, thereby solving the technical problems of ignoring the differentiated and personalized verification time arrangements according to the specific circumstances of the enterprise in carbon verification, and being difficult to monitor and verify the carbon emission data of the enterprise in real time; the present invention can improve the intelligence level of enterprise carbon emission management and the real-time verification level of carbon emissions.

[0042] 2. The present invention adopts a time-sharing strategy, dividing a day into multiple time intervals, and finely dividing these intervals during working hours, so as to implement more frequent data verification and in-depth analysis during the enterprise's emission peak period, so as to timely identify emission anomalies and take rapid countermeasures, greatly improving the real-time monitoring and response efficiency of the system; during non-working hours, a fixed-duration time division method is adopted, which helps to reduce the consumption of system resources and optimize computing efficiency.

[0043] 3. The present invention adopts a method of comparative analysis of characteristic values ​​and actual values ​​when determining the total characteristic carbon emissions in the current time period. Specifically, the characteristic value and actual value of a specific time period are first calculated, and then the two are proportionally calculated to evaluate the changing trend of the characteristic value relative to the actual value. Based on this changing trend, the total characteristic carbon emissions of the current time period are further calculated. By performing proportional calculations on the characteristic value and the actual value of a specific time period, the actual situation of the total characteristic carbon emissions can be more accurately reflected, effectively reducing calculation errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 It is a schematic diagram of the operation steps of the present invention;

[0046] Figure 2 A schematic diagram of the operation steps for planning time periods and department areas of the present invention;

[0047] Figure 3 The figure is a schematic diagram of the operation steps of performing data verification and issuing an alarm instruction in the present invention. DETAILED DESCRIPTION

[0048] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] See also Figure 1 The first aspect of the present invention provides a real-time carbon verification method based on metrology support, comprising:

[0050] Plan time periods and departmental areas, and obtain basic data based on the time periods and departmental areas; basic data include direct carbon emissions and target data, and target data include electricity consumption, heating volume, and vehicle mileage;

[0051] Analyze the target data to obtain indirect carbon emissions, combine direct carbon emissions and indirect carbon emissions into total carbon emissions, and obtain the characteristic total carbon emissions of each department in the current time period based on the historical total carbon emissions;

[0052] Extract the total carbon emissions of the department in the current time period, perform data verification on the total carbon emissions based on the characteristic total carbon emissions and issue an alarm instruction, and issue a warning message based on the alarm instruction; wherein the alarm instruction includes instruction one, instruction two and instruction three.

[0053] See also Figure 2 , the planning time periods and departmental areas in this application include:

[0054] A1: Get the company's work schedule and determine whether the current day is a workday. If yes, jump to A2. If no, divide the current day into time periods based on fixed durations and jump to A4. The fixed durations are set manually.

[0055] A2: Extract the non-working time of the current enterprise on working days, integrate the continuous non-working time into a non-working time period, extract the non-working time periods one by one, and determine whether the extracted non-working time periods can be divided into several complete time periods based on a fixed duration; if yes, divide the extracted non-working time periods into several time periods based on a fixed duration; if no, extract the duration NC of the non-working time period and the fixed duration GC, and then calculate the duration NC based on the formula A first division number HL1 is obtained, and the extracted non-working time period is divided into a plurality of time periods based on the first division number HL1; wherein, is the rounding symbol;

[0056] A3: Multiply the fixed duration GC by the proportional adjustment coefficient α to obtain the dynamic duration DC, integrate the continuous working time into a working time period, extract the working time periods one by one, and determine whether the extracted working time period can be divided into several complete time periods based on the dynamic duration DC; if yes, divide the extracted working time period into several time periods based on the dynamic duration DC and jump to A4; if no, extract the duration ZC of the working time period and the dynamic duration DC, and based on the formula A second division number HL2 is obtained, and the extracted non-working time period is divided into a plurality of time periods based on the second division number HL2, and the process jumps to A4; wherein α is a proportional adjustment coefficient, and the value range of α is (0,1];

[0057] A4: Obtain the production area and activity area of ​​the current enterprise, and divide the production area and activity area into departmental areas of each department by manual demarcation.

[0058] It is worth noting that when the present invention conducts data analysis on the carbon emissions of an enterprise, it first plans a day into several time periods, and divides the time periods more finely during working hours. In this way, high-frequency data verification and data analysis can be performed during the high emission times of the enterprise, and emission anomalies can be discovered in real time and timely measures can be taken, thereby increasing the real-time and responsiveness of the system; fixed-time division during non-working hours can save the system's computing resources.

[0059] It should be noted that the work schedule records the working dates set by the company.

[0060] It should be noted that working days are the working days set by the enterprise.

[0061] It should be noted that the activity area includes each department’s exclusive meeting rooms, exclusive gyms, etc.

[0062] It should be noted that the determination of whether the day is a working day and the division of time periods are performed at 0:00 of the day.

[0063] It should be noted that, since the working hours of an enterprise may be adjusted at any time, the present invention divides the time periods of each day, so as to prevent the time period division from not fitting the production situation of the enterprise due to changes in working hours.

[0064] It should be noted that the division of time periods of the day based on fixed durations can be illustrated by the following examples:

[0065] If in this embodiment, the fixed duration is 30 minutes, then at 0:00 today, the time is planned as: 00:00-00:30, 00:30-01:00, ..., 22:30-23:00, 23:00-23:30, 23:30-00:00;

[0066] If there is a fixed duration that cannot divide a day into several complete time periods, the last incomplete time period in the day is also marked as a time period. For example, if the fixed duration is 50 minutes, today will be planned at 0:00 today as: 00:00-00:50, 00:50-01:40, ..., 21:40-22:30, 2:30-23:20, 23:20-00:00; in which, in this embodiment, the duration of the complete time period is 50 minutes, and the duration of the incomplete time period is 40 minutes.

[0067] It should be noted that, in determining whether the extracted non-working time period can be divided into a number of complete time periods based on a fixed time period, a complete time period refers to a time period whose duration is equal to the fixed time period;

[0068] If yes, the extracted non-working time period is divided into several time periods based on the fixed duration. For example, if the fixed duration is 30 minutes and the extracted non-working time period is 12:00-13:30, the non-working time period can be divided into: 12:00-12:30, 12:30-13:00, and 13:00-13:30;

[0069] No, the extracted non-working time period is divided into several time periods based on the first division quantity HL1. For example, the fixed duration is 25 minutes, and the extracted non-working time period is 12:00-13:30. The first division quantity HL1=4 is obtained, and 12:00-13:30 is evenly divided into 4 time periods, namely 12:00-12:22:30, 12:22:30-12:45, 12:45-13:07:30, and 13:07:30-13:30.

[0070] This application obtains basic data based on time periods and departmental areas, including:

[0071] It is used to measure the concentration of carbon dioxide and the exhaust flow rate in each time period through a high-precision carbon dioxide concentration sensor and a flow meter installed in a fixed position, and obtain the carbon dioxide emission in each time period according to the product of gas concentration and flow rate;

[0072] The electricity consumption and heating capacity of each department area in each time period are obtained from the database; and the mileage of each car used in each department area in the time period is extracted.

[0073] It should be noted that the electricity consumption refers to the total electricity consumption of each department area of ​​the department within a time period, and the heating volume refers to the total heating provided by the heating system to each department area of ​​the department within a time period.

[0074] In this application, the target data is analyzed to obtain indirect carbon emissions, including:

[0075] The mileage of each car is extracted, and the mileage of each car is classified by type. The mileage of each type is added to obtain the total mileage LCi of each type. The electricity consumption YD and heating volume GN are extracted, and the indirect carbon emissions JCP are obtained based on the formula JCP=YD×DZ+GN×NZ+∑(LCi×LZi); wherein DZ is the electricity emission factor, NZ is the heating emission factor, i is the type number of the car, and LZi is the mileage emission factor of the corresponding type of car.

[0076] It should be noted that the mileage of each car is classified according to type, and the mileage of each type is added to obtain the total mileage LCi of each type. It can be illustrated as follows:

[0077] The department area owned by department 1 needs cars 1, 2, 3, 4 and 5 from 14:00 to 14:25, and the mileage of car 1 is 5 km, the mileage of car 2 is 15 km, the mileage of car 3 is 20 km, the mileage of car 4 is 10 km, and the mileage of car 5 is 25 km;

[0078] If car 1 and car 2 are of the same type, and they are type 1; car 3, car 4 and car 5 are of the same type, and they are type 2;

[0079] Therefore, the mileage of each car is added up according to the type to obtain the total mileage LCi of each type:

[0080] Type 1: LC1 = 5 + 15 + 20 = 40 km;

[0081] Type 2: LC2=10+25=35km.

[0082] It should be noted that the cars used in this embodiment are all fuel cars.

[0083] It should be noted that the electricity emission factor is the carbon emission per kilowatt-hour of electricity. In this embodiment, the electricity emission factor is 0.5568 kgCO2 / kWh;

[0084] The heating emission factor is the carbon emissions per kilowatt-hour of heating. In this embodiment, the heating emission factor is 1.62 kgCO2 / kWh;

[0085] The automobile emission factor is the carbon emission per kilometer traveled by different types of automobiles. In this embodiment, the emission factor of type 1 automobile is 0.27 kgCO2 / km, and the emission factor of type 2 automobile is 0.17 kgCO2 / km.

[0086] In this embodiment, if the electricity consumption of department 1 YD = 10 kWh, the heating capacity GN = 20 kWh, the total driving mileage LC1 of type 1 is 40 km, and the total driving mileage LC2 of type 2 is 35 km;

[0087] Therefore, the indirect carbon emissions of department 1 JCP = YD×DZ+GN×NZ+∑(LCi×LZi)=10kWh×0.5568kgCO2 / kWh+20kWh×1.62kgCO2 / kWh+(40km×0.27kgCO2 / km+35km×0.17kgCO2 / km)=54.718kgCO2.

[0088] In this application, direct carbon emissions and indirect carbon emissions are combined into total carbon emissions, including:

[0089] Extract direct carbon emissions ZCP and indirect carbon emissions JCP, add direct carbon emissions ZCP and indirect carbon emissions JCP to get the total carbon emissions CPT; extract the total duration ZC of the current time period, and get the total carbon emissions per unit time DSC based on the formula DSC=CPT / ZC; determine whether the total carbon emissions per unit time DSC exceeds the unit carbon emission threshold; if yes, issue an over-limit information for the current time period; if no, do nothing; the unit carbon emission threshold is obtained through experience.

[0090] It is worth noting that after obtaining the total amount of carbon emissions, the present invention also analyzes the total amount of carbon emissions per unit time in the current time period. This is because the lengths of time periods are different. If abnormal value judgment is made based on the total amount of carbon emissions, it is necessary to set a judgment threshold for time periods of different lengths, which increases the amount of calculation in the system. Therefore, in order to prevent carbon emissions from exceeding the standard within the time period, the present invention analyzes the total amount of carbon emissions per unit time. In this way, only a small number of judgment thresholds need to be set to meet the judgment requirements, thereby increasing the flexibility of the system.

[0091] In this application, the characteristic carbon emissions of each department in the current time period are obtained based on the historical carbon emissions, including:

[0092] Obtain the characteristic values ​​of each department in each time period of the day in turn, extract the date type of the current time period, integrate the characteristic values ​​of the first n dates of the same type in the current time period into the D1 group, and integrate the total carbon emissions of the first n dates of the same type in the current time period into the D2 group; extract the time state of the current time period, integrate the unit time characteristic values ​​of the first m time periods of the same state in the current time period into the D3 group, and integrate the total carbon emissions per unit time DSC of the first m time periods of the same state in the current time period into the D3 group; among them, the date type includes working days and non-working days, and the time state includes working time and non-working time;

[0093] Obtain the standard value of each group, and obtain the characteristic total carbon emissions TCZ of each department in the current time period based on the formula TCZ=DTZ×(β1×BZ1 / BZ2+β2×BZ3 / BZ4); wherein DTZ is the characteristic value of the current time period; β1 and β2 are proportional adjustment coefficients, and the value ranges of β1 and β2 are both [0,1], and β1+β2=1; BZ1 is the standard value of group D1, BZ2 is the standard value of group D2, BZ3 is the standard value of group D3, and BZ4 is the standard value of group D4.

[0094] It is worth noting that the present invention uses a method of comparing characteristic values ​​and actual values ​​when obtaining the characteristic total carbon emissions for the current time period. Specifically, the characteristic value and actual value for a specific time are calculated, and then the ratio of the characteristic value and the actual value for the specific time is calculated. The change of the characteristic value relative to the actual value can be used to obtain the characteristic total carbon emissions for the current time period. By calculating the ratio of the characteristic value and the actual value for a specific time, the actual situation of the characteristic total carbon emissions can be obtained more accurately, reducing errors.

[0095] It is worth noting that in the comparison between characteristic values ​​and actual values, the time periods used include the historical time periods corresponding to the current time period in the historical dates, as well as several time periods before the current time period; by analyzing the corresponding historical time periods in the historical dates, we can get the production habits of the company in the current time period, such as some companies have higher production efficiency in the morning than in the afternoon; by analyzing several time periods before the current time period, we can get the company's recent production situation, such as recently receiving a large order, resulting in high-intensity production in recent days; by analyzing the company's production habits and production situation, we can get the production characteristics of the current time period, which improves the accuracy of the calculated characteristic total carbon emissions results.

[0096] It should be noted that the analysis of the characteristic carbon emissions of each department in the current time period based on the historical total carbon emissions is a separate analysis of each department in turn.

[0097] It should be noted that when extracting the date type of the date in the current time period, the characteristic values ​​of the first n dates of the same type in the current time period are integrated into the D1 group, and the total carbon emissions of the first n dates of the same type in the current time period are integrated into the D2 group. If the current time period is a time period on a working day, the historical data used is the data of the current time period in the historical working days; similarly, if the current time period is a time period on a non-working day, the historical data used is the data of the current time period in the historical non-working days.

[0098] It should be noted that the same-status time period refers to the time period with the same time status as the current time period. An example is: if the time status of the current time period is working time, and the current time period is the second time period of the working time of the day, if m=5, then the first m same-status time periods of the current time period are the first time period of the working time of the day and the last four time periods of the working time of the previous working day.

[0099] It should be noted that the characteristic value per unit time is obtained by dividing the characteristic value of the current time period by the length of the current time period.

[0100] It should be noted that the first n dates of the same type refer to the first n dates of the same type as the current date.

[0101] It should be noted that the characteristic values ​​of the first n dates of the same type in the current time period can be illustrated as follows:

[0102] If in this embodiment n=5, and the current date is December 20, the date type day is a working day, and the current time period is 14:00-14:25; then the characteristic values ​​of the first five dates of the same type in the current time period are: the characteristic value of December 13 at 14:00-14:25, the characteristic value of December 16 at 14:00-14:25, the characteristic value of December 17 at 14:00-14:25, the characteristic value of December 18 at 14:00-14:25, and the characteristic value of December 19 at 14:00-14:25; among which, the values ​​of n and m are only for the convenience of understanding the current step, and in practice the values ​​of n and m will be larger.

[0103] It should be noted that the m time periods with the same status before the current time period can be illustrated as follows:

[0104] If m=5 in this embodiment, and the current date is December 20, the date type day is a working day, and the working hours are 8:30-12:00, 14:00-17:30;

[0105] If the current time period is 14:00-14:20, the first five time periods with the same status can be: December 20, 11:40-12:00, December 20, 11:20-11:40, December 20, 11:00-11:20, December 20, 10:40-11:00, December 20, 10:20-10:40;

[0106] If the current time period is 8:20-8:40, the first five time periods with the same status can be: December 20, 8:00-8:20, December 19, 17:10-17:30, December 19, 16:50-17:10, December 19, 16:30-16:50, December 19, 16:10-16:30, December 19.

[0107] This application obtains the characteristic values ​​of each department at each time period of the day, including:

[0108] Extract each department in turn, divide the total carbon emissions of each department into several emission groups according to the time period, obtain the variance of the data in each emission group, and judge in turn whether the variance of each emission group is less than the corresponding variance judgment threshold; if yes, the total carbon emissions of the emission group will be retained; if not, remove the total carbon emissions with the largest difference between the mode of the total carbon emissions in the emission group, and re-judge the variance until the variance of the emission group is less than the corresponding variance judgment threshold, and retain the remaining total carbon emissions of the emission group; wherein the variance judgment threshold is obtained through experience;

[0109] The total carbon emissions retained by each emission group are averaged to obtain the characteristic value of the corresponding time period.

[0110] It should be noted that when the total carbon emissions of each department are divided into several data groups according to time periods, the time periods of working days and non-working days are divided separately; for example:

[0111] If a time period is 9:00-9:20 and the current day is a working day, the data from the time period 9:00-9:20 in the historical working day will be included in the time period 9:00-9:20 on the current day.

[0112] If a time period is 9:30-10:00 and the current day is a non-working day, then during the division, the data of the time period 9:30-10:00 in the historical non-working day will be included in the time period 9:30-10:00 on the current day.

[0113] The standard values ​​of each group are obtained in this application, including:

[0114] The maximum eigenvalue ZD1, percentile BS1 and average eigenvalue PZ1 of group D1 are extracted, and the standard value BZ1 of group D1 is obtained based on the formula BZ1=(δ1×ZD1+δ2×BS1+PZ1) / 2; wherein δ1 and δ2 are both proportional adjustment coefficients greater than 0, and δ1+δ2=1, δ1<δ2; the percentile of the percentile is obtained by manual setting;

[0115] The maximum total carbon emission ZD2, percentile BS2 and average total carbon emission PZ2 of group D2 are extracted, and the standard value BZ2 of group D2 is obtained based on the formula BZ2 = (δ1 × ZD2 + δ2 × BS2 + PZ2) / 2;

[0116] The maximum unit time characteristic value ZD3, percentile BS3 and average unit time characteristic value PZ3 of group D3 are extracted, and the standard value BZ3 of group D3 is obtained based on the formula BZ3=(μ1×ZD3+μ2×BS3+PZ3) / 2; wherein μ1 and μ2 are both proportional adjustment coefficients greater than 0, and μ1+μ2=1, μ1<μ2;

[0117] The maximum total carbon emission per unit time ZD4, percentile BS4 and average total carbon emission per unit time PZ4 of group D4 are extracted, and the standard value BZ4 of group D4 is obtained based on the formula BZ4=(μ1×ZD4+μ2×BS4+PZ4) / 2.

[0118] It is worth noting that the present invention uses percentiles when calculating standard values. The reason for using percentiles is that: since there may be abnormal values ​​or outliers in the data group, these values ​​may have a greater impact on statistics such as the average. Using percentiles can reduce the interference of these abnormal values ​​and improve the accuracy of system analysis.

[0119] It should be noted that in the present invention, the percentile is the value at a specific percentile in each group. For example, the data of each group are sorted in ascending order. If the set percentile is 60%, then the data at the 60% position of each group is the percentile of the group. If there is no data at the 60% position of the group, the data closest to the 60% position is used as the percentile of the group.

[0120] It should be noted that the average characteristic value PZ1 is the average value of the data in group D1, the average total carbon emissions PZ2 is the average value of the data in group D2, the average unit time characteristic value PZ3 is the average value of the data in group D3, and the average unit time total carbon emissions PZ4 is the average value of the data in group D4.

[0121] See also Figure 3 In this application, the total carbon emissions are verified based on the characteristic total carbon emissions and an alarm instruction is issued, including:

[0122] E1: Obtain the total characteristic carbon emissions TCZ and the total carbon emissions CPT for the current time period, and determine whether the total characteristic carbon emissions TCZ are greater than the total carbon emissions CPT; if so, obtain the verification anomaly factor YCZ based on the formula YCZ = exp(-σ1×|(TCZ - CPT) / CPT|), and jump to E2; if not, obtain the verification anomaly factor YCZ based on the formula YCZ = exp(-σ2×|(TCZ - CPT) / CPT|), and jump to E3; where both σ1 and σ2 are amplitude adjustment coefficients greater than 0, and σ1 > σ2;

[0123] E2: Extract the verification anomaly factor YCZ, and determine whether the verification anomaly factor YCZ is less than the first defined threshold; if so, issue Instruction One; if not, issue Instruction Two; where both the first defined threshold and the second defined threshold are obtained through experience;

[0124] E3: Extract the verification anomaly factor YCZ, and determine whether the verification anomaly factor YCZ is less than the second defined threshold; if so, issue Instruction Three; if not, issue Instruction Two.

[0125] It should be noted that the function curve composed of the formula YCZ = exp(-σ1×|(TCZ - CPT) / CPT|) and the formula YCZ = exp(-σ2×|(TCZ - CPT) / CPT|) is a curve similar to a "human" shape, and the midpoint is the calculated value of |(TCZ - CPT) / CPT|;

[0126] In step E2, it indicates that the point where the current verification anomaly factor YCZ is located is on the right curve of the "human" shape. When the verification anomaly factor YCZ is less than the first defined threshold, it indicates that the total characteristic carbon emissions TCZ for the current time period are much greater than the total carbon emissions CPT, and this may be caused by underreporting, misreporting, or detection equipment failure; when the verification anomaly factor YCZ is not less than the first defined threshold, it indicates that the total characteristic carbon emissions TCZ and the total carbon emissions CPT for the current time period are similar, and the total carbon emissions monitored by the department at this time are normal; where the first defined threshold is at a certain position on the right curve of the "human" shape in the two-dimensional coordinate;

[0127] In step E3, it indicates that the point where the current verification anomaly factor YCZ is located is on the left curve of the "human" shape. When the verification anomaly factor YCZ is less than the second defined threshold, it indicates that the total characteristic carbon emissions TCZ for the current time period are much less than the total carbon emissions CPT, and this may be caused by misreporting or detection equipment failure; when the verification anomaly factor YCZ is not less than the second defined threshold, it indicates that the total characteristic carbon emissions TCZ and the total carbon emissions CPT for the current time period are similar, and the total carbon emissions monitored by the department at this time are normal; where the second defined threshold is at a certain position on the left curve of the "human" shape in the two-dimensional coordinate.

[0128] In this application, warning information is issued based on the alarm instruction, including:

[0129] H1: Extract the operation instruction and determine whether the extracted operation instruction is instruction 1; if yes, issue a warning message that the characteristic total carbon emission TCZ is much greater than the total carbon emission CPT, and perform subtraction calculation on the characteristic total carbon emission TCZ and the total carbon emission CPT to obtain the error value; if no, jump to H2;

[0130] H2: Determine whether the extracted operation instruction is instruction 2; if yes, do not perform the operation; if no, issue a warning message that the characteristic total carbon emissions TCZ is far less than the total carbon emissions CPT, and subtract the characteristic total carbon emissions TCZ from the total carbon emissions CPT to obtain the error value.

[0131] It should be noted that the error value obtained by subtracting the characteristic total carbon emissions TCZ from the total carbon emissions CPT is specifically: the error value is obtained by subtracting the total carbon emissions CPT from the characteristic total carbon emissions TCZ.

[0132] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0133] Working principle of the present invention:

[0134] The present invention first plans time periods and department areas, and obtains basic data based on the time periods and department areas; analyzes the target data to obtain indirect carbon emissions, and combines direct carbon emissions and indirect carbon emissions into total carbon emissions; then obtains the characteristic total carbon emissions of each department in the current time period based on the historical total carbon emissions; this step calculates the ratio of the characteristic value and the actual value at a specific time, so as to more accurately obtain the actual situation of the characteristic total carbon emissions and reduce errors; finally, extracts the total carbon emissions of the department in the current time period, performs data verification on the total carbon emissions based on the characteristic total carbon emissions, issues an alarm instruction, and issues a warning message based on the alarm instruction.

[0135] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A real-time carbon verification method based on metrology support, characterized in that: Plan time periods and departmental areas, and obtain basic data based on the time periods and departmental areas; basic data include direct carbon emissions and target data, and target data include electricity consumption, heating volume, and vehicle mileage; Analyze the target data to obtain indirect carbon emissions, combine direct carbon emissions and indirect carbon emissions into total carbon emissions, and obtain the characteristic total carbon emissions of each department in the current time period based on the historical total carbon emissions; Extract the total carbon emissions of the department in the current time period, perform data verification on the total carbon emissions based on the characteristic total carbon emissions and issue an alarm instruction, and issue a warning message based on the alarm instruction; wherein the alarm instruction includes instruction one, instruction two and instruction three.

2. A real-time carbon verification method based on metrology support according to claim 1, characterized in that: The planning time period and departmental areas include: A1: Get the company's work schedule and determine whether the current day is a workday. If yes, jump to A2. If no, divide the current day into time periods based on fixed durations and jump to A4. A2: Extract the non-working time of the current enterprise on working days, integrate the continuous non-working time into a non-working time period, extract the non-working time periods one by one, and determine whether the extracted non-working time periods can be divided into several complete time periods based on a fixed duration; if yes, divide the extracted non-working time periods into several time periods based on a fixed duration; if no, extract the duration NC of the non-working time period and the fixed duration GC, and then calculate the duration NC based on the formula A first division number HL1 is obtained, and the extracted non-working time period is divided into a plurality of time periods based on the first division number HL1; wherein, is the rounding symbol; A3: Multiply the fixed duration GC by the proportional adjustment coefficient α to obtain the dynamic duration DC, integrate the continuous working time into a working time period, extract the working time periods one by one, and determine whether the extracted working time period can be divided into several complete time periods based on the dynamic duration DC; if yes, divide the extracted working time period into several time periods based on the dynamic duration DC and jump to A4; if no, extract the duration ZC of the working time period and the dynamic duration DC, and based on the formula A second division number HL2 is obtained, and the extracted non-working time period is divided into a plurality of time periods based on the second division number HL2, and the process jumps to A4; wherein α is a proportional adjustment coefficient, and the value range of α is (0,1]; A4: Obtain the production area and activity area of ​​the current enterprise, and divide the production area and activity area into departmental areas of each department by manual demarcation.

3. A real-time carbon verification method based on metrology support according to claim 1, characterized in that: The basic data is obtained based on time period and department area, including: It is used to measure the concentration of carbon dioxide and the exhaust flow rate in each time period through a high-precision carbon dioxide concentration sensor and a flow meter installed in a fixed position, and obtain the carbon dioxide emission in each time period according to the product of gas concentration and flow rate; The electricity consumption and heating capacity of each department area in each time period are obtained from the database; and the mileage of each car used in each department area in the time period is extracted.

4. The real-time carbon verification method based on metrology support according to claim 1 is characterized in that: The indirect carbon emissions obtained by analyzing the target data include: The mileage of each car is extracted, and the mileage of each car is classified by type. The mileage of each type is added to obtain the total mileage LCi of each type. The electricity consumption YD and heating volume GN are extracted, and the indirect carbon emissions JCP are obtained based on the formula JCP=YD×DZ+GN×NZ+∑(LCi×LZi); wherein DZ is the electricity emission factor, NZ is the heating emission factor, i is the type number of the car, and LZi is the mileage emission factor of the corresponding type of car.

5. The real-time carbon verification method based on metrology support according to claim 1 is characterized in that: The above-mentioned direct carbon emissions and indirect carbon emissions are combined into total carbon emissions, including: Extract direct carbon emissions ZCP and indirect carbon emissions JCP, add direct carbon emissions ZCP and indirect carbon emissions JCP to obtain total carbon emissions CPT; extract the total duration ZC of the current time period, and obtain the total carbon emissions per unit time DSC based on the formula DSC=CPT / ZC; determine whether the total carbon emissions per unit time DSC exceeds the unit carbon emissions threshold; if yes, issue an over-limit information for the current time period; if no, do nothing.

6. A real-time carbon verification method based on metrology support according to claim 1, characterized in that: The method of obtaining the characteristic total carbon emissions of each department in the current time period based on the total historical carbon emissions includes: Obtain the characteristic values ​​of each department in each time period of the day in turn, extract the date type of the current time period, integrate the characteristic values ​​of the first n dates of the same type in the current time period into the D1 group, and integrate the total carbon emissions of the first n dates of the same type in the current time period into the D2 group; extract the time state of the current time period, integrate the unit time characteristic values ​​of the first m time periods of the same state in the current time period into the D3 group, and integrate the total carbon emissions per unit time DSC of the first m time periods of the same state in the current time period into the D3 group; among them, the date type includes working days and non-working days, and the time state includes working time and non-working time; Obtain the standard value of each group, and obtain the characteristic total carbon emissions TCZ of each department in the current time period based on the formula TCZ=DTZ×(β1×BZ1 / BZ2+β2×BZ3 / BZ4); wherein DTZ is the characteristic value of the current time period; β1 and β2 are proportional adjustment coefficients, and the value ranges of β1 and β2 are both [0,1], and β1+β2=1; BZ1 is the standard value of group D1, BZ2 is the standard value of group D2, BZ3 is the standard value of group D3, and BZ4 is the standard value of group D4.

7. A real-time carbon verification method based on metrology support according to claim 6, characterized in that: The acquisition of characteristic values ​​of each department in each time period of the day includes: Extract each department in turn, divide the total carbon emissions of each department into several emission groups according to the time period, obtain the variance of the data in each emission group, and judge whether the variance of each emission group is less than the corresponding variance judgment threshold in turn; if yes, the total carbon emissions of the emission group will be retained; if not, remove the total carbon emissions with the largest difference between the mode of the total carbon emissions in the emission group, and re-judge the variance until the variance of the emission group is less than the corresponding variance judgment threshold, and then retain the remaining total carbon emissions of the emission group; The total carbon emissions retained by each emission group are averaged to obtain the characteristic value of the corresponding time period.

8. A real-time carbon verification method based on metrology support according to claim 7, characterized in that: The step of obtaining the standard value of each group includes: The maximum eigenvalue ZD1, percentile BS1 and average eigenvalue PZ1 of group D1 are extracted, and the standard value BZ1 of group D1 is obtained based on the formula BZ1=(δ1×ZD1+δ2×BS1+PZ1) / 2; wherein δ1 and δ2 are both proportional adjustment coefficients greater than 0, and δ1+δ2=1, δ1<δ2; The maximum total carbon emission ZD2, percentile BS2 and average total carbon emission PZ2 of group D2 are extracted, and the standard value BZ2 of group D2 is obtained based on the formula BZ2 = (δ1 × ZD2 + δ2 × BS2 + PZ2) / 2; The maximum unit time characteristic value ZD3, percentile BS3 and average unit time characteristic value PZ3 of group D3 are extracted, and the standard value BZ3 of group D3 is obtained based on the formula BZ3=(μ1×ZD3+μ2×BS3+PZ3) / 2; wherein μ1 and μ2 are both proportional adjustment coefficients greater than 0, and μ1+μ2=1, μ1<μ2; The maximum total carbon emission per unit time ZD4, percentile BS4 and average total carbon emission per unit time PZ4 of group D4 are extracted, and the standard value BZ4 of group D4 is obtained based on the formula BZ4=(μ1×ZD4+μ2×BS4+PZ4) / 2.

9. A real-time carbon verification method based on metrology support according to claim 6, characterized in that: The method of verifying the total carbon emissions based on the characteristic total carbon emissions and issuing an alarm instruction includes: E1: Obtain the characteristic total carbon emissions TCZ and total carbon emissions CPT of the current time period, and determine whether the characteristic total carbon emissions TCZ is greater than the total carbon emissions CPT; if yes, obtain the verification anomaly factor YCZ based on the formula YCZ=exp(-σ1×|(TCZ-CPT) / CPT|), and jump to E2; if no, obtain the verification anomaly factor YCZ based on the formula YCZ=exp(-σ2×|(TCZ-CPT) / CPT|), and jump to E3; where σ1 and σ2 are both amplitude adjustment coefficients greater than 0, and σ1>σ2; E2: extract the verification abnormality factor YCZ, and determine whether the verification abnormality factor YCZ is less than the defined threshold value 1; if yes, issue instruction 1; if no, issue instruction 2; E3: Extract the verification abnormality factor YCZ, and determine whether the verification abnormality factor YCZ is less than the defined threshold value 2; if yes, issue instruction 3; if no, issue instruction 2.

10. A real-time carbon verification method based on metrology support according to claim 9, characterized in that: The issuing of warning information based on the alarm instruction includes: H1: Extract the operation instruction and determine whether the extracted operation instruction is instruction 1; if yes, issue a warning message that the characteristic total carbon emission TCZ is much greater than the total carbon emission CPT, and perform subtraction calculation on the characteristic total carbon emission TCZ and the total carbon emission CPT to obtain the error value; if no, jump to H2; H2: Determine whether the extracted operation instruction is instruction 2; if yes, do not perform the operation; if no, issue a warning message that the characteristic total carbon emissions TCZ is far less than the total carbon emissions CPT, and subtract the characteristic total carbon emissions TCZ from the total carbon emissions CPT to obtain the error value.

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