Carbon emission data processing method and device, electronic equipment and storage medium

Abstract

The invention provides a carbon emission data processing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a data source of a target unit according to the identification of the target unit inputted by a user, the data source comprising the power supply amount of the target unit and the heat supply amount of the target unit; obtaining a carbon emission data prediction time period input by a user; and determining carbon emission prediction data of the target unit in the carbon emission data prediction time period according to the data source of the target unit, preset carbon emission data reference parameter information and the carbon emission data prediction time period. The determined carbon emission data of the target unit in the carbon emission data prediction period is more accurate, manual calculation in the prior art is avoided, and the efficiency of carbon emission data calculation is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a carbon emission data processing method, device, electronic device and storage medium. Background Art

[0002] With rapid economic development, energy consumption is also increasing year by year. Due to the irrational use of resources, environmental problems are becoming increasingly serious. The most prominent issue is global warming, which is undoubtedly caused by the large-scale emission of greenhouse gases, of which carbon dioxide is the largest contributor. Therefore, it is imperative for power companies to improve their carbon emission management capabilities.

[0003] In the existing technology, the accounting of carbon emission-related data mainly relies on manual calculations, and the database of carbon emission-related data in power companies is not fully established, resulting in low efficiency and easy errors in the calculation of carbon emission-related data by power companies. Summary of the Invention

[0004] The purpose of this application is to address the deficiencies in the above-mentioned prior art and provide a carbon emission data processing method, device, electronic device and storage medium to improve the efficiency of carbon emission data prediction.

[0005] To achieve the above objectives, the technical solutions adopted in the embodiments of the present application are as follows:

[0006] In a first aspect, an embodiment of the present application provides a method for processing carbon emission data, the method comprising:

[0007] According to the identifier of the target unit input by the user, a data source of the target unit is obtained, wherein the data source includes the power supply and the heat supply of the target unit;

[0008] Obtain the carbon emission data forecast period input by the user;

[0009] The carbon emission prediction data of the target unit in the carbon emission data prediction period is determined according to the data source of the target unit, the preset carbon emission data baseline parameter information and the carbon emission data prediction period.

[0010] Optionally, before obtaining the data source of the target unit according to the identifier of the target unit input by the user, the method includes:

[0011] Based on the parameter values ​​of each benchmark parameter entered by the user on the parameter setting page, carbon emission data benchmark parameter information is generated, and the carbon emission data benchmark parameter information includes: the identification of the target unit, the power supply benchmark value of the target unit, the heating benchmark value of the target unit, the unit type of the target unit, the unit type of the target unit, the target unit cooling method, and the target unit cooling method correction coefficient.

[0012] Optionally, determining the predicted carbon emission data of the target unit in the carbon emission data prediction period according to the data source of the target unit, preset carbon emission data baseline parameter information, and the carbon emission data prediction period includes:

[0013] Determine the heating carbon emission data prediction result and the power supply carbon emission data prediction result respectively according to the data source of the target unit, the preset carbon emission data benchmark parameter information and the carbon emission data prediction period;

[0014] The carbon emission prediction data of the target unit in the carbon emission data prediction period is determined according to the heating carbon emission data prediction result and the power supply carbon emission data prediction result.

[0015] Optionally, determining the heating carbon emission data prediction result and the power supply carbon emission data prediction result respectively according to the data source of the target unit, the preset carbon emission data benchmark parameter information, and the carbon emission data prediction period includes:

[0016] Determining a value of a load factor correction factor of the target unit according to a value of a load factor in a data source of the target unit;

[0017] Determining a heating carbon emission data prediction result based on the heating capacity of the target unit and the heating reference value in the carbon emission data reference parameter information;

[0018] The power supply carbon emission data prediction result is determined based on the power supply reference value and the target unit cooling mode correction coefficient in the carbon emission data reference parameter information, as well as the power supply of the target unit, the target unit heat supply correction coefficient and the target unit load factor correction coefficient in the data source.

[0019] Optionally, determining the value of the load factor correction coefficient of the target unit according to the value of the load factor in the data source of the target unit includes:

[0020] If the target unit is a conventional coal-fired unit, or if the target unit is not a conventional coal-fired unit and the load factor of the target unit is greater than or equal to a first preset threshold, then determining the load factor correction coefficient of the target unit to be a first value;

[0021] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than a first preset threshold and greater than or equal to a second preset threshold, determining the load factor correction coefficient of the target unit to be a second value;

[0022] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than the second preset threshold and greater than or equal to the third preset threshold, determining the load factor correction coefficient of the target unit to be a third value;

[0023] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than a third preset threshold, the load factor correction coefficient of the target unit is determined to be a third value.

[0024] Optionally, determining the heating carbon emission data prediction result according to the heating amount of the target unit and the heating reference value in the carbon emission data reference parameter information includes:

[0025] The product of the heat supply of the target unit and the heat supply reference value in the carbon emission data reference parameter information is used as the heat supply carbon emission data prediction result.

[0026] Optionally, determining the power supply carbon emission data prediction result based on the power supply baseline value and the target unit cooling mode correction coefficient in the carbon emission data baseline parameter information, and the target unit power supply, target unit heat supply correction coefficient, and target unit load factor correction coefficient in the data source includes:

[0027] The product of the power supply of the target unit, the power supply reference value, the target unit cooling mode correction coefficient, the target unit heat supply correction coefficient and the target unit load factor correction coefficient is used as the power supply carbon emission data prediction result.

[0028] In a second aspect, an embodiment of the present application further provides a carbon emission data processing device, the device comprising:

[0029] An acquisition module, configured to acquire a data source of the target unit according to an identifier of the target unit input by a user, wherein the data source includes a power supply amount and a heat supply amount of the target unit;

[0030] An acquisition module is used to obtain the carbon emission data forecast period input by the user;

[0031] The determination module is used to determine the carbon emission prediction data of the target unit in the carbon emission data prediction period according to the data source of the target unit, the preset carbon emission data baseline parameter information and the carbon emission data prediction period.

[0032] Optionally, the acquisition module is specifically configured to:

[0033] Based on the parameter values ​​of each benchmark parameter entered by the user on the parameter setting page, carbon emission data benchmark parameter information is generated, and the carbon emission data benchmark parameter information includes: the identification of the target unit, the power supply benchmark value of the target unit, the heating benchmark value of the target unit, the unit type of the target unit, the unit type of the target unit, the target unit cooling method, and the target unit cooling method correction coefficient.

[0034] Optionally, the determining module is specifically configured to:

[0035] Determine the heating carbon emission data prediction result and the power supply carbon emission data prediction result respectively according to the data source of the target unit, the preset carbon emission data benchmark parameter information and the carbon emission data prediction period;

[0036] The carbon emission prediction data of the target unit in the carbon emission data prediction period is determined according to the heating carbon emission data prediction result and the power supply carbon emission data prediction result.

[0037] Optionally, the determining module is specifically configured to:

[0038] Determining a value of a load factor correction factor of the target unit according to a value of a load factor in a data source of the target unit;

[0039] Determining a heating carbon emission data prediction result based on the heating capacity of the target unit and the heating reference value in the carbon emission data reference parameter information;

[0040] The power supply carbon emission data prediction result is determined based on the power supply reference value and the target unit cooling mode correction coefficient in the carbon emission data reference parameter information, as well as the power supply of the target unit, the target unit heat supply correction coefficient and the target unit load factor correction coefficient in the data source.

[0041] Optionally, the determining module is specifically configured to:

[0042] If the target unit is a conventional coal-fired unit, or if the target unit is not a conventional coal-fired unit and the load factor of the target unit is greater than or equal to a first preset threshold, then determining the load factor correction coefficient of the target unit to be a first value;

[0043] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than a first preset threshold and greater than or equal to a second preset threshold, determining the load factor correction coefficient of the target unit to be a second value;

[0044] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than the second preset threshold and greater than or equal to the third preset threshold, determining the load factor correction coefficient of the target unit to be a third value;

[0045] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than a third preset threshold, the load factor correction coefficient of the target unit is determined to be a third value.

[0046] Optionally, the determining module is specifically configured to:

[0047] The product of the heat supply of the target unit and the heat supply reference value in the carbon emission data reference parameter information is used as the heat supply carbon emission data prediction result.

[0048] Optionally, the determining module is specifically configured to:

[0049] The product of the power supply of the target unit, the power supply reference value, the target unit cooling mode correction coefficient, the target unit heat supply correction coefficient and the target unit load factor correction coefficient is used as the power supply carbon emission data prediction result.

[0050] In a third aspect, an embodiment of the present application further provides an electronic device comprising: a processor, a storage medium and a bus, wherein the storage medium stores program instructions executable by the processor. When the application is running, the processor communicates with the storage medium via the bus, and the processor executes the program instructions to perform the steps of the carbon emission data processing method described in the first aspect above.

[0051] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and the computer program is read and executes the steps of the carbon emission data processing method described in the first aspect above.

[0052] The beneficial effects of this application are:

[0053] The present application provides a carbon emission data processing method, device, electronic device and storage medium. By obtaining the data source of the target group according to the identification of the target group, the data basis of the carbon emission data of the determined target group can be made more comprehensive and complete. In addition, based on the data source of the target group, the pre-set carbon emission data baseline parameter information and the carbon emission data prediction period, the carbon emission data of the determined target group in the carbon emission data prediction period can be made more accurate, avoiding reliance on manual calculation in the existing technology and improving the efficiency of carbon emission data calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 A flowchart of a carbon emission data processing method provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of a carbon emission data prediction interface provided in an embodiment of the present application;

[0057] Figure 3 A schematic diagram of a parameter information setting interface provided in an embodiment of the present application;

[0058] Figure 4 A flowchart of another carbon emission data processing method provided in an embodiment of the present application;

[0059] Figure 5 A flowchart of another carbon emission data processing method provided in an embodiment of the present application;

[0060] Figure 6 A schematic diagram of a process for determining a target unit's carbon emission prediction result provided in an embodiment of the present application;

[0061] Figure 7 A schematic diagram of a device for a carbon emission data processing method provided in an embodiment of the present application;

[0062] Figure 8 This is a structural block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of illustration and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowcharts can be implemented out of sequence, and steps without logical context can be reversed or implemented simultaneously. In addition, those skilled in the art, under the guidance of the contents of this application, can add one or more other operations to the flowchart, or remove one or more operations from the flowchart.

[0064] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0065] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0066] Optionally, the carbon emission data processing method provided in the embodiments of the present application is applied to an electronic device, such as a mobile phone, tablet computer, laptop computer, PDA, desktop computer, or other terminal device with computing and display capabilities, or a server. Specifically, the method can be applied to an application in a terminal device, such as a mobile phone app (application) or a computer application system.

[0067] The following is a detailed explanation of the specific implementation process of carbon emission data processing provided in the embodiments of this application.

[0068] Figure 1 This is a flow chart of a carbon emission data processing method provided in an embodiment of the present application, the execution subject of the method is the aforementioned electronic device. Figure 1 As shown, the method includes:

[0069] S101. Acquire a data source of a target unit according to an identifier of the target unit input by a user.

[0070] The data source may include the power supply of the target unit and the heat supply of the target unit, and the data source may refer to the data source of the target unit in all time periods.

[0071] Specifically, the user can enter the ID of the target unit and the name of the unit to which the target unit belongs on the quota forecast interface of the electronic device. Then, based on the ID of the target unit and the name of the unit to which the target unit belongs, the data source of the target unit can be obtained from the production data or plan data of the unit to which the target unit belongs. Figure 2 As shown, users can Figure 2 In the Unit Name input field, select the target unit's ID; you can also select a company name in the Company Name input field.

[0072] S102: Obtain the carbon emission data prediction period input by the user.

[0073] Specifically, the user can enter the carbon emission forecast period on the quota forecast interface on the electronic device, for example, Figure 2 In the Quota Forecast interface, select the forecast type in the Forecast Type selection column. The forecast type can be annual or monthly. The specific forecast date can be selected in the Forecast Date selection column.

[0074] For example, if the user selects monthly in the forecast type selection column and selects a specific month in the forecast date, the month of the carbon emission data forecast entered by the user can be obtained. For example, the user can predict the carbon emissions for January 2022, or the carbon emissions data for February 2023, or the carbon emissions data for May 2024. The selection can be made according to the actual situation.

[0075] S103 , determining the carbon emission data of the target unit in the carbon emission data prediction period according to the data source of the target unit, the pre-set carbon emission data benchmark parameter information, and the carbon emission data prediction period.

[0076] Optionally, the data source of the target unit within the forecast period can be determined from the data source of the target unit obtained in S101 according to the carbon emission data forecast period input by the user. Specifically, if the carbon emission forecast period input by the user is January 2022, that is, the user needs to calculate the carbon emission data for the forecast period, then the data source of the target unit for the forecast period can be obtained, that is, the power supply of the target unit and the heat supply of the target unit in January 2022 can be extracted from the data source of the target unit obtained in S101 according to the forecast period input by the user.

[0077] Optionally, different units may have different carbon emission data baseline parameters, and the carbon emission data baseline parameters can be determined based on the unit identifier on the parameter setting page. Figure 3 shown.

[0078] Optionally, a preset method may be used based on the data source of the target unit, pre-set carbon emission data baseline parameter information, and the carbon emission data prediction period to determine the carbon emission prediction data of the target unit in the carbon emission data prediction period.

[0079] In this embodiment, the data source of the target group can be obtained according to the identification of the target group, so that the data basis of the carbon emission data of the determined target group can be more comprehensive and complete, and according to the data source of the target group, the pre-set carbon emission data baseline parameter information and the carbon emission data prediction period, the carbon emission data of the determined target group in the carbon emission data prediction period can be made more accurate, avoiding reliance on manual calculation in the existing technology and improving the efficiency of carbon emission data calculation.

[0080] Optionally, before the above S101, obtaining the data source of the target unit according to the identifier of the target unit input by the user, includes:

[0081] Optionally, based on the parameter values ​​of each benchmark parameter entered by the user on the parameter setting page, carbon emission data benchmark parameter information is generated. The carbon emission benchmark parameter information may include: the target unit identifier, the target unit power supply benchmark value, the target unit heating benchmark value, the target unit type, the target unit cooling method, and the target unit cooling method correction factor.

[0082] The parameter setting page is as follows: Figure 3 As shown, the user can select the specific name of the unit to which the target unit belongs in the unit name selection column; can select the identifier of the target unit in the unit selection column, such as unit 1, unit 2, etc.; can select the category of the target unit in the unit category, where the category of the unit can include, for example, conventional coal-fired units above 300MW, conventional coal-fired units below 300MW, unconventional coal-fired units such as coal gangue and water-coal slurry, and gas-fired units; select the type of the target unit in the unit type, where the unit type can include coal-fired units and gas-fired units; can enter the power supply benchmark value of the target unit in the power supply benchmark value input column, and can enter the heating benchmark value of the target unit in the heating benchmark value input column, where, The heating benchmark value and the power supply benchmark value can be determined according to the unit to which the target unit belongs. Each unit can include different power supply benchmark values ​​and heating benchmark values; the type of the target unit can be selected in the unit type selection column; the specific year of the forecast can be selected in the performance year selection column; the cooling method of the target unit can be selected in the unit cooling method selection column; and based on the cooling method of the target unit, the cooling method correction coefficient of the target unit can be entered in the cooling method correction coefficient input column. For example, if the cooling method is air cooling, the cooling method correction coefficient can be determined to be 10.5; if the cooling method is water cooling, the cooling method correction coefficient can be determined to be 1; if the cooling method is other, the cooling method correction coefficient can be determined to be 0.

[0083] Figure 4 A flow chart of another carbon emission data processing method provided in an embodiment of the present application is shown as follows: Figure 4As shown, the above S103 determines the carbon emission data of the target unit in the carbon emission data prediction period according to the data source of the target unit, the preset carbon emission data baseline parameter information, and the carbon emission data prediction period, which may include:

[0084] S201 , determining heating carbon emission data prediction results and power supply carbon emission data prediction results respectively according to the data source of the target unit, pre-set carbon emission data benchmark parameter information, and carbon emission data prediction period.

[0085] Optionally, based on the data source of the target unit, the preset carbon emission data baseline parameter information and the carbon emission data prediction period, a preset method can be used to respectively determine the target unit's heating carbon emission data prediction results and the target unit's power supply carbon emission data prediction results.

[0086] For example, if the carbon emission data prediction period is an annual period, such as 2022, the preset method can be used based on the historical data source of the target unit from January to December 2022 and the pre-set negotiation data benchmark parameter information to obtain the heating carbon emission data prediction results of the target unit from January to December 2022 and the power supply carbon emission data prediction results of the target unit.

[0087] For example, if the carbon emission data prediction period is monthly, such as May 2024, the preset method can be used according to the planned data source for May 2024 and the pre-set negotiation data benchmark parameter information to obtain the heating carbon emission data prediction results of the target unit and the power supply carbon emission data prediction results of the target unit in May 2024.

[0088] S202: Determine the carbon emission prediction data of the target unit during the carbon emission data prediction period based on the heat supply carbon emission data prediction results and the power supply carbon emission data prediction results.

[0089] The carbon emission forecast data can be obtained based on the heat supply carbon emission data forecast results and the power supply carbon emission data forecast results, and is the total carbon emission forecast data of the target unit. Specifically, the sum of the heat supply carbon emission data forecast results and the power supply carbon emission data forecast results can be used as the carbon emission forecast data of the target unit during the forecast period.

[0090] For example, if the carbon emission data prediction period is a year, such as 2022, the carbon emission prediction data of the target unit in 2022 can be obtained based on the heating carbon emission data prediction results and the power supply carbon emission data prediction results of the target unit in 2022.

[0091] For example, if the carbon emission data prediction period is a month, such as May 2024, the carbon emission prediction data of the target unit in May 2024 can be determined using a preset method based on the heating carbon emission data prediction results of the target unit and the power supply carbon emission data prediction results of the target unit in May 2024.

[0092] Figure 5 A flow chart of another carbon emission data processing method provided in an embodiment of the present application is shown as follows: Figure 5 As shown, in the above S201, based on the data source of the target unit, the preset carbon emission data benchmark parameter information, and the carbon emission data prediction period, respectively determining the heating carbon emission data prediction results and the power supply carbon emission data prediction results may include:

[0093] S301. Determine a load factor correction factor of the target unit according to the load factor in the data source of the target unit.

[0094] The target unit load factor can be represented by F, for example, and the target unit load factor correction factor can be represented by Ff, for example. The target unit load factor can be determined based on the target unit power supply, target unit capacity, and target unit operating time in the target unit data source. For example, the target unit load factor can be represented by Ff according to the formula Calculated, where F is the load factor of the target unit, W fdi is the power generation of the target unit, P ei is the target unit capacity, i is the target unit identifier, t i The target unit operating time.

[0095] S302: Determine a heating carbon emission data prediction result based on the heating amount of the target unit and the heating reference value in the carbon emission data reference parameter information.

[0096] The heat supply of the target unit refers to the heat supply of the target unit in the carbon emission prediction period extracted from the data source of the target unit, and can be represented by Ah, for example.

[0097] Optionally, the heating carbon emission data prediction result of the target unit in the carbon emission prediction period can be determined using a preset method based on the heating amount of the target unit in the prediction period in the target unit data source and the heating reference value in the carbon emission data reference parameter information.

[0098] S303. Determine the power supply carbon emission data prediction result based on the power supply of the target unit, the power supply reference value in the carbon emission data reference parameter information, the target unit cooling mode correction coefficient, the target unit heat supply correction coefficient in the data source, and the target unit load factor correction coefficient.

[0099] The target unit's power supply refers to the target unit's power supply during the carbon emission forecast period, extracted from the target unit's data source. For example, this can be represented by Qe. The target unit's heat supply correction factor can also be obtained from the data source. Specifically, it can be calculated using the formula 1-0.22Q5, where Q5 refers to the target unit's heat supply ratio.

[0100] Optionally, a preset method can be used to determine the power supply carbon emission data prediction result based on the power supply of the target unit in the prediction period in the target unit data source and the power supply baseline value in the carbon emission data baseline parameter information, the target unit cooling mode correction coefficient, the target unit heating correction coefficient in the data source, and the target unit load factor correction coefficient.

[0101] Optionally, determining the value of the load factor correction coefficient of the target unit according to the load factor value in the data source of the target unit in S301 may include:

[0102] The specific process of determining the value of the target unit load factor correction factor can be achieved by Figure 6 To indicate display.

[0103] Optionally, if the target unit is a conventional coal-fired unit, or if the target unit is not a conventional coal-fired unit and the load factor of the target unit is greater than or equal to a first preset threshold, the load factor correction factor of the target unit is determined to be a first value. The first preset threshold may be, for example, 0.85, and the first value may be, for example, 1. It is worth noting that the first preset threshold and the first value may also be other values, which are set according to actual circumstances.

[0104] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than the first preset threshold and greater than or equal to the second preset threshold, the load factor correction factor of the target unit is determined to be a second value. The second preset threshold may be, for example, 0.8. The second preset threshold is less than the first preset threshold, and the second value may be Ff = 1 + 0.0014 * (85 - 100 * F). It is worth noting that the second preset threshold may also be other values, which are set according to actual conditions.

[0105] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than the second preset threshold and greater than or equal to the third preset threshold, the target unit load factor correction factor is determined to be a third value, which may be, for example, Ff = 1.007 + 0.0016 * (80 - 100 * F), where the third preset threshold may be, for example, 0.75, which is less than the second preset threshold. It is worth noting that the third preset threshold may also be other values, which are set according to actual conditions.

[0106] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than the third preset threshold, the load factor correction factor of the target unit is determined to be a third value, wherein the third value can be, for example, Ff=1.015 (16-20*F) .

[0107] In this embodiment, different target unit load factor correction coefficients are determined according to the different values ​​of the target unit load factor, which can make the determined target unit load factor correction coefficient more accurate, and thus the obtained target unit carbon emission data prediction results more accurate. At the same time, through multi-condition intelligent calculation, the traditional manual calculation method is replaced, the manual workload is reduced, and the accuracy of the calculation is improved.

[0108] Optionally, determining the heating carbon emission data prediction result in S302 according to the heating amount of the target unit and the heating reference value in the carbon emission data reference parameter information may include:

[0109] Optionally, the product of the heating supply of the target unit and the heating reference value in the carbon emission data reference parameter information can be used as the heating carbon emission data prediction result. For example, the heating supply of the target unit can be expressed by Ah, and the heating reference value can be expressed by Bh, for example. Then the heating carbon emission data prediction result of the target unit is Ah*Bh.

[0110] Optionally, determining the power supply carbon emission data prediction result in S303 based on the power supply of the target unit, the power supply baseline value in the carbon emission data baseline parameter information, the target unit cooling mode correction factor, the target unit heat supply correction factor in the data source, and the target unit load factor correction factor may include:

[0111] Optionally, the product of the target unit's power supply, the power supply baseline value in the carbon emission data baseline parameter information, the target unit's cooling mode correction coefficient, the target unit's heat supply correction coefficient in the data source, and the target unit's load factor correction coefficient is used as the target unit's power supply carbon emission data prediction result.

[0112] Among them, the power supply of the target unit can be represented by Qe, for example, the power supply benchmark value in the carbon emission data benchmark parameter information can be represented by Be, for example, the target unit cooling method correction coefficient can be represented by FL, for example, the target unit heat supply correction coefficient can be represented by Fr, for example, the target unit load factor correction coefficient can be represented by Ff, then the target unit power supply carbon emission data prediction result can be Qe*Be*FL*Fr*Ff.

[0113] Optionally, the method may further include:

[0114] Optionally, when a user needs to access the platform front-end interface in this application, platform authentication and third-party user authentication need to be completed. Specifically, the user can use user information to log in to the platform service. After logging in, the user can obtain the third-party authentication service by clicking. After switching from the platform service to the third-party authentication service, the user can use user information to log in to the third-party authentication service. When the user successfully logs in to the third-party authentication service, the third-party service returns an authorization code generated based on the user information to the platform service, wherein the authorization code may indicate the access module authorized by the user. The platform then sends an access request to the third-party service based on the returned authorization code. The access request includes the module that the user can access. When the third party receives the access request, it parses the access request, obtains the user information and the authorization code, and verifies the user information and the authorization code. After the verification is passed, the platform service can be provided with the read permission of the authorization module, and the user can access the authorization module.

[0115] In this embodiment, the security and confidentiality of enterprise carbon asset-related data can be improved through platform authentication and third-party service authentication.

[0116] Figure 7 A schematic diagram of a device for processing carbon emission data provided in an embodiment of the present application is shown in FIG. Figure 7 As shown, the device includes:

[0117] An acquisition module 401 is configured to acquire a data source of a target unit according to an identifier of the target unit input by a user, wherein the data source includes a power supply amount and a heat supply amount of the target unit;

[0118] The acquisition module 401 is used to obtain the carbon emission data prediction period input by the user;

[0119] The determination module 402 is configured to determine the carbon emission prediction data of the target unit in the carbon emission data prediction period according to the data source of the target unit, the preset carbon emission data baseline parameter information and the carbon emission data prediction period.

[0120] Optionally, the acquisition module 401 is specifically configured to:

[0121] Based on the parameter values ​​of each benchmark parameter entered by the user on the parameter setting page, carbon emission data benchmark parameter information is generated, and the carbon emission data benchmark parameter information includes: the identification of the target unit, the power supply benchmark value of the target unit, the heating benchmark value of the target unit, the unit type of the target unit, the unit type of the target unit, the target unit cooling method, and the target unit cooling method correction coefficient.

[0122] Optionally, the determining module 402 is specifically configured to:

[0123] Determine the heating carbon emission data prediction result and the power supply carbon emission data prediction result respectively according to the data source of the target unit, the preset carbon emission data benchmark parameter information and the carbon emission data prediction period;

[0124] The carbon emission prediction data of the target unit in the carbon emission data prediction period is determined according to the heating carbon emission data prediction result and the power supply carbon emission data prediction result.

[0125] Optionally, the determining module 402 is specifically configured to:

[0126] Determining a value of a load factor correction factor of the target unit according to a value of a load factor in a data source of the target unit;

[0127] Determining a heating carbon emission data prediction result based on the heating capacity of the target unit and the heating reference value in the carbon emission data reference parameter information;

[0128] The power supply carbon emission data prediction result is determined based on the power supply reference value and the target unit cooling mode correction coefficient in the carbon emission data reference parameter information, as well as the power supply of the target unit, the target unit heat supply correction coefficient and the target unit load factor correction coefficient in the data source.

[0129] Optionally, the determining module 402 is specifically configured to:

[0130] If the target unit is a conventional coal-fired unit, or if the target unit is not a conventional coal-fired unit and the load factor of the target unit is greater than or equal to a first preset threshold, then determining the load factor correction coefficient of the target unit to be a first value;

[0131] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than a first preset threshold and greater than or equal to a second preset threshold, determining the load factor correction coefficient of the target unit to be a second value;

[0132] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than the second preset threshold and greater than or equal to the third preset threshold, determining the load factor correction coefficient of the target unit to be a third value;

[0133] If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than a third preset threshold, the load factor correction coefficient of the target unit is determined to be a third value.

[0134] Optionally, the determining module 402 is specifically configured to:

[0135] The product of the heat supply of the target unit and the heat supply reference value in the carbon emission data reference parameter information is used as the heat supply carbon emission data prediction result.

[0136] Optionally, the determining module 402 is specifically configured to:

[0137] The product of the power supply of the target unit, the power supply reference value, the target unit cooling mode correction coefficient, the target unit heat supply correction coefficient and the target unit load factor correction coefficient is used as the power supply carbon emission data prediction result.

[0138] Figure 8 This is a structural block diagram of an electronic device 500 provided in an embodiment of the present application. Figure 8 As shown, the electronic device may include: a processor 501 and a memory 502.

[0139] Optionally, a bus 503 may be further included, wherein the memory 502 is used to store machine-readable instructions (for example, Figure 7 When the electronic device 500 is running, the processor 501 communicates with the memory 502 via the bus 503, and when the machine-readable instructions are executed by the processor 501, the method steps in the above method embodiment are performed.

[0140] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method steps in the above-mentioned carbon emission data processing method embodiment are executed.

[0141] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the method embodiment, and will not be repeated in this application. In the several embodiments provided in this application, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0142] In addition, the functional units in the various embodiments of the present application can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0143] The above is only a specific implementation method of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the protection scope of the present application.

Claims

1. A carbon emission data processing method, characterized in that: The method comprises: According to the identifier of the target unit input by the user, a data source of the target unit is obtained, wherein the data source includes the power supply and the heat supply of the target unit; Obtain the carbon emission data forecast period input by the user; The carbon emission prediction data of the target unit in the carbon emission data prediction period is determined according to the data source of the target unit, the preset carbon emission data baseline parameter information and the carbon emission data prediction period.

2. The carbon emission data processing method according to claim 1, characterized in that: Before obtaining the data source of the target unit according to the identifier of the target unit input by the user, the method includes: Based on the parameter values ​​of each benchmark parameter entered by the user on the parameter setting page, carbon emission data benchmark parameter information is generated, and the carbon emission data benchmark parameter information includes: the identification of the target unit, the power supply benchmark value of the target unit, the heating benchmark value of the target unit, the unit type of the target unit, the unit type of the target unit, the target unit cooling method, and the target unit cooling method correction coefficient.

3. The carbon emission data processing method according to claim 1, characterized in that: The step of determining the carbon emission forecast data of the target unit during the carbon emission data forecast period based on the data source of the target unit, the preset carbon emission data baseline parameter information, and the carbon emission data forecast period includes: Determine the heating carbon emission data prediction result and the power supply carbon emission data prediction result respectively according to the data source of the target unit, the preset carbon emission data benchmark parameter information and the carbon emission data prediction period; The carbon emission prediction data of the target unit in the carbon emission data prediction period is determined according to the heating carbon emission data prediction result and the power supply carbon emission data prediction result.

4. The carbon emission data processing method according to claim 3, characterized in that: The step of determining the heating carbon emission data prediction result and the power supply carbon emission data prediction result respectively according to the data source of the target unit, the preset carbon emission data benchmark parameter information, and the carbon emission data prediction period includes: Determine the load factor correction factor of the target unit according to the load factor in the data source of the target unit; Determining a heating carbon emission data prediction result based on the heating capacity of the target unit and the heating reference value in the carbon emission data reference parameter information; The power supply carbon emission data prediction result is determined based on the power supply reference value and the target unit cooling mode correction coefficient in the carbon emission data reference parameter information, as well as the power supply of the target unit, the target unit heat supply correction coefficient and the target unit load factor correction coefficient in the data source.

5. The carbon emission data processing method according to claim 4, characterized in that: Determining the value of the load factor correction coefficient of the target unit according to the value of the load factor in the data source of the target unit includes: If the target unit is a conventional coal-fired unit, or if the target unit is not a conventional coal-fired unit and the load factor of the target unit is greater than or equal to a first preset threshold, then determining the load factor correction coefficient of the target unit to be a first value; If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than a first preset threshold and greater than or equal to a second preset threshold, determining the load factor correction coefficient of the target unit to be a second value; If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than the second preset threshold and greater than or equal to the third preset threshold, determining the load factor correction coefficient of the target unit to be a third value; If the target unit is not a conventional coal-fired unit and the load factor of the target unit is less than a third preset threshold, the load factor correction coefficient of the target unit is determined to be a third value.

6. The carbon emission data processing method according to claim 4, characterized in that: The step of determining the heating carbon emission data prediction result based on the heating amount of the target unit and the heating reference value in the carbon emission data reference parameter information includes: The product of the heat supply of the target unit and the heat supply reference value is used as the heat supply carbon emission data prediction result.

7. The carbon emission data processing method according to claim 6, characterized in that: The determining of the power supply carbon emission data prediction result according to the power supply reference value and the target unit cooling mode correction coefficient in the carbon emission data reference parameter information, and the target unit power supply, the target unit heat supply correction coefficient, and the target unit load factor correction coefficient in the data source, includes: The product of the power supply of the target unit, the power supply reference value, the target unit cooling mode correction coefficient, the target unit heat supply correction coefficient and the target unit load factor correction coefficient is used as the power supply carbon emission data prediction result.

8. A carbon emission data processing device, characterized in that: include: An acquisition module, configured to acquire a data source of the target unit according to an identifier of the target unit input by a user, wherein the data source includes a power supply amount and a heat supply amount of the target unit; An acquisition module is used to obtain the carbon emission data forecast period input by the user; The determination module is used to determine the carbon emission prediction data of the target unit in the carbon emission data prediction period according to the data source of the target unit, the preset carbon emission data baseline parameter information and the carbon emission data prediction period.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, the steps of the carbon emission data processing method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the carbon emission data processing method according to any one of claims 1 to 7.

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