Method, device, storage medium and equipment for monitoring indirect carbon emissions of electric power

Abstract

The present invention discloses a method, apparatus, storage medium, and device for monitoring indirect carbon emissions from electricity. The method comprises: obtaining line power data for a grid node; generating an input-output table based on the line power data; processing the input-output table to determine a traceability vector for the grid node; and determining the indirect carbon emissions from electricity at the grid node based on the power generation carbon emission coefficient and the traceability vector. This invention addresses the technical problem that existing monitoring methods cannot accurately monitor indirect carbon emissions from electricity in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of real-time carbon emission monitoring, and in particular to a method, device, storage medium and equipment for indirect carbon emission monitoring of electricity. Background Art

[0002] Currently, indirect carbon emissions from electricity consumption, or the amount of CO2 embodied in electricity, are primarily calculated using the average carbon emission factor for power grids. Depending on the target and scope, these factors include regional baseline emission factors, regional average CO2 emission factors, and provincial average CO2 emission factors. Carbon emission factors are calculated on an annual or multi-year basis, reflecting long-term averages. Grid average carbon emission factors are published periodically by relevant authorities, but they have a long time lag and cannot reflect real-time dynamic changes.

[0003] Furthermore, all regions, industries, and businesses must control both direct carbon emissions from primary energy consumption such as coal, oil, and gas, and indirect carbon emissions from secondary energy consumption such as electricity. As the proportion of electricity in final energy consumption and the proportion of clean energy continue to increase, real-time monitoring of indirect carbon emissions will become increasingly important for accurately calculating and providing early warning of the total amount and intensity of carbon emissions from various entities.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] Embodiments of the present invention provide a method, apparatus, storage medium, and device for monitoring indirect carbon emissions from electricity, to at least solve the technical problem that existing monitoring methods cannot monitor indirect carbon emissions from electricity in real time and with high precision.

[0006] According to one aspect of an embodiment of the present invention, a method for monitoring indirect carbon emissions from electricity is provided, including: obtaining line power data of a grid node; generating an input-output table based on the above line power data; processing the above input-output table to determine the traceability vector of the above grid node; and determining the indirect carbon emissions from electricity of the above grid node based on the power generation carbon emission coefficient and the above traceability vector.

[0007] Optionally, before obtaining the line power data of the grid node, the method further includes: determining the target equivalent node and external grid node to be monitored, wherein the target equivalent node is the first grid node in the target monitoring area, and the external grid node is the second grid node having a voltage level greater than or equal to the target equivalent node and connected to the target equivalent node; determining the network loss equivalent node to be monitored, wherein the network loss equivalent node is the third grid node on the connection line between the target equivalent node and the external grid node; wherein the grid node includes the target equivalent node, the external grid node and the network loss equivalent node.

[0008] Optionally, the above-mentioned acquisition of the line power data of the power grid node includes: obtaining the first online power value, the first offline power value and the first node exchange power value of the above-mentioned external power grid node at the target time; obtaining the power supply power value, the power consumption power value and the interconnecting line power value of the above-mentioned target equivalent node at the above-mentioned target time; obtaining the second online power value, the second offline power value and the second node exchange power value of the above-mentioned network loss equivalent node at the above-mentioned target time; wherein, the line power data of the above-mentioned power grid node includes: the above-mentioned first online power value, the above-mentioned first offline power value and the above-mentioned first node exchange power value of the above-mentioned external power grid node, the above-mentioned power supply power value, the above-mentioned power consumption power value and the above-mentioned interconnecting line power value of the above-mentioned target equivalent node, the above-mentioned second online power value, the above-mentioned second offline power value and the above-mentioned second node exchange power value of the above-mentioned network loss equivalent node.

[0009] Optionally, the above-mentioned generation of the input-output table based on the above-mentioned line power data includes: constructing the first input-output table of the above-mentioned external power grid node based on the above-mentioned first online power value, the above-mentioned first offline power value and the above-mentioned first node exchange power value; constructing the second input-output table of the above-mentioned external power grid node based on the above-mentioned power supply power value, the above-mentioned power consumption power value and the above-mentioned interconnection line power value; constructing the third input-output table of the above-mentioned external power grid node based on the above-mentioned second online power value, the above-mentioned second offline power value and the above-mentioned second node exchange power value; wherein the above-mentioned input-output table includes: the above-mentioned first input-output table, the above-mentioned second input-output table and the above-mentioned third input-output table.

[0010] Optionally, the above-mentioned processing of the input-output table to determine the traceability vector of the above-mentioned power grid node includes: determining the power consumption coefficient matrix based on the above-mentioned input-output table; and selecting the data of the preset column from the above-mentioned power consumption coefficient matrix as the above-mentioned traceability vector.

[0011] Optionally, the above-mentioned determination of the indirect carbon emissions of electricity of the above-mentioned grid node based on the power generation carbon emission coefficient and the above-mentioned traceability vector includes: determining the above-mentioned power generation carbon emission coefficient based on the historical power generation carbon emission coefficient and the above-mentioned line power data; determining a preset monitoring time scale; and using a preset calculation formula to determine the above-mentioned indirect carbon emissions of electricity of the above-mentioned grid node based on the above-mentioned power generation carbon emission coefficient and the above-mentioned preset monitoring time scale.

[0012] According to another aspect of an embodiment of the present invention, a device for monitoring indirect carbon emissions from electricity is also provided, including: an acquisition module for acquiring line power data of a power grid node; a generation module for generating an input-output table based on the above-mentioned line power data; a first determination module for processing the above-mentioned input-output table to determine the traceability vector of the above-mentioned power grid node; and a second determination module for determining the amount of indirect carbon emissions from electricity of the above-mentioned power grid node based on the power generation carbon emission coefficient and the above-mentioned traceability vector.

[0013] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is provided. The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executed by any one of the above-mentioned methods for monitoring indirect carbon emissions from electricity.

[0014] According to another aspect of an embodiment of the present invention, a processor is further provided, and the processor is used to run a program, wherein the program is configured to execute any one of the above-mentioned methods for monitoring indirect carbon emissions from electricity when running.

[0015] According to another aspect of an embodiment of the present invention, an electronic device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any one of the above-mentioned methods for monitoring indirect carbon emissions from electricity.

[0016] In an embodiment of the present invention, by acquiring line power data of a grid node; generating an input-output table based on the line power data; processing the input-output table to determine the traceability vector of the grid node; and determining the indirect carbon emissions of electricity of the grid node based on the power generation carbon emission coefficient and the traceability vector, the purpose of converting the monitored grid current into the input-output of each node, analyzing the input-output using mathematical economics, and calculating the traceability vector is achieved, thereby achieving the technical effect of combining different power generation carbon emission coefficients and calculating the real-time indirect carbon emissions of electricity in the region through the traceability vector, thereby solving the technical problem that the existing monitoring method cannot monitor the indirect carbon emissions of electricity in real time and with high precision. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 is a flow chart of a method for monitoring indirect carbon emissions from electricity according to an embodiment of the present invention;

[0019] Figure 2 is a schematic diagram of an optional real-time monitoring method for power carbon emissions based on input-output analysis according to an embodiment of the present invention;

[0020] Figure 3 3 is a schematic structural diagram of an indirect carbon emission monitoring device for electric power according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] Example 1

[0024] According to an embodiment of the present invention, an embodiment of a method for monitoring indirect carbon emissions from electricity is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0025] Figure 1FIG. 1 is a flow chart of a method for monitoring indirect carbon emissions from electricity according to an embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0026] Step S102, obtaining line power data of the grid node;

[0027] Step S104: generating an input-output table based on the line power data;

[0028] Step S106: Process the input-output table to determine the traceability vector of the power grid node.

[0029] Step S108: determining the indirect carbon emissions of electricity of the above-mentioned grid node based on the power generation carbon emission coefficient and the above-mentioned traceability vector.

[0030] In an embodiment of the present invention, the executor of the indirect carbon emission monitoring method for electricity provided in the above steps S102 to S108 is a carbon emission monitoring system, which uses the above monitoring system to obtain real-time line power data corresponding to the electrical nodes and equivalent nodes of the grid involved, and uses the input-output analysis method of mathematical economics to generate an input-output table based on the above line power data to achieve the power structure traceability corresponding to the power consumption of the equivalent nodes in the region, and obtain the traceability vector through calculation; finally, combined with the carbon emission coefficients of different power sources, the real-time indirect carbon emissions of electricity in the region are calculated through the traceability vector.

[0031] It should be noted that, based on the hierarchical and zoning characteristics of the power grid, the target area (i.e., the target monitoring area) is treated as an equivalent node, eliminating the need for monitoring internal power flow. Furthermore, only power flow above the external interconnection voltage level is considered, avoiding monitoring the entire external power flow. This effectively simplifies the system and facilitates real-time monitoring. Furthermore, the carbon emission coefficient for power generation can be used over a long timescale corresponding to an annual period to address the difficulty in obtaining basic monitoring data.

[0032] As an optional embodiment, Figure 2 The schematic diagram of the real-time monitoring method of electricity carbon emissions based on input-output analysis is shown. The real-time data corresponding to the electrical nodes and equivalent nodes of the power grid involved in real-time monitoring are converted into an input-output table suitable for the input-output analysis method. The input-output analysis method of mathematical economics is used to trace the power structure corresponding to the power consumption of the regional equivalent nodes, and the traceability vector is calculated. Combined with the carbon emission coefficients of different power sources, the real-time indirect carbon emissions of the region are calculated through the traceability vector.

[0033] It should be noted that the grid flow monitoring values are collated based on the input-output analysis method. The grid flow includes active power P and reactive power Q. In the embodiment of the present application, only the active power P corresponding to each node can be obtained. The grid flow node is defined as the social production department in the input-output method, and the flow of electricity is processed as the exchange of products between departments. In order to implement carbon emission monitoring of the electricity used in the target area, it is necessary to consider the entire region as a whole, and treat this region as an equivalent node in the grid flow, which helps to simplify the consideration of internal power supply and load conditions. The grid nodes outside the region only consider the corresponding nodes of the grid grid above the highest voltage level of the regional network, which reflects the layered characteristics of the grid and lays a data foundation for the structural traceability of the external power in the region.

[0034] Alternatively, input-output analysis is a structural approach in economics. Through multi-sectoral design, it reflects the interconnectedness between sectors, which essentially lies in complete interconnection. With the targets set for indirect carbon emissions indicators, the construction of a new power system has become an inevitable requirement. This means that the proportion of new and clean energy in electricity production will further increase. Considering the intermittent and volatile characteristics of wind and photovoltaic power generation will also mean a more dynamic power balance on a larger scale. When calculating the indirect carbon emissions of a region's electricity consumption, it is necessary to fully consider the structure of the electricity sources, especially for regions with a large proportion of electricity received, such as large receiving-end power grids. Applying input-output analysis can simply and effectively trace the structural source of regional electricity consumption.

[0035] Through the embodiments of the present invention, a real-time monitoring method for power carbon emissions based on input-output analysis will monitor the electrical flow and regard it as the input-output of each node. The transmission between nodes will be expressed by "intermediate use", and the off-grid power will be expressed by "final use". The processing brought by the grid flow will be regarded as a network loss equivalent node, and the line network loss will be expressed by "final use", so as to achieve the tracing of the power consumption structure of the target area and further realize the real-time and high-precision monitoring of regional indirect carbon emissions.

[0036] In an optional embodiment, before obtaining the line power data of the grid node, the method further includes: determining the target equivalent node and the external grid node to be monitored, wherein the target equivalent node is the first grid node in the target monitoring area, and the external grid node is the second grid node having a voltage level greater than or equal to the target equivalent node and connected to the target equivalent node; determining the network loss equivalent node to be monitored, wherein the network loss equivalent node is the third grid node on the connection line between the target equivalent node and the external grid node; wherein the grid node includes the target equivalent node, the external grid node and the network loss equivalent node.

[0037] In an embodiment of the present invention, the target monitoring area power grid is equivalent to an electrical node and defined as the target node, namely the above-mentioned first power grid node; according to the voltage level of the regional power grid and the external power grid, the external power grid substation and power plant at this voltage level and above, as well as the new energy centralized access station, are respectively equivalent to an electrical node and defined as a general node, namely the above-mentioned second power grid node.

[0038] As an optional embodiment, a network loss equivalent node, ie, the third grid node, is added between two electrical nodes that are directly connected through a power line.

[0039] It should be noted that the above-mentioned network loss equivalent node is the third grid node on the connection line between the above-mentioned target equivalent node and the above-mentioned external grid node; wherein, the above-mentioned grid node includes the above-mentioned target equivalent node, the above-mentioned external grid node and the above-mentioned network loss equivalent node.

[0040] In an optional embodiment, the above-mentioned acquisition of the line power data of the power grid node includes: acquiring the first online power value, the first offline power value and the first node exchange power value of the above-mentioned external power grid node at the target time; acquiring the power supply power value, the power consumption power value and the interconnecting line power value of the above-mentioned target equivalent node at the above-mentioned target time; acquiring the second online power value, the second offline power value and the second node exchange power value of the above-mentioned network loss equivalent node at the above-mentioned target time; wherein, the line power data of the above-mentioned power grid node includes: the above-mentioned first online power value, the above-mentioned first offline power value and the above-mentioned first node exchange power value of the above-mentioned external power grid node, the above-mentioned power supply power value, the above-mentioned power consumption power value and the above-mentioned interconnecting line power value of the above-mentioned target equivalent node, and the above-mentioned second online power value, the above-mentioned second offline power value and the above-mentioned second node exchange power value of the above-mentioned network loss equivalent node.

[0041] In an embodiment of the present invention, the outgoing, online, and offline power values of each node at the same time scale t are obtained based on the real-time measurement system of the power grid. The power flowing into the line of the network loss equivalent node is positive, and the power flowing out of the line is negative. The sum of the inflow and outflow is regarded as the offline power value of the network loss equivalent node. Each node is regarded as a department in the input-output analysis method, and an input-output table is constructed. Among them, x_ij in the "intermediate use" matrix is the power value transmitted from node i to node j, y_i in the "final use" vector Y is the offline power value of node i, and x_i in the "total input" vector X is the sum of the online power c_i of node i and the power flowing in from other nodes.

[0042] It should be noted that the line power data of the above-mentioned grid nodes include: the above-mentioned first on-grid power value, the above-mentioned first off-grid power value and the above-mentioned first node exchange power value of the above-mentioned external grid node, the above-mentioned power supply power value, the above-mentioned power consumption power value and the above-mentioned tie line power value of the above-mentioned target equivalent node, the above-mentioned second on-grid power value, the above-mentioned second off-grid power value and the above-mentioned second node exchange power value of the above-mentioned network loss equivalent node

[0043] As an optional embodiment, external grid node data processing includes: selecting a range for obtaining the active power P of the external grid nodes based on the highest voltage level corresponding to the region. Obtaining the on-grid power, off-grid power, and inter-node exchange power values corresponding to n nodes at time t from the real-time grid measurement system. On-grid power generally refers to the power value of the power lines corresponding to power plants and renewable energy aggregation booster stations; off-grid power generally refers to the power value of the power lines corresponding to the step-down transformers of substations; and inter-node exchange power generally refers to the power value of the power lines corresponding to the outgoing lines of power plants.

[0044] Optionally, data processing for equivalent nodes in the target region includes obtaining data on source power, power consumption, and tie-line power at the equivalent node at time t from the real-time grid measurement system, and calculating the corresponding on-grid power, off-grid power, and inter-node exchange power values for the equivalent node. On-grid power refers to the sum of the source power within the target region; off-grid power refers to the sum of the region's total power consumption and grid losses; and inter-node exchange power refers to the outgoing power value of the tie-line from the region to the external grid.

[0045] Optionally, data processing for network loss equivalent nodes includes: connecting external grid nodes and regional equivalent nodes via power lines to form m corresponding network loss equivalent nodes, obtaining the power at the beginning and end of the power lines at time t from the real-time grid measurement system, and calculating the on-grid power, off-grid power, and inter-node exchange power values corresponding to the network loss equivalent nodes. The on-grid power is 0; the off-grid power is the difference between the power flowing into the line and the power flowing out of the line; and the inter-node exchange power is the power flowing into or out of the line.

[0046] In an optional embodiment, the above-mentioned generation of the input-output table based on the above-mentioned line power data includes: constructing a first input-output table of the above-mentioned external power grid node based on the above-mentioned first online power value, the above-mentioned first offline power value and the above-mentioned first node exchange power value; constructing a second input-output table of the above-mentioned external power grid node based on the above-mentioned power supply power value, the above-mentioned power consumption power value and the above-mentioned interconnection line power value; constructing a third input-output table of the above-mentioned external power grid node based on the above-mentioned second online power value, the above-mentioned second offline power value and the above-mentioned second node exchange power value; wherein the above-mentioned input-output table includes: the above-mentioned first input-output table, the above-mentioned second input-output table and the above-mentioned third input-output table.

[0047] In this embodiment of the present invention, each external grid node, equivalent node, and network loss equivalent node is considered a sector in the input-output analysis method, and an input-output table for m+n+1 sectors is established. In the "intermediate use" matrix, x_ij represents the power transmitted from node i to node j. In the "final use" vector Y, y_i represents the off-grid power value of node i. In the "total input" vector X, x_i represents the sum of the on-grid power c_i of node i and the power flowing in from other nodes.

[0048] In an optional embodiment, the above-mentioned processing of the input-output table to determine the traceability vector of the above-mentioned power grid node includes: determining the power consumption coefficient matrix based on the above-mentioned input-output table; and selecting the data in the preset column from the above-mentioned power consumption coefficient matrix as the above-mentioned traceability vector.

[0049] In the embodiment of the present invention, based on the input-output table, the power direct consumption coefficient matrix A is established. The row vector relationship corresponding to "intermediate use + final use = total input" at time t is established: Correspondingly, an m+n+1 dimensional direct consumption coefficient matrix A is established, where the element a ij =x ij / x i , calculate the Leontief inverse matrix (IA) -1 , where I is the identity matrix.

[0050] Optionally, calculate the traceability vector H corresponding to the equivalent node k in the target area t The economic meaning of each column in the Leontief inverse matrix is the output increase required by each department if the department corresponding to the column increases by one unit. Corresponding to the power flow, that is, the power increase required by each node if the target node increases consumption by one unit of electricity, it reflects the structure of power consumption. Take (IA) -1 The kth column of the matrix is used as the traceability vector of the equivalent node k in the target area, H t =(IA) -1 [0 … 0 1 0 … 0] T .

[0051] In an optional embodiment, the above-mentioned determination of the indirect carbon emissions of electricity of the above-mentioned grid node based on the power generation carbon emission coefficient and the above-mentioned traceability vector includes: determining the above-mentioned power generation carbon emission coefficient based on the historical power generation carbon emission coefficient and the above-mentioned line power data; determining a preset monitoring time scale; and using a preset calculation formula to determine the above-mentioned indirect carbon emissions of electricity of the above-mentioned grid node based on the above-mentioned power generation carbon emission coefficient and the above-mentioned preset monitoring time scale.

[0052] In the embodiment of the present invention, the carbon emission coefficient vector E of power generation at time t is first calculated. t , the carbon emission coefficient of each node power generation ei , where the power plant carbon emission coefficient is selected as the ratio of carbon emissions in the previous year to the corresponding power generation; for new energy grid nodes, the power generation carbon emission coefficient is set to 0; the equivalent node k in the target area corresponds to the power generation carbon emission coefficient c j.t is the grid-connected power of power plant j at time t in the target area, e j The carbon emission coefficient of power generation of power plant j in the target area; the carbon emission coefficient of power generation corresponding to other nodes with zero grid power is 0.

[0053] Optionally, calculate the indirect carbon emissions of electricity in the region at time t F t ,in, Δt is the monitoring time scale.

[0054] As an optional embodiment, the above steps are repeated to realize the real-time monitoring of regional electricity indirect carbon emissions at time intervals of Δt. When the frequency of data resource acquisition and computing resources are sufficient, a relatively small time scale can be selected. is the real-time carbon emission coefficient per kilowatt-hour at time t.

[0055] Through the above steps, a real-time monitoring method for electricity carbon emissions based on input-output analysis can be implemented. The monitored electrical flow is regarded as the input-output of each node, the transmission between nodes is expressed by "intermediate use", and the off-grid power is expressed by "final use". The processing brought by the grid flow is regarded as a network loss equivalent node, and the line network loss is expressed by "final use". The electricity consumption structure of the target area can be traced, and then the real-time and high-precision monitoring of regional indirect carbon emissions can be achieved.

[0056] Example 2

[0057] According to an embodiment of the present invention, there is also provided an embodiment of a device for implementing the above-mentioned method for monitoring indirect carbon emissions from electricity. Figure 3 FIG. 1 is a schematic diagram of a structure of an indirect carbon emission monitoring device for electric power according to an embodiment of the present invention. Figure 3 As shown, the above-mentioned apparatus includes: an acquisition module 30, a generation module 32, a first determination module 34 and a second determination module 36, wherein:

[0058] An acquisition module 30 is used to acquire line power data of a grid node;

[0059] A generating module 32 is configured to generate an input-output table based on the line power data;

[0060] A first determining module 34 is configured to process the input-output table to determine the traceability vector of the power grid node;

[0061] The second determining module 36 is configured to determine the indirect carbon emissions of electricity of the above-mentioned grid node based on the power generation carbon emission coefficient and the above-mentioned traceability vector.

[0062] It should be noted here that the above-mentioned acquisition module 30, generation module 32, first determination module 34 and second determination module 36 correspond to steps S102 to S108 in Example 1. The four modules and the corresponding steps implement the same instances and application scenarios, but are not limited to the contents disclosed in the above-mentioned Example 1.

[0063] It should be noted that the preferred implementation of this embodiment can be found in the relevant description in Example 1 and will not be repeated here.

[0064] According to an embodiment of the present invention, an embodiment of a computer-readable storage medium is further provided. Optionally, in this embodiment, the computer-readable storage medium can be used to store program codes executed by the method for monitoring indirect carbon emissions from electricity provided in the first embodiment.

[0065] Optionally, in this embodiment, the computer-readable storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0066] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: obtaining line power data of the grid node; generating an input-output table based on the above line power data; processing the above input-output table to determine the traceability vector of the above grid node; and determining the indirect carbon emissions of electricity of the above grid node based on the power generation carbon emission coefficient and the above traceability vector.

[0067] Optionally, the computer-readable storage medium is configured to store program code for executing the following steps: determining the target equivalent node and external grid node to be monitored, wherein the target equivalent node is the first grid node in the target monitoring area, and the external grid node is the second grid node having a voltage level greater than or equal to the target equivalent node and connected to the target equivalent node; determining the network loss equivalent node to be monitored, wherein the network loss equivalent node is the third grid node on the connection line between the target equivalent node and the external grid node; wherein the grid nodes include the target equivalent node, the external grid node and the network loss equivalent node.

[0068] Optionally, the computer-readable storage medium is configured to store program codes for executing the following steps: obtaining the first online power value, the first offline power value and the first node exchange power value of the external grid node at the target time; obtaining the power supply power value, the power consumption power value and the interconnecting line power value of the target equivalent node at the target time; obtaining the second online power value, the second offline power value and the second node exchange power value of the network loss equivalent node at the target time; wherein the line power data of the grid node includes: the first online power value, the first offline power value and the first node exchange power value of the external grid node, the power supply power value, the power consumption power value and the interconnecting line power value of the target equivalent node, and the second online power value, the second offline power value and the second node exchange power value of the network loss equivalent node.

[0069] Optionally, the computer-readable storage medium is configured to store program codes for executing the following steps: constructing a first input-output table of the external power grid node based on the first online power value, the first offline power value and the first node exchange power value; constructing a second input-output table of the external power grid node based on the power supply power value, the power consumption power value and the interconnection line power value; constructing a third input-output table of the external power grid node based on the second online power value, the second offline power value and the second node exchange power value; wherein the input-output table includes: the first input-output table, the second input-output table and the third input-output table.

[0070] Optionally, the computer-readable storage medium is configured to store program code for executing the following steps: determining a power consumption coefficient matrix based on the input-output table; and selecting data in the preset column from the power consumption coefficient matrix as the traceability vector.

[0071] Optionally, the computer-readable storage medium is configured to store program codes for executing the following steps: determining the power generation carbon emission coefficient based on the historical power generation carbon emission coefficient and the line power data; determining a preset monitoring time scale; and determining the indirect carbon emissions of electricity of the grid node based on the power generation carbon emission coefficient and the preset monitoring time scale using a preset calculation formula.

[0072] According to an embodiment of the present invention, a processor embodiment is also provided. Optionally, in this embodiment, the computer-readable storage medium may be used to store program codes executed by the method for monitoring indirect carbon emissions from electricity provided in the first embodiment.

[0073] An embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and runnable on the processor. When the processor executes the program, the following steps are implemented: obtaining line power data of a power grid node; generating an input-output table based on the above line power data; processing the above input-output table to determine the traceability vector of the above power grid node; and determining the indirect carbon emissions of electricity of the above power grid node based on the power generation carbon emission coefficient and the above traceability vector.

[0074] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program initialized with the following method steps: obtaining line power data of a power grid node; generating an input-output table based on the above line power data; processing the above input-output table to determine the traceability vector of the above power grid node; and determining the indirect carbon emissions of electricity of the above power grid node based on the power generation carbon emission coefficient and the above traceability vector.

[0075] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0076] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0077] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units 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 interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0078] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0079] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0080] If the integrated unit 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 invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0081] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for monitoring indirect carbon emissions from electricity, characterized in that: include: Obtain line power data of grid nodes; generating an input-output table based on the line power data; Processing the input-output table to determine the traceability vector of the power grid node; Determining the indirect carbon emissions of electricity at the grid node based on the power generation carbon emission coefficient and the traceability vector; Before obtaining the line power data of the grid node, the method further includes: determining a target equivalent node and an external grid node to be monitored, wherein the target equivalent node is a first grid node in a target monitoring area, and the external grid node is a second grid node having a voltage level greater than or equal to the target equivalent node and connected to the target equivalent node; determining a network loss equivalent node to be monitored, wherein the network loss equivalent node is a third grid node on the connection line between the target equivalent node and the external grid node; wherein the grid nodes include the target equivalent node, the external grid node, and the network loss equivalent node; The obtaining of line power data of the grid node includes: obtaining the first online power value, the first offline power value and the first node exchange power value of the external grid node at the target time, wherein the first online power value refers to the power value of the incoming line of the power plant and the new energy collection and boosting station corresponding to the plant-station line, the first offline power value refers to the power value of the incoming line corresponding to the step-down transformer of the substation, and the first node exchange power value refers to the power value corresponding to the outgoing line of the plant-station line; obtaining the power supply power value, power consumption power value and tie line power value of the target equivalent node at the target time; obtaining the second online power value, the second offline power value and the second node exchange power value of the network loss equivalent node at the target time, wherein the second online power value is 0, the second offline power value is the difference between the power flowing into the power line and the power flowing out of the power line, the second node exchange power value is the power flowing into the power line or the power flowing out of the power line, and the power line is the power line between the external grid node and the regional equivalent node.

2. The method according to claim 1, characterized in that Generating an input-output table based on the line power data includes: Constructing a first input-output table of the external power grid node based on the first online power value, the first offline power value, and the first node exchange power value; Constructing a second input-output table of the target equivalent node based on the power value of the power supply, the power value of the power consumption, and the tie line power value; Constructing a third input-output table of the network loss equivalent node based on the second online power value, the second offline power value, and the second node switching power value; The input-output table includes: the first input-output table, the second input-output table and the third input-output table.

3. The method according to claim 1, characterized in that The processing of the input-output table to determine the traceability vector of the power grid node includes: Determining a power consumption coefficient matrix based on the input-output table; From the power consumption coefficient matrix, data in a preset column is selected as the tracing vector.

4. The method according to any one of claims 1 to 3, characterized in that The determining of the indirect carbon emissions of electricity of the grid node based on the power generation carbon emission coefficient and the traceability vector includes: Determining the power generation carbon emission coefficient based on the historical power generation carbon emission coefficient and the line power data; Determine the preset monitoring time scale; The indirect carbon emissions from electricity of the grid node are determined using a preset calculation formula based on the power generation carbon emission coefficient and the preset monitoring time scale.

5. An indirect carbon emission monitoring device for electricity, characterized in that: include: An acquisition module, used to obtain line power data of power grid nodes; A generating module, configured to generate an input-output table based on the line power data; A first determination module is configured to process the input-output table to determine the traceability vector of the power grid node; A second determination module is configured to determine the indirect carbon emissions of electricity of the grid node based on the power generation carbon emission coefficient and the traceability vector; The device is further configured to: determine a target equivalent node and an external grid node to be monitored, wherein the target equivalent node is a first grid node in a target monitoring area, and the external grid node is a second grid node having a voltage level greater than or equal to the target equivalent node and connected to the target equivalent node; determine a network loss equivalent node to be monitored, wherein the network loss equivalent node is a third grid node on a connection line between the target equivalent node and the external grid node; and the grid nodes include the target equivalent node, the external grid node, and the network loss equivalent node. The device is also used to: obtain the first online power value, the first offline power value and the first node exchange power value of the external power grid node at the target time, wherein the first online power value refers to the power value of the incoming line of the power plant and the new energy collection and boosting station corresponding to the power plant, the first offline power value refers to the power value of the incoming line corresponding to the substation step-down transformer, and the first node exchange power value refers to the power value corresponding to the outgoing line of the power plant; obtain the power supply power value, power consumption power value and tie line power value of the target equivalent node at the target time; obtain the second online power value, the second offline power value and the second node exchange power value of the network loss equivalent node at the target time, wherein the second online power value is 0, the second offline power value is the difference between the power flowing into the power line and the power flowing out of the power line, the second node exchange power value is the power flowing into the power line or the power flowing out of the power line, and the power line is the power line between the external power grid node and the regional equivalent node.

6. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executed by the method for monitoring indirect carbon emissions from electricity according to any one of claims 1 to 4.

7. A processor, characterized in that: The processor is used to run a program, wherein the program is configured to execute the method for monitoring indirect carbon emissions from electricity according to any one of claims 1 to 4 when running.

8. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the method for monitoring indirect carbon emissions from electricity according to any one of claims 1 to 4.

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