Method, device, terminal and storage medium for calculating carbon emission intensity

Abstract

The embodiment of the application discloses a kind of methods, devices, terminal and storage medium for calculating carbon emission intensity, belong to the field of energy management.The method comprises: obtaining the basic attribute data of power system, and obtaining the active power generation of generator set based on the data;According to the life cycle type of generator set, obtain the initial value of power generation fuel carbon emission factor of generator set, and the initial value of power generation fuel carbon emission factor is used to indicate the carbon emission of unit power generation;According to the active power generation of generator set and the initial value of power generation fuel carbon emission factor, calculate the carbon emission intensity of generator set.The embodiment of the application can determine the carbon emission intensity of generator set in real time by obtaining the active power generation of generator set and the initial value of power generation fuel carbon emission factor of generator set, so that the carbon emission of equipment in power plant can be counted in real time, the statistical granularity of carbon emission intensity is reduced, and the monitoring effect of carbon emission intensity of power generation equipment is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of energy management, and in particular to a method, device, terminal, and storage medium for calculating carbon emission intensity. Background Art

[0002] As global warming becomes increasingly prominent, humanity is beginning to regulate carbon emissions in various fields. In the energy sector, the carbon emission intensity of power generation, as a key production indicator, is increasingly being considered by local authorities.

[0003] In related technologies, administrative departments can obtain the total net power generation, fuel type and total fuel consumption of all power plants in the managed area within a statistical period of one quarter or one year, and calculate and publish the marginal emission factor of electricity, also known as carbon emission intensity. Summary of the Invention

[0004] The present invention provides a method, device, terminal, and storage medium for calculating carbon emission intensity. The technical solution is as follows:

[0005] According to one aspect of the present application, a method for calculating carbon emission intensity is provided, the method comprising:

[0006] Acquiring basic attribute data of the power system, and obtaining active power generation of the generator set based on the basic attribute data;

[0007] Obtaining an initial value of the carbon emission factor of the power generation fuel of the power generation set according to the life cycle type of the power generation set, wherein the initial value of the carbon emission factor of the power generation fuel is used to indicate the size of the carbon emissions generated per unit power generation;

[0008] The carbon emission intensity of the generator set is calculated based on the active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel.

[0009] According to another aspect of the present application, a device for calculating carbon emission intensity is provided, the device comprising:

[0010] A first acquisition module is configured to acquire basic attribute data of the power system and obtain active power generation of the generator set based on the basic attribute data;

[0011] A second acquisition module is used to obtain an initial value of the carbon emission factor of the power generation fuel of the power generation set according to the life cycle type of the power generation set, wherein the initial value of the carbon emission factor of the power generation fuel is used to indicate the size of the carbon emissions generated per unit power generation;

[0012] A data calculation module is used to calculate the carbon emission intensity of the generator set based on the active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel.

[0013] According to another aspect of the present application, a terminal is provided, comprising a processor and a memory, wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method for calculating carbon emission intensity as provided in various aspects of the present application.

[0014] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium stores at least one instruction, and the instruction is loaded and executed by a processor to implement the method for calculating carbon emission intensity as provided in various aspects of the present application.

[0015] According to one aspect of the present application, a computer program product is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for calculating carbon emission intensity provided in the various optional implementations described above.

[0016] The beneficial effects of the technical solutions provided in the embodiments of the present application may include:

[0017] This application obtains the basic attribute data of the power system, obtains the active power generation of the generator set based on the basic attribute data; then obtains the initial value of the carbon emission factor of the power generation fuel of the generator set according to the life cycle type of the generator set, and the initial value of the carbon emission factor of the power generation fuel is used to indicate the size of the carbon emissions generated by the unit power generation; finally, the carbon emission intensity of the generator set is calculated based on the rated active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel. Since this application can target the active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel of the generator set, and calculate the carbon emission intensity of the generator set based on the data, the carbon emission intensity of the smallest unit generator set in the power generation system can be monitored, thereby reducing the monitoring granularity of the carbon emission intensity of the entire power system, and then by accumulating different generator sets, the real-time carbon emission intensity of each power plant or region can be counted, providing relevant data for subsequent carbon trading of the power system, thereby promoting the development of energy conservation and emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly introduce the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is a structural block diagram of a terminal provided by an exemplary embodiment of the present application;

[0020] Figure 2 is a framework diagram of a system for calculating carbon emission intensity provided by an exemplary embodiment of the present application;

[0021] Figure 3 is a framework diagram of a system for calculating carbon emission intensity provided by an exemplary embodiment of the present application;

[0022] Figure 4 is a flow chart of a method for calculating carbon emission intensity provided by an exemplary embodiment of the present application;

[0023] Figure 5 is a flow chart of a method for calculating carbon emission intensity provided by another exemplary embodiment of the present application;

[0024] Figure 6 This application is based on Figure 5 A schematic diagram of carbon emission intensity monitoring provided by the illustrated embodiment;

[0025] Figure 7 This is a flow chart of a method for tracking regional carbon footprints provided by an exemplary embodiment of the present application;

[0026] Figure 8 is a flow chart of a carbon intensity calculation method provided by an exemplary embodiment of the present application;

[0027] Figure 9 This is a flow chart of a method for calculating carbon intensity by site provided by an exemplary embodiment of the present application;

[0028] Figure 10 This is a structural block diagram of an apparatus for calculating carbon emission intensity provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0030] When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of devices and methods consistent with certain aspects of the present application as detailed in the appended claims.

[0031] In the description of this application, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to the specific circumstances. In addition, in the description of this application, unless otherwise specified, "multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship.

[0032] As used herein, the term "if" is optionally interpreted as "when," "upon," "in response to determining," or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined that," or "if (stated condition or event) is detected," or "in response to detecting (stated condition or event)," depending on the context.

[0033] It is important to note that the use of personally identifiable information should comply with privacy policies and practices that are generally recognized to meet or exceed industry or government requirements for maintaining user privacy. Specifically, the nature of authorized use of personally identifiable information should be clearly stated to users during the management and processing of personally identifiable information to minimize the risk of unintentional or unauthorized access or use.

[0034] In order to facilitate understanding of the solutions shown in the embodiments of the present application, several nouns appearing in the embodiments of the present application are introduced below.

[0035] GDF (Grid Data Fabric).

[0036] CI (Carbon Intensity).

[0037] Multi-time Scales.

[0038] Multi-spatial Dimensions.

[0039] For example, the method for calculating carbon emission intensity shown in the embodiments of this application can be applied to a terminal that has a display screen and is capable of calculating carbon emission intensity. The terminal may include a laptop, desktop computer, all-in-one computer, server, or workstation. It should be noted that as the amount of data calculation required by this application increases, this application requires a high-performance terminal. Technicians applying this application can schematically adjust the hardware performance of the terminal running the solution of this application.

[0040] See Figure 1 , Figure 1 This is a structural block diagram of a terminal provided by an exemplary embodiment of the present application. Figure 1 As shown, the terminal includes a processor 120, a memory 140, and a communication component 160. The memory 140 stores at least one instruction, which is loaded and executed by the processor 120 to implement the method for calculating carbon emission intensity as described in the various method embodiments of this application. The communication component 160 is used to receive data obtained from the outside world and send data to the outside world.

[0041] In the present application, the terminal 100 is capable of acquiring basic attribute data of the power system, and obtaining the active power generation of the generator set based on the basic attribute data; obtaining the initial value of the carbon emission factor of the power generation fuel of the generator set according to the life cycle type of the generator set, and the initial value of the carbon emission factor of the power generation fuel is used to indicate the size of the carbon emissions generated per unit power generation; and calculating the carbon emission intensity of the generator set based on the active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel.

[0042] The processor 120 may include one or more processing cores. The processor 120 utilizes various interfaces and circuits to connect various components within the terminal 100. It executes instructions, programs, code sets, or instruction sets stored in the memory 140, and accesses data stored in the memory 140 to perform various functions and process data for the terminal 100. Optionally, the processor 120 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 120 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 120 and may be implemented as a separate chip.

[0043] The memory 140 may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory 140 includes a non-transitory computer-readable storage medium. The memory 140 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 140 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the following various method embodiments, etc.; the data storage area may store data involved in the following various method embodiments, etc.

[0044] The communication component 160 may include a signal processing module and an antenna. The antenna may also be replaced by a communication cable. For example, the terminal 100 in this application is capable of obtaining basic attribute data of the power system, which may be obtained from an external power system. The basic attribute data may be stored in a designated device, and the terminal 100, after obtaining the corresponding permissions, can obtain the basic attribute data through the communication component 160.

[0045] Please refer toFigure 2 , Figure 2 This is a framework diagram of a system for calculating carbon emission intensity, provided in accordance with an exemplary embodiment of the present application. System 200 includes a terminal 100, a generator set 211, and a management device 220. Generator set 211 is connected to management device 220. Management device 220 stores the active power generation of devices including generator set 211. It should be noted that the data stored in management device 220 may not be active power generation, but rather a set of other intermediate data that, after calculation, can be used to determine the active power generation of generator set 211.

[0046] It should be noted that the terminal 100 can be placed in a dispatch center or monitoring center. The terminal 100 can display data on multiple screens. For example, when the present solution is executed on a terminal in a dispatch center, the dispatch center can display the carbon emission intensity of the currently managed generators or power plants in real time on multiple screens.

[0047] Please refer to Figure 3 , Figure 3 This is a framework diagram of a system for calculating carbon emission intensity, provided by an exemplary embodiment of the present application. System 300 includes a terminal 100, a thermal power plant 210, a management device 220, an equivalent load 230, a hydropower plant 240, a photovoltaic power plant 250, a wind power plant 260, and a nuclear power plant 270.

[0048] Among them, each power plant has its own generator set. In one possible scenario, the types of generator sets belonging to the same power plant are the same. For example, the generator sets belonging to the same thermal power plant 210 are all thermal power sets. In another possible scenario, the types of generator sets belonging to the same power plant may be different. For example, a hybrid power plant includes both photovoltaic units and thermal power units. The embodiment of the present application does not limit the types of generator sets in a power plant. Regardless of whether the types of generator sets in the same power plant are the same, the solution shown in the present application can be used.

[0049] The following describes the situation of the generator sets in each power plant in this example.

[0050] The thermal power plant 210 includes a thermal power unit 211 , a thermal power unit 212 , and a thermal power unit 213 .

[0051] The hydropower plant 240 includes a hydropower unit 241 and a hydropower unit 242 .

[0052] The photovoltaic power plant 250 is provided with a photovoltaic generator group 251 .

[0053] The wind power plant 260 includes a wind turbine 261 and a wind turbine 262 .

[0054] The nuclear power plant 270 includes a steam unit 271 and a steam unit 272 .

[0055] In this example, management device 220 can access data from each power plant. In one possible implementation, each power plant has plant-specific equipment for managing its generator sets. Management device 220 communicates with the plant-specific equipment at each power plant to obtain data about its generator sets. For example, the management device can communicate with the plant-specific equipment at each power plant to obtain the active power generation of its generator sets. In another possible implementation, management device 220 communicates directly with the generator sets at each power plant to obtain relevant data for each generator set.

[0056] The equivalent load 230 may be a device that consumes power generated by other devices in the power grid where the system 300 is located during a first period and provides power to the power grid where the system 300 is located during a second period. It should be noted that the first period and the second period do not overlap.

[0057] In other words, the equivalent load 230 may be an equivalent object of a port outside the system 300 .

[0058] With the introduction of carbon peak and carbon neutrality plans, the carbon trading market has become a tradable carbon emissions performance standard across multiple industries. The power industry, as the primary frontier for achieving the dual carbon goals, has proposed building a new power system dominated by renewable energy. The low-carbon transformation of the power sector has become a critical need and a key initiative for government agencies. Quantitative analysis of carbon intensity, as a foundational technical support, enables more precise energy flow and optimized grid operation through time- and location-based carbon footprint management. This helps mitigate the strong random fluctuations in renewable energy power and improve its utilization.

[0059] There are multiple factors that influence carbon emission intensity, and different conclusions can be drawn from different analytical perspectives. Among these factors, economic scale, energy intensity, energy structure, and industrial structure are some of the most frequently mentioned in current research. Before implementing the solution presented in this application, administrative departments will compile statistics for the regions comprising multiple provinces and regions to determine the carbon emission intensity of a given region during a specified measurement period.

[0060] Based on the above issues, for government agencies, the solution provided in this application can monitor the total carbon emissions within the administrative regions under their jurisdiction and allocate carbon quotas. For the power sector, the solution provided in this application can understand the carbon footprint of electricity and assist in the promotion of new energy consumption and power market reform.

[0061] Among other solutions provided by this proposal, since the source of electricity used by ordinary enterprises can be monitored and ultimately traced back to the generator set, the carbon emissions of ordinary enterprises during electricity production can also be monitored, improving the carbon emission intensity of ordinary enterprises when producing goods. For enterprises that need to export goods, this application can provide precision marketing based on the carbon emission intensity of goods produced, helping enterprises to scientifically arrange production plans and facilitate their smooth participation in carbon trading.

[0062] Please refer to Figure 4 , Figure 4 This is a flow chart of a method for calculating carbon emission intensity provided by an exemplary embodiment of the present application. The method for calculating carbon emission intensity can be applied in the terminal shown above. Figure 4 In the 2016-2020 report, the methods for calculating carbon emission intensity include:

[0063] Step 410: Obtain basic attribute data of the power system, and obtain the active power generation of the generator set based on the basic attribute data.

[0064] In the embodiment of the present application, the terminal can obtain basic attribute data of the power system. It should be noted that, in one possible manner, the basic attribute data can directly include the active power generation of the generator set.

[0065] In another possible embodiment, the basic attribute data includes data used to calculate the active power generation of the generator set. For example, the basic attribute data also includes measurement data such as the current and voltage of the generator set, and the active power generation of the generator set is calculated based on the current and voltage.

[0066] Optionally, the basic attribute data may further include, according to data type, at least one of management data, power grid model data, power grid operation data, power supply operation data, load operation data, and transaction data.

[0067] Optionally, management data may include administrative region data, generator unit type, and generator unit installed capacity. Illustratively, administrative region data may include province, prefecture-level city, district, county, township, and other data. Generator unit types include thermal power units, hydropower units, wind power units, photovoltaic units, and nuclear power units. The input power of a thermal power unit is thermal energy; the input power of a hydropower unit is hydraulic potential energy; the input power of a wind power unit is wind kinetic energy; the input power of a photovoltaic unit is solar energy; and the input power of a nuclear power unit is nuclear energy. The installed capacity of a generator unit indicates the maximum power generation capacity of a single unit.

[0068] Optionally, the grid operation data includes measurement data such as active power generation, reactive power generation, current of the generator set, and voltage of the generator set.

[0069] Optionally, the power supply operation type data comprises energy power prediction data, power generation plan data and maintenance plan data.

[0070] Optionally, the load operation type data comprises bus load prediction type data, energy storage and electric vehicle charging and discharging power and orderly electricity consumption sequence.

[0071] Optionally, the transaction type data comprises power plant medium and long term transaction curve and power plant day-ahead plan curve.

[0072] In step 420, the initial value of the carbon emission factor of the power generation fuel of the power generation unit is obtained according to the life cycle type of the power generation unit, and the initial value of the carbon emission factor of the power generation fuel of the power generation unit is used to indicate the size of the carbon emission amount per unit of power generation.

[0073] In this example, the terminal can obtain the initial value of the carbon emission factor of the power generation fuel of the power generation unit according to the life cycle type of the power generation unit.

[0074] Optionally, the life cycle type comprises a true type and a false type. In the true type, the life cycle type needs to be considered when determining the initial value of the carbon emission factor of the power generation fuel of the power generation unit. In the false type, the life cycle type does not need to be considered when determining the initial value of the carbon emission factor of the power generation fuel of the power generation unit.

[0075] In this example, different life cycle types correspond to different mapping relationships. In the case of determining the life cycle type of the power generation unit, the terminal can obtain the initial value of the carbon emission factor of the power generation fuel of the power generation unit, which can indicate the size of the carbon emission amount per unit of power generation. It should be noted that the initial value of the carbon emission factor of the power generation fuel can be a unitless coefficient. The higher the value, the higher the carbon emission amount per unit of power generation of the power generation unit. Correspondingly, in the case of the lower value of the initial value of the carbon emission factor of the power generation fuel of the power generation unit, the carbon emission amount per unit of power generation of the power generation unit is lower.

[0076] In step 430, the carbon emission intensity of the power generation unit is calculated according to the active power generation amount of the power generation unit and the initial value of the carbon emission factor of the power generation fuel.

[0077] In the embodiment of the present application, the terminal can multiply the active power generation amount of the power generation unit and the initial value of the carbon emission factor of the power generation fuel, and take the product as the carbon emission intensity of the power generation unit. Thus, the embodiment of the present application can obtain the basic carbon emission intensity of the power generation unit.

[0078] Optionally, if the data of the power generation unit is updated in real time, the carbon emission intensity shown by the terminal is also real-time updated data.

[0079] Optionally, if the display screen of the terminal can display the carbon intensity of the generator set, the terminal can display the current carbon intensity of the generator set in real time when the carbon intensity is real-time updated data of the generator set.

[0080] Illustratively, if the active power generation amount P of the generator set is known, and the initial value of the carbon emission factor of the power generation fuel of the generator set is coef, the carbon intensity CI of the generator set can be obtained by multiplying the two. CI=P*coef.

[0081] On this basis, if it is necessary to calculate the carbon intensity CI of the power plant, the power plant can include N units, and the carbon intensities of the units are CI1, CI2, …, CIn respectively. The carbon intensity CI of the power plant is obtained by accumulating the carbon intensities of the units. The related formula can be CI-Plant(i)=CI1+CI2+…+CIn.

[0082] In summary, the method for calculating the carbon intensity provided by the embodiment can obtain the basic attribute data of the power system, obtain the active power generation amount of the generator set based on the basic attribute data, obtain the initial value of the carbon emission factor of the power generation fuel of the generator set according to the life cycle type of the generator set, the initial value of the carbon emission factor of the power generation fuel is used to indicate the size of the carbon emission amount per unit of power generation, and finally calculate the carbon intensity of the generator set according to the active power generation amount of the generator set and the initial value of the carbon emission factor of the power generation fuel. Since the application can calculate the carbon intensity of the generator set according to the active power generation amount of the generator set and the initial value of the carbon emission factor of the power generation fuel of the generator set, the carbon intensity of the smallest unit of the generator set in the power system can be monitored, thereby reducing the monitoring granularity of the carbon intensity in the entire power system, and further calculating the carbon intensity of different generator sets can also be used to calculate the real-time carbon intensity of each power plant or each region, providing relevant data for subsequent carbon trading of the power system, thereby promoting the development of energy saving and emission reduction work.

[0083] Based on the scheme disclosed in the previous embodiment, the terminal can also implement the method for calculating the carbon intensity in another possible way. Please refer to the following embodiment.

[0084] Please refer to Figure 5 , Figure 5 is a flowchart of a method for calculating the carbon intensity provided by another exemplary embodiment of the application. The method for calculating the carbon intensity can be applied in the terminal shown in the above. In Figure 5 , the method for calculating the carbon intensity comprises:

[0085] Step 510, obtaining the basic attribute data of the power system.

[0086] In the embodiment of the present application, the execution process of step 510 is the same as the execution process of step 410 and will not be repeated here.

[0087] After executing step 510 , the present application can execute steps 521 and 522 , or steps 531 , 532 , and 533 .

[0088] Step 521: When the life cycle type is false, a first preset mapping relationship is used to determine the intermediate power generation fuel carbon emission factor corresponding to the type of the generator set.

[0089] In this example, the generator set's lifecycle type is false, indicating that the initial value of the generator set's power generation fuel carbon emission factor does not need to be considered during its lifecycle. In this scenario, the terminal has a pre-set mapping relationship. Based on the generator set type specified in the first pre-set mapping relationship, the terminal can determine the intermediate power generation fuel carbon emission factor corresponding to the generator set type.

[0090] Step 522: Determine the intermediate power generation fuel carbon emission factor as the initial value of the power generation fuel carbon emission factor corresponding to the type of the power generation unit.

[0091] In this case, since there is no need to consider the entire life cycle of the power generation unit, the terminal will directly determine the intermediate power generation fuel carbon emission factor as the initial value of the power generation fuel carbon emission factor.

[0092] For example, when the terminal does not consider the entire life cycle of the generator set, the first preset mapping relationship may be as shown in Table 1.

[0093]

[0094] Table 1

[0095] It should be noted that the process shown in Table 1 can be summarized as follows: the terminal obtains the type of generator set, which indicates the input power used by the generator set. This input power includes at least one of thermal energy, hydraulic potential energy, wind kinetic energy, solar energy, and nuclear energy. The terminal then determines the intermediate power generation fuel carbon emission factor corresponding to the generator set type based on the records of the first preset mapping relationship.

[0096] In this scenario, the terminal directly uses the intermediate power generation fuel carbon emission factor determined by the unit type as the initial value of the power generation fuel carbon emission factor. For example, the power generation fuel carbon emission factor can be denoted as coef.

[0097] Due to the different fuel conditions of thermal power units, the intermediate power generation fuel carbon emission factors are different. The embodiment of the present application can determine the intermediate power generation fuel carbon emission factor set corresponding to the thermal power unit according to the record of the first preset mapping relationship when the input energy used by the power generation unit includes thermal energy, that is, when the power generation unit is a thermal power unit, the intermediate power generation fuel carbon emission factor set is a set including n integers, where n is a positive integer; obtain the thermal power carbon emission level in the power system to which the thermal power unit belongs, and the thermal power carbon emission level is used to indicate the carbon emissions when the thermal power unit generates unit electricity; determine the intermediate power generation fuel carbon emission factor corresponding to the thermal power carbon emission level from the intermediate power generation fuel carbon emission factor set according to the second preset mapping relationship, and the second preset mapping relationship is associated with the power system to which the thermal power unit belongs.

[0098] In a specific embodiment, when the unit type is a thermal power unit, this application determines the intermediate power generation fuel carbon emission factor as an integer value x, where x is in the range [80, 90]. Subsequently, this application obtains the thermal power level of the administrative division where the thermal power unit is located and determines the specific value of x based on the thermal power level and the thermal power unit's own subdivided thermal power model.

[0099] For example, a thermal power unit belongs to Administrative Region A, which has four thermal power grades: Q1, Q2, Q3, and Q4. Q1 represents conventional coal-fired units of 300MW and above; Q2 represents conventional coal-fired units of 300MW and below; Q3 represents unconventional coal-fired units; and Q4 represents gas-fired units.

[0100] On this basis, this application makes the Q1 level correspond to the intermediate power generation fuel carbon emission factor of 90, the Q2 level correspond to the intermediate power generation fuel carbon emission factor of 87, the Q3 level correspond to the intermediate power generation fuel carbon emission factor of 83, and the Q4 level correspond to the intermediate power generation fuel carbon emission factor of 80.

[0101] It should be noted that the above scheme is only an example of the method for determining the intermediate power generation fuel carbon emission factor when the thermal power level of the administrative region is divided into 4 levels. As the administrative regions are different, the scheme provided in this application can meet the needs of administrative regions with up to 11 thermal power levels to determine the intermediate power generation fuel carbon emission factor. If the thermal power levels exceed 11, this scheme can use a method in which multiple thermal power levels correspond to the same intermediate power generation fuel carbon emission factor to determine the intermediate power generation fuel carbon emission factor. For example, if the thermal power levels are divided into 22, then 2 thermal power levels are equal to the same intermediate power generation fuel carbon emission factor. For example, thermal power level q1 and thermal power level q2 both correspond to an intermediate power generation fuel carbon emission factor of 90.

[0102] Step 531: When the lifecycle type is true, obtain the basic power generation fuel carbon emission factor of the generator set.

[0103] Among them, the basic power generation fuel carbon emission factor is used to indicate the estimated value of the carbon emissions generated by the power generation unit before it is put into operation.

[0104] Optionally, this application takes into account the entire life cycle of the generator set. Since the entire life cycle includes the carbon emission intensity generated by the generator set during production, transportation, etc., it is necessary to input a basic power generation fuel carbon emission factor, which includes planning data and equipment manufacturers. Optionally, the terminal can read the carbon emission intensity generated by the generator set during the production process from the equipment factor library. Subsequently, the terminal determines the carbon emission intensity generated during transportation based on the transportation method and transportation distance of the generator set. Among them, the transportation distance is the distance from the manufacturer of the generator set to the deployment location.

[0105] Step 532: Using the first preset mapping relationship, determine the intermediate power generation fuel carbon emission factor corresponding to the type of the generator set.

[0106] It should be noted that the execution process of step 532 is similar to that of step 521 and will not be repeated here.

[0107] Step 533: The sum of the intermediate power generation fuel carbon emission factor and the basic power generation fuel carbon emission factor is determined as the initial value of the power generation fuel carbon emission factor corresponding to the type of the generator set.

[0108] In this example, the intermediate power generation fuel carbon emission factor and the basic power generation fuel carbon emission factor calculated in the above steps are added together to obtain the initial value of the power generation fuel carbon emission factor corresponding to the type of power generation unit.

[0109] For example, the intermediate power generation fuel carbon emission factor of the generator set E1 is F1, and the basic power generation fuel carbon emission factor of the generator set E1 is F2, then the initial value of the power generation fuel carbon emission factor of the generator set E1 is (F1+F2).

[0110] Step 540 , calculating the carbon emission intensity of the generator set based on the active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel.

[0111] In this application, the execution process of step 540 is the same as the execution process of step 430, and will not be repeated here.

[0112] Step 551: Obtain the load of the generator set.

[0113] In this example, the terminal can obtain the load of the generator set.

[0114] In one possible manner, the load of the generator set may be the real-time load of the generator set.

[0115] In another possible manner, the load of the generator set may be an average load in a specified period of time.

[0116] In step 552 , the load of the generator set is divided by the carbon emission intensity of the generator set, and the resulting quotient is the carbon intensity factor of the generator set.

[0117] Among them, the carbon intensity factor is used to indicate the carbon emissions generated by the unit power generation of the generator set, and the carbon intensity factor is positively correlated with the initial value of the carbon emission factor of the power generation fuel.

[0118] In this example, the terminal will obtain the load and carbon emission intensity of the generator set within the same statistical time dimension. For example, the statistical time scale can be real-time statistics, or the statistical time scale can be data within the past period A.

[0119] After obtaining the load of the generator set and the carbon emission intensity of the generator set at the same statistical time, the terminal will divide the load of the generator set by the carbon emission intensity of the generator set, and the quotient obtained is the carbon intensity factor of the generator set.

[0120] It should be noted that the carbon intensity factor of a power plant and the carbon intensity factor within a designated area can both be calculated using this method, and will not be elaborated here.

[0121] Step 561: Acquire the spatiotemporal statistical range, where the spatiotemporal conditions include a time range and / or a spatial range.

[0122] In this example, the spatiotemporal statistical range can be obtained in a variety of ways. In one possible way, the terminal obtains it through a user interface (UI). In another possible way, the terminal obtains it through a display screen identifier of the currently displayed data.

[0123] Optionally, the terminal can select the spatiotemporal statistical range by clicking a mouse in the UI, selecting a menu, or other methods. In one possible embodiment, the spatiotemporal statistical range includes both the time range and the spatial range of the statistical data. In another possible embodiment, the spatiotemporal statistical range includes only the time range, and the spatial range is the default data. In yet another possible embodiment, the spatiotemporal statistical range includes only the spatial range, and the time range is the default data.

[0124] Optionally, since this application can be integrated into an executable application. The application supports the ability to display related windows on M display screens at the same time. Wherein, M can be an integer less than 100. During the initialization phase, the display screen identifier can be bound to the spatiotemporal statistical range. For example, display screen S1 is bound to the real-time data of County A, display screen S2 is bound to the weekly data of County A, display screen S3 is bound to the real-time data of County B, and display screen S4 is bound to the real-time data of Power Plant E1.

[0125] It should be noted that the above binding relationship is only a possible implementation method and does not limit the specific implementation method of this application.

[0126] Step 562: determine the generator sets within the spatiotemporal statistical range as the target generator set group.

[0127] In this example, the terminal can determine the generator sets participating in power generation as the target generator set group based on the spatiotemporal statistical range. The target generator set group includes at least one generator set.

[0128] Optionally, if the terminal determines that no generator set exists in the target generator group, that is, no generator set participating in power generation is within the spatiotemporal statistical range, the terminal terminates the calculation process and returns a prompt message. The prompt message can be used to prompt the user to check whether the line is abnormal and to indicate that no generator set is participating in power generation within the spatiotemporal statistical range.

[0129] Schematically, if the spatial dimension is included in the scope of spatiotemporal statistics, the relevant carbon emission intensity measurement process is as follows.

[0130] In one possible application, the spatial dimension can be national, regional, provincial, municipal, county, or township. First, the terminal can sum the loads in the spatial dimension to obtain the spatial load sum (Sum-Load). Second, the terminal will accumulate the carbon emission intensity of the generator sets within the spatial dimension to obtain the total carbon emission intensity (SumCI-Plant) of the generator sets. Subsequently, the terminal calculates the carbon intensity factor for the spatial dimension. During the calculation process, the terminal divides the total carbon emission intensity (SumCI-Plant) of the generator sets by the spatial load sum (Sum-Load) to obtain the spatial carbon intensity factor (C-factor).

[0131] Schematically, if the time dimension is included in the scope of spatiotemporal statistics, the relevant carbon emission intensity measurement process is as follows.

[0132] In one possible application, the time dimension can be every 15 minutes, every hour, every day, every ten days, every month, every quarter, or every year. It should be noted that the time periods involved in these time dimensions can include only past periods or both past and future periods. The data corresponding to past periods is measured data, while future periods can refer to the data from the same period in the past.

[0133] For example, if the time dimension is every 15 minutes or every hour, the data corresponding to the future time period can be the data of the same time period in the previous day's historical data. In other words, the data of the same time period yesterday can be used to predict the data of the same time period today.

[0134] For example, if the time dimension is daily, the data corresponding to the future time period can be the data of the same day in the previous month in the historical data. For example, the data on the 18th of this month can be predicted based on the data on the 18th of the previous month.

[0135] In an annual statistical method, this application can collect carbon emissions data on an hourly basis. If a year has 365 days, there are 365 * 24 = 8760 time series data points. The terminal can connect these 8760 data points in chronological order to obtain seasonal and peak-valley carbon emissions data for the subject throughout the year.

[0136] Please refer to Figure 6 , Figure 6 This application is based on Figure 5 The embodiment shown provides a schematic diagram of carbon emission intensity monitoring. Figure 6 In the , users can select the statistical area and the statistical time. Then, the system can automatically display the carbon emission intensity of the specified time and area. Figure 6 In the example, the time is from time 1 to time 2, and the region is sub-region A3. The carbon emission intensity of the region is 47.54, and the power generation of each type can also be displayed in real time. Figure 6 An adjustment box for the carbon emission factor of power generation fuel is provided. Users can change the carbon emission factor of power generation fuel according to their own needs and then recalculate.

[0137] Step 563 , accumulating the carbon emission intensity of each generator set in the target generator set group to obtain the carbon emission intensity corresponding to the spatiotemporal statistical range.

[0138] In this example, the terminal can accumulate the carbon emission intensity of each generator set in the target group of units, and use the accumulated carbon emission intensity as the carbon emission intensity corresponding to the spatiotemporal statistical range.

[0139] Optionally, step 536 can be replaced by steps (1), (2) and (3) to achieve the effect of obtaining the carbon emission intensity corresponding to the spatiotemporal statistical range.

[0140] Step (1), obtain the equivalent load within the time and space statistics range.

[0141] It should be noted that the equivalent load indicates the external devices supplying power to the target generator group. The power grid corresponding to the specified spatiotemporal statistical range includes ports connected to external power grids. This external power grid may be a power grid at the same level, a lower level, or a higher level. Following power dispatch instructions, the external power grid can either draw power from the power grid corresponding to the spatiotemporal statistical range or provide power to the power grid corresponding to the spatiotemporal statistical range.

[0142] Based on the above analysis, this application treats the external power grid outside the power grid corresponding to the spatiotemporal statistical range as an equivalent load. Since the value of the equivalent load can be either positive or negative, the equivalent load can logically represent the external power grid.

[0143] Schematically, if the value of the equivalent load is a negative number, the equivalent load can be equivalent to a generator.

[0144] Step (2) is to obtain the bus carbon emission intensity on the power supply path of the equivalent load, where the bus carbon emission intensity is used to indicate the sum of the carbon emission intensity of each section of the bus and the carbon emission intensity of the transformer.

[0145] In this example, the carbon emission intensity of the path from the generator set to the equivalent load within the spatiotemporal statistical scope needs to be calculated. One possible approach involves calculating the line carbon intensity factor and the transformer carbon intensity factor for the power transmission path. In other words, the carbon emission intensity of the path from the generator set to the equivalent load within the spatiotemporal statistical scope is the sum of the line carbon intensity factor and the transformer carbon intensity factor for the optimal power transmission path from the generator set to the equivalent load within the spatiotemporal statistical scope.

[0146] Schematically, the carbon emission intensity of a busbar can be obtained by topologically integrating the carbon emission factors of the lines and the carbon intensity factors of the transformers under the busbar. In one possible application scenario, the present application can calculate the carbon intensity factors of each transmission line and transformer through topological fusion. First, the terminal implements topological fusion in the power grid based on the topological relationship. Topological fusion includes the topological structure of the power generation grid, transmission grid, distribution grid and user grid and the connection relationship between them, the physical connection between the user and the grid, and the specific installation location of various sensors and data acquisition devices in the grid, etc. The fusion of grid space data. For example, a generator set has a power supply path from the generator set outlet to the 500kV transformer. According to Kirchhoff's law, the carbon emission intensity of the AC lines and transformers on this power supply path is the same as the carbon emission intensity of the power plant. If there are M generator sets within the calculation range, there are M power supply paths. The terminal accumulates and sums all substations and AC lines on the power supply path.

[0147] The following example illustrates how to obtain bus carbon emission intensity. Suppose the carbon emission intensity of the Gen-i generator in a power grid within the spatiotemporal statistical range is CIi, and it passes through j AC lines and m transformers. The AC lines are numbered Line-1, Line-2, ..., Line-j, and the transformers are numbered Trans-1, Trans-2, ..., Trans-m. Their carbon emission intensities are all CIi.

[0148] The above statistical method is performed for a single generator set. Subsequent statistics can be performed for all generator sets in the grid within the temporal and spatial statistical range to obtain the carbon emission intensity of each generator set for each power supply path and transformer. Finally, the carbon emission intensity of all power supply paths and all transformers is summed to obtain the carbon emission intensity of all power supply paths and all transformers.

[0149] Step (3) accumulates the carbon emission intensity of each generator set in the target generator group, adds the obtained sum to the bus carbon emission intensity, and obtains the carbon emission intensity in the spatiotemporal statistical range.

[0150] It should be noted that bus carbon emission intensity represents the carbon emission intensity of equivalent load. Therefore, the carbon emission intensity of the power grid corresponding to the spatiotemporal statistical range will be the sum of the carbon emission intensity of each generator in the target unit group and the bus carbon emission intensity.

[0151] Among them, the bus carbon emission intensity is used to indicate the bus carbon emission intensity corresponding to all equivalent loads in the temporal and spatial statistical range.

[0152] It should be noted that this application can also adjust the carbon emission intensity of the measured object through steps (a) and (b). The measured object can be a generator set, a power plant, a regional power grid, or a company, etc., and this application does not limit this. Since this application can calculate the carbon emission intensity of the generator set, it can also calculate the carbon emission intensity of the power plant, regional power grid, or company.

[0153] Step (a), obtaining the number of green certificates of the object to be tested from the carbon exchange.

[0154] It should be noted that to ensure the reproducibility of system data, this application can verify the Green Certificates of the subject being tested on the carbon exchange after obtaining the Green Certificates. Optionally, this verification method includes cryptographic verification with the carbon exchange. Alternatively, if the Green Certificates are blockchain-based, verification can be performed using blockchain verification.

[0155] Step (b) adjusting the carbon intensity factor of the object being measured according to a preset factor adjustment rule.

[0156] In this example, if the original carbon intensity factor of the measured object is A, and the measured object purchases a green certificate from elsewhere, the carbon intensity factor of the measured object changes to B, which is less than A.

[0157] If the original carbon intensity factor of the measured object is A, and the measured object purchases a green certificate from elsewhere, the carbon intensity factor of the measured object will change to C, which is greater than A.

[0158] The factor adjustment rule is used to specify the relationship between the number of green certificates and the adjustment range of the carbon intensity factor. In one possible approach, the number of green certificates indicated by the factor adjustment rule is linearly related to the adjustment range of the carbon intensity factor.

[0159] In another possible approach, the number of green certificates indicated by the factor adjustment rule is in a nonlinear relationship with the adjustment range of the carbon intensity factor. In this scenario, when the carbon intensity factor A of the measured object is greater than the first threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P1. When the carbon intensity factor A of the measured object is less than or equal to the first threshold value and greater than the second threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P2. When the carbon intensity factor A of the measured object is less than or equal to the second threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P3. Among them, the first threshold value is greater than the second threshold value, P1>P2>P3.

[0160] It should be noted that when the carbon intensity factor of the measured object is too high, the number of green certificates required to reduce the unit carbon intensity factor is large; when the carbon intensity factor of the measured object is low, the number of green certificates required to reduce the unit carbon intensity factor is small. This can encourage the measured object to pay attention to maintaining its own carbon intensity factor at a reasonable level.

[0161] Optionally, the terminal may also utilize a genetic algorithm to mine high-frequency factors to form a carbon intensity factor correction knowledge base, which may be used together with the above-mentioned factor adjustment rules to adjust the carbon intensity factor of the measured object.

[0162] It should be noted that based on the statistical method of carbon emission intensity provided by this application, the terminal can draw a carbon trajectory more conveniently. The carbon trajectory display can be displayed through graphical components including task process nodes and connecting lines. In the graphical display, the terminal can also attach configuration information next to the corresponding object for display. Among them, the configuration information includes process node participant configuration, task process variables and task process condition configuration. When the results are counted, the carbon emission intensity is displayed on a map of the power grid by time, place and business, and finally a statistical analysis report is generated to provide decision-making information for professionals, so as to facilitate the refined and efficient management of carbon emissions.

[0163] In summary, this embodiment not only calculates the carbon emission intensity of a generator set based on data provided by the power grid, but also allows for flexible switching between spatial and temporal statistical dimensions. Because the statistical data is based on real-time data from the power grid where the generator set resides, it is objective and timely, facilitating further carbon emissions trading and carbon emission labeling required for product production.

[0164] The method for calculating carbon emission intensity provided in this embodiment can also enable users to more intuitively understand the flow of carbon emission intensity through a carbon trajectory diagram.

[0165] The method for calculating carbon emission intensity provided in this embodiment can also take into account the existence of externally input electric energy in the power grid, and calculate the carbon emission intensity of the electric energy at the same time, ensuring that each granularity in the power grid can provide correct carbon emission data.

[0166] See Figure 7 , Figure 7 This is a flow chart of a method for tracking regional carbon footprints provided by an exemplary embodiment of the present application. Figure 7 The solution shown can be applied in Figure 1 In the terminal shown. Figure 7 In the case of a project, methods for tracking the carbon footprint of the region may include:

[0167] Step 701: Select a generator set within a target area.

[0168] In this example, the target area can be either an administrative region or a commercial area divided according to the affiliation of power plants, which is not limited in this embodiment of the application. The administrative region can be a country, province, city, county, or township. Commercial areas can be counted based on the distribution of power plants. There is no specific standard for commercial demarcation, so it will not be listed here.

[0169] In this example, after the user selects a target area, the terminal can automatically determine the generator sets within that target area. It should be noted that in one possible approach, the generator sets are generator sets located within the target area. In another possible approach, the generator sets are generator sets belonging to the target area. This application may adopt any of these criteria and is not limited thereto.

[0170] Step 702: For the selected generator set, a depth-first search strategy is used.

[0171] In this example, the terminal uses a depth-first search strategy for the selected generator set in the target area to determine the flow of carbon emission intensity after the generator set generates electricity. In other words, this step can determine the trajectory of carbon emission intensity generated by the selected generator set.

[0172] Step 703: Generate a corresponding carbon trajectory tracking graph based on the search results.

[0173] In this example, the terminal can generate a corresponding carbon trajectory tracking map based on the carbon emission intensity trajectory generated by a single generator set. It should be noted that since this embodiment aims to draw a carbon trajectory tracking map for the target area, each generator set can be processed by drawing a new carbon trajectory tracking map on top of the carbon trajectory tracking map generated by the previous generator set. This carbon trajectory tracking map is a superposition of the carbon emission intensity trajectories generated by each generator set.

[0174] Step 704: Determine whether all generator sets have been searched.

[0175] After the terminal has searched all the generator sets, the process ends and a carbon trajectory tracking map for the region is generated. If there are still generator sets that have not been searched, the process jumps to step 702 and continues until all the generator sets have been searched.

[0176] To sum up, the regional carbon footprint tracking method provided in the embodiment of the present application can automatically traverse and count the generator sets in the target area after the user selects the target area to be counted, and after processing the carbon footprints generated by the generator sets one by one, generate an overall carbon footprint map of the target area, thereby improving the efficiency of obtaining the carbon footprint tracking map of the target area.

[0177] SeeFigure 8 , Figure 8 This is a flowchart of a carbon intensity calculation method provided by an exemplary embodiment of the present application. Figure 8 The solution shown can be applied in Figure 1 In the terminal shown. Figure 8 The carbon intensity calculation method may include:

[0178] Step 801: Collect and analyze power system data.

[0179] Step 802: Establish a carbon data analysis task model, allocate analysis tasks, and pre-process operating resources.

[0180] Step 803: Perform data normalization and data cleaning based on the power system data.

[0181] Step 804 : Based on the carbon data analysis task model, the normalized and cleaned power system data is processed to obtain the corresponding carbon emission intensity.

[0182] Step 805: Call the generated carbon trajectory tracking diagram to display the carbon trace and the corresponding carbon emission intensity.

[0183] Step 806 , determining whether all the generator sets have completed displaying the carbon footprint and the corresponding carbon emission intensity.

[0184] If all generator sets have completed displaying their carbon footprints and corresponding carbon emission intensities, the terminal ends the process. If there are still generator sets that have not completed displaying their carbon footprints and corresponding carbon emission intensities, the terminal jumps to step 805 and continues executing the process until all generator sets have completed displaying their carbon footprints and corresponding carbon emission intensities.

[0185] In summary, in the embodiment of the present application, the terminal can automatically clean and normalize the power system data after collecting it. After pre-establishing a carbon data analysis task model, the computing resources are pre-processed according to the model, and then the normalized power system data is imported into the model for calculation. After all data processing is completed, the corresponding carbon emission intensity data can be displayed together with the carbon footprint, so that the carbon footprint can be displayed together with the carbon emission intensity data, making it easier for users to understand the quantified indicators of the measured object in the field of environmental protection from the above two dimensions.

[0186] See Figure 9 , Figure 9 This is a flowchart of a method for calculating carbon intensity by site provided by an exemplary embodiment of the present application. Figure 9 The solution shown can be applied in Figure 1 In the terminal shown. Figure 9 The site-specific carbon intensity calculation method may include:

[0187] Step 901: Read the organizational structure chart of the generator group in the target area.

[0188] Step 902 , reading the actual power generation of the hydropower units, thermal power units, wind power units, photovoltaic units, nuclear power units and biomass energy storage units in the target area.

[0189] Step 903: Read the power load of the target area.

[0190] Step 904: Calculate the carbon emission intensity of the target area.

[0191] Step 905: Summarize and accumulate the carbon emission intensity of each sub-region in the target region.

[0192] Step 906: Determine whether there are any sub-regions that have not been counted.

[0193] If there are no uncounted sub-regions, the process ends. If there are uncounted sub-regions, the process jumps to step 902 to continue counting until all sub-regions are counted and the carbon emission intensity of the target region is obtained.

[0194] To sum up, the embodiment of the present application can count the carbon emission intensity according to different regions separately. After the carbon emission intensity of each sub-region in the target area is counted, the total carbon emission intensity of the target area is summarized, thereby achieving the simultaneous acquisition of carbon emission intensity at two statistical levels, namely, sub-region and target area, and improving the three-dimensionality of statistical data.

[0195] The following are device embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0196] Please refer to Figure 10 , Figure 10 This is a block diagram of a device for calculating carbon emission intensity provided by an exemplary embodiment of the present application. The device for calculating carbon emission intensity can be implemented as all or part of a terminal through software, hardware, or a combination of both. The device includes:

[0197] A first acquisition module 1010 is configured to acquire basic attribute data of the power system and obtain active power generation of the generator set based on the basic attribute data;

[0198] A second acquisition module 1020 is configured to acquire an initial value of a carbon emission factor of a power generation fuel of the power generation unit according to a life cycle type of the power generation unit, wherein the initial value of the carbon emission factor of the power generation fuel is used to indicate the amount of carbon emissions generated per unit of power generation;

[0199] The data calculation module 1030 is used to calculate the carbon emission intensity of the generator set based on the active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel.

[0200] In an optional embodiment, the device also includes a first execution module for obtaining the load of the generator set; dividing the load of the generator set by the carbon emission intensity of the generator set, and the resulting quotient is the carbon intensity factor of the generator set, and the carbon intensity factor is used to indicate the carbon emissions generated per unit power generation of the generator set, and the carbon intensity factor is positively correlated with the initial value of the carbon emission factor of the power generation fuel.

[0201] In an optional embodiment, the second acquisition module 1020 is configured to, when the lifecycle type is false, use a first preset mapping relationship to determine an intermediate power generation fuel carbon emission factor corresponding to the type of the generator set; and determine the intermediate power generation fuel carbon emission factor as the initial value of the power generation fuel carbon emission factor corresponding to the type of the generator set. Alternatively, the second acquisition module 1020 is configured to, when the lifecycle type is true, obtain a basic power generation fuel carbon emission factor for the generator set, the basic power generation fuel carbon emission factor being used to indicate an estimated value of carbon emissions generated by the generator set before it is put into operation; use a first preset mapping relationship to determine the intermediate power generation fuel carbon emission factor corresponding to the type of the generator set; and determine the sum of the intermediate power generation fuel carbon emission factor and the basic power generation fuel carbon emission factor as the initial value of the power generation fuel carbon emission factor corresponding to the type of the generator set.

[0202] In an optional embodiment, the second acquisition module 1020 is used to obtain the type of the generator set, and the type of the generator set is used to indicate the input power used by the generator set, and the input power includes at least one of thermal energy, hydraulic potential energy, wind kinetic energy, solar energy and nuclear energy; according to the record of the first preset mapping relationship, the intermediate power generation fuel carbon emission factor corresponding to the type of the generator set is determined.

[0203] In an optional embodiment, the second acquisition module 1020 is used to determine the intermediate power generation fuel carbon emission factor set corresponding to the thermal power generation group according to the record of the first preset mapping relationship when the input energy used by the generator group includes the thermal heat energy and the generator group is a thermal power generation group, wherein the intermediate power generation fuel carbon emission factor set is a set including n integers, where n is a positive integer; obtain the thermal power carbon emission level in the power system to which the thermal power generation group belongs, wherein the thermal power carbon emission level is used to indicate the carbon emissions when the thermal power generation group generates unit electricity; determine the intermediate power generation fuel carbon emission factor corresponding to the thermal power carbon emission level from the intermediate power generation fuel carbon emission factor set according to the second preset mapping relationship, wherein the second preset mapping relationship is associated with the power system to which the thermal power generation group belongs.

[0204] In an optional embodiment, the device also includes a second execution module for obtaining a spatiotemporal statistical range, wherein the spatiotemporal conditions include a time range and / or a spatial range; determining the generator sets within the spatiotemporal statistical range as a target generator group; and accumulating the carbon emission intensity of each generator set in the target generator group to obtain the carbon emission intensity corresponding to the spatiotemporal statistical range.

[0205] In an optional embodiment, the second execution module is used to obtain the equivalent load within the spatiotemporal statistical range, the equivalent load is used to indicate the external equipment that supplies power to the target group of units; obtain the bus carbon emission intensity on the power supply path of the equivalent load, the bus carbon emission intensity is used to indicate the sum of the carbon emission intensity of each section of the line included in the bus and the carbon emission intensity of the transformer; accumulate the carbon emission intensity of each generator set in the target group of units, add the obtained sum to the bus carbon emission intensity, and obtain the carbon emission intensity within the spatiotemporal statistical range.

[0206] In summary, this embodiment not only calculates the carbon emission intensity of a generator set based on data provided by the power grid, but also allows for flexible switching between spatial and temporal statistical dimensions. Because the statistical data is based on real-time data from the power grid where the generator set resides, it is objective and timely, facilitating further carbon emissions trading and carbon emission labeling required for product production.

[0207] The method for calculating carbon emission intensity provided in this embodiment can also enable users to more intuitively understand the flow of carbon emission intensity through a carbon trajectory diagram.

[0208] The method for calculating carbon emission intensity provided in this embodiment can also take into account the existence of externally input electric energy in the power grid, and calculate the carbon emission intensity of the electric energy at the same time, ensuring that each granularity in the power grid can provide correct carbon emission data.

[0209] An embodiment of the present application further provides a computer-readable medium storing at least one instruction, wherein the at least one instruction is loaded and executed by the processor to implement the method for calculating carbon emission intensity as described in the above embodiments.

[0210] It should be noted that the device for calculating carbon emission intensity provided in the above embodiment only uses the division of the above functional modules as an example when executing the method for calculating carbon emission intensity. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device for calculating carbon emission intensity provided in the above embodiment and the method for calculating carbon emission intensity are of the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0211] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0212] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0213] The above description is merely an exemplary embodiment that can be implemented in the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for calculating carbon emission intensity, characterized in that: The method comprises: Acquiring basic attribute data of the power system, and obtaining active power generation of the generator set based on the basic attribute data; Obtaining an initial value of the carbon emission factor of the power generation fuel of the power generation set according to the life cycle type of the power generation set, wherein the initial value of the carbon emission factor of the power generation fuel is used to indicate the size of the carbon emissions generated per unit power generation; Calculating the carbon emission intensity of the generator set based on the active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel; Obtaining the load of the generator set; Divide the load of the generator set by the carbon emission intensity of the generator set, and the resulting quotient is the carbon intensity factor of the generator set. The carbon intensity factor is used to indicate the carbon emissions generated per unit power generation of the generator set, and the carbon intensity factor is positively correlated with the initial value of the carbon emission factor of the power generation fuel; Obtain the number of green certificates for the power generation unit from the carbon exchange; The carbon intensity factor of the power generation unit is adjusted according to the preset factor adjustment rules and the modified knowledge base; when the carbon intensity factor A of the power generation unit is greater than the first threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P1; when the carbon intensity factor A of the power generation unit is less than or equal to the first threshold value and greater than the second threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P2; when the carbon intensity factor A of the power generation unit is less than or equal to the second threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P3; wherein, the first threshold value is greater than the second threshold value, P1>P2>P3; the modified knowledge base is a modified knowledge base of the carbon intensity factor formed by mining high-frequency factors using a genetic algorithm; selecting the generator set within the target area; For the selected generator set, a depth-first search strategy is used to obtain the flow direction of the carbon emission intensity after the generator set generates electricity; Based on the search results, a carbon trajectory tracking map of the target area is generated; the carbon trajectory tracking map is a superposition effect of the trajectory of the carbon emission intensity generated by at least one power generation group.

2. The method according to claim 1, characterized in that The obtaining of the initial value of the carbon emission factor of the power generation fuel of the generator set according to the life cycle type of the generator set includes: When the life cycle type is false, a first preset mapping relationship is used to determine the intermediate power generation fuel carbon emission factor corresponding to the type of the generator set; Determining the intermediate power generation fuel carbon emission factor as the initial value of the power generation fuel carbon emission factor corresponding to the type of the generator set; or, If the lifecycle type is true, obtaining a basic power generation fuel carbon emission factor of the power generation unit, where the basic power generation fuel carbon emission factor is used to indicate an estimated value of carbon emissions generated by the power generation unit before it is put into operation; Determining the intermediate power generation fuel carbon emission factor corresponding to the type of the generator set by using a first preset mapping relationship; The sum of the intermediate power generation fuel carbon emission factor and the basic power generation fuel carbon emission factor is determined as the initial value of the power generation fuel carbon emission factor corresponding to the type of the generator set.

3. The method according to claim 2, characterized in that The determining of the intermediate power generation fuel carbon emission factor corresponding to the type of the generator set by using the first preset mapping relationship includes: Obtaining a type of the generator set, where the type of the generator set indicates an input power used by the generator set, and the input power includes at least one of thermal energy, hydraulic potential energy, wind kinetic energy, solar energy, and nuclear energy; The intermediate power generation fuel carbon emission factor corresponding to the type of the generator set is determined according to the record of the first preset mapping relationship.

4. The method according to claim 3, characterized in that In a case where the input energy used by the generator set includes thermal energy, and the generator set is a thermal power generation set, determining the intermediate power generation fuel carbon emission factor corresponding to the type of the generator set according to the record of the first preset mapping relationship includes: Determining, based on the record of the first preset mapping relationship, a set of intermediate power generation fuel carbon emission factors corresponding to the thermal power generation unit, wherein the set of intermediate power generation fuel carbon emission factors is a set including n integers, where n is a positive integer; Obtaining a thermal power carbon emission level in the power system to which the thermal power unit belongs, the thermal power carbon emission level being used to indicate the carbon emissions per unit of electricity generated by the thermal power unit; According to a second preset mapping relationship, the intermediate power generation fuel carbon emission factor corresponding to the thermal power carbon emission level is determined from the intermediate power generation fuel carbon emission factor set, and the second preset mapping relationship is associated with the power system to which the thermal power unit belongs.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Acquire a spatiotemporal statistical range, where the spatiotemporal statistical range includes a time range and / or a spatial range; Determine the generator sets within the spatiotemporal statistical range as target generator sets; The carbon emission intensity of each of the generator sets in the target generator set group is accumulated to obtain the carbon emission intensity corresponding to the spatiotemporal statistical range.

6. The method according to claim 5, characterized in that The accumulating the carbon emission intensity of each of the generator sets in the target generator set group to obtain the carbon emission intensity in the spatiotemporal statistical range includes: Acquire an equivalent load within the spatiotemporal statistical range, where the equivalent load is used to indicate an external device that supplies power to the target machine group; Obtaining a busbar carbon emission intensity on the power supply path of the equivalent load, where the busbar carbon emission intensity is used to indicate the sum of the carbon emission intensities of each section of the busbar and the carbon emission intensity of the transformer; The carbon emission intensity of each of the generator sets in the target generator set group is accumulated, and the obtained sum is added to the bus carbon emission intensity to obtain the carbon emission intensity in the spatiotemporal statistical range.

7. A device for calculating carbon emission intensity, characterized in that: The device comprises: A first acquisition module is configured to acquire basic attribute data of the power system and obtain active power generation of the generator set based on the basic attribute data; A second acquisition module is used to obtain an initial value of the carbon emission factor of the power generation fuel of the power generation set according to the life cycle type of the power generation set, and the initial value of the carbon emission factor of the power generation fuel is used to indicate the size of the carbon emissions generated per unit power generation; a data calculation module, configured to calculate the carbon emission intensity of the generator set based on the active power generation of the generator set and the initial value of the carbon emission factor of the power generation fuel; A first execution module is configured to obtain a load of the generator set; divide the load of the generator set by the carbon emission intensity of the generator set, and the resulting quotient is a carbon intensity factor of the generator set, wherein the carbon intensity factor is used to indicate the carbon emissions generated per unit power generation of the generator set, and the carbon intensity factor is positively correlated with an initial value of the carbon emission factor of the power generation fuel; Wherein, the number of green certificates of the power generation unit is obtained from the carbon exchange; The carbon intensity factor of the power generation unit is adjusted according to the preset factor adjustment rules and the modified knowledge base; when the carbon intensity factor A of the power generation unit is greater than the first threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P1; when the carbon intensity factor A of the power generation unit is less than or equal to the first threshold value and greater than the second threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P2; when the carbon intensity factor A of the power generation unit is less than or equal to the second threshold value, the ratio of the number of green certificates to the adjustment amount of the carbon intensity factor is P3; wherein, the first threshold value is greater than the second threshold value, P1>P2>P3; the modified knowledge base is a modified knowledge base of the carbon intensity factor formed by mining high-frequency factors using a genetic algorithm; selecting the generator set within the target area; For the selected generator set, a depth-first search strategy is used to obtain the flow direction of the carbon emission intensity after the generator set generates electricity; Based on the search results, a carbon trajectory tracking map of the target area is generated; the carbon trajectory tracking map is a superposition effect of the trajectory of the carbon emission intensity generated by at least one power generation group.

8. A terminal, characterized in that: The terminal includes a processor, a memory connected to the processor, and program instructions stored in the memory. When the processor executes the program instructions, the method for calculating carbon emission intensity according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium storing program instructions, characterized in that: When the program instructions are executed by a processor, the method for calculating carbon emission intensity according to any one of claims 1 to 6 is implemented.

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