Indirect carbon emission rapid accounting method and system
By using equivalent power flow calculation and lossless network mapping model, the problem of carbon flow distribution deviation in the indirect carbon emission accounting of the power system is solved, realizing the fair allocation and rapid accounting of green electricity benefits, and supporting the accurate monitoring and market integration of carbon emissions in the power system.
Patent Information
- Application Number
- CN202511597937.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-04
- Publication Date
- 2026-03-06
AI Technical Summary
Traditional indirect carbon emission accounting methods for power systems cannot effectively reflect the actual distribution patterns of carbon flow in the complex topology of the power grid. Especially with the increasing proportion of renewable energy generation, they cannot distinguish the essential differences in carbon emission intensity between thermal power units and renewable energy units, resulting in significant deviations between user-side carbon emission accounting results and actual carbon footprints.
By acquiring power grid generation, load, and network topology data, equivalent power flow calculations are performed to equate the carbon emission intensity of new energy units to that of thermal power units. An equivalent lossless network mapping model is constructed, the regional average carbon reduction factor is calculated, and corrections are made in conjunction with green electricity trading data to achieve rapid traceability and real-time monitoring of indirect carbon emissions on the user side.
It achieves a fair distribution of green electricity benefits, reduces computational complexity, accurately quantifies the carbon offset effect of green electricity trading, supports the connection between the electricity market and the carbon market, and helps achieve the goals of renewable energy consumption and emission reduction in the power industry.
Smart Images
Figure CN121615907A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of carbon emission accounting technology for power systems, and in particular to a rapid indirect carbon emission accounting method and system. Background Technology
[0002] As the proportion of global renewable energy generation continues to increase, indirect carbon emission accounting in the power system has become a core requirement for carbon management.
[0003] Traditional accounting methods rely on macroeconomic statistical data to estimate indirect carbon emissions on the user side. This approach is difficult to reflect the actual distribution pattern of carbon flow in the complex topology of the power grid. Especially with the continuous increase in the proportion of renewable energy generation, it is impossible to effectively distinguish the essential differences in carbon emission intensity between thermal power units and renewable energy units, resulting in a significant deviation between the carbon emission accounting results on the user side and the actual carbon footprint. Summary of the Invention
[0004] This invention provides a method and system for rapid indirect carbon emission accounting, which addresses the technical problem of how to optimize existing indirect carbon emission accounting methods and achieves rapid traceability and real-time monitoring of user-side indirect carbon emissions.
[0005] To address the aforementioned technical problems, embodiments of the present invention provide a rapid indirect carbon emission calculation method, comprising: Acquire generation-side data, load-side data, and network topology data of the power grid in the target area. The generation-side data includes data of new energy generating units and thermal power units, and the load-side data includes the total electricity consumption in the target area and the electricity consumption of each user. Based on the power generation side data, the load side data, and the network topology data, an equivalent power flow calculation is performed on the target area power grid to obtain the power flow calculation results; wherein, the equivalent power flow calculation is designed to equate the carbon emission intensity of each node in the new energy unit to the carbon emission intensity of the thermal power unit. Based on the power flow calculation results, an equivalent lossless network mapping model for load-side and generation-side electricity carbon emissions is constructed to obtain the user-side carbon emission benchmark value under the all-thermal power scenario. The equivalent lossless network mapping model achieves network lossless conversion by allocating node losses to downstream branches and loads according to the power flow ratio and load ratio of downstream branches. Based on the data of the new energy units, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption in the target area, the regional average carbon reduction factor is calculated. The carbon emission reduction of each user is calculated based on the average carbon reduction factor and the electricity consumption of each user, and the actual indirect carbon emission of each user is obtained based on the carbon emission reduction and the user-side carbon emission benchmark. The actual indirect carbon emissions of each user are integrated to obtain the total indirect carbon emissions of the target area power grid on the user side.
[0006] As one preferred embodiment, after calculating the regional average carbon reduction factor based on the data of the new energy units, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption in the target area, the following further steps are included: Obtain the total green electricity transaction volume of users within the target area and the green electricity transaction volume of each user; The average carbon reduction factor of the region is corrected based on the total amount of green electricity traded by the user, resulting in the corrected average carbon reduction factor. The carbon emission reduction of each user is calculated based on the electricity consumption and the green electricity trading volume of each user, and the actual indirect carbon emission of each user is obtained based on the carbon emission reduction and the user-side carbon emission benchmark. The total indirect carbon emissions of the target area power grid are obtained by summing up the actual indirect carbon emissions of each user.
[0007] As one preferred embodiment, the step of correcting the regional average carbon reduction factor based on the total amount of green electricity traded by the users to obtain the corrected average carbon reduction factor includes: Determine the total amount of green electricity traded by users within the target area; The regional average carbon reduction factor is corrected based on the total amount of green electricity traded, and is expressed as follows: in, This is the average carbon reduction factor for this region; The power generation of all green power units in the region, The total electricity consumption of users within the region; This represents the difference between the carbon emission intensity of thermal power and the carbon emission intensity of new energy sources within the region. Purchase electricity for users through green electricity trading.
[0008] As one preferred embodiment, the power flow calculation results include the active power flow, branch power flow, branch losses, and load power of each node in the target area power grid; The step of constructing an equivalent lossless network mapping model for load-side and generation-side electricity carbon emissions based on the power flow calculation results, in order to obtain a benchmark value for user-side carbon emissions under a full thermal power scenario, includes: The active power flow, the branch power flow, the branch loss, and the load power are respectively subjected to lossless conversion to obtain equivalent active power flow, equivalent branch power flow, equivalent branch loss, and equivalent load power. An equivalent lossless network mapping model is constructed based on the equivalent active power flow, the equivalent branch power flow, the equivalent branch loss, and the equivalent load power. Carbon flow tracing is performed based on the node carbon potential matrix in the equivalent lossless network mapping model to obtain the carbon emission benchmark value for each user in the full thermal power scenario.
[0009] As one preferred embodiment, the calculation of the regional average carbon reduction factor based on the data of the new energy units, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption in the target area includes: Extract the total power generation of all new energy generating units within the target area from the new energy generating unit data; Determine the first carbon emission intensity of the thermal power unit and the second carbon emission intensity of the new energy unit, and calculate the difference in carbon emission intensity between the thermal power unit and the new energy unit; The regional average carbon reduction factor is calculated based on the carbon emission intensity difference, the total power generation, and the total electricity consumption within the target area. The average carbon reduction factor is used to quantify the green electricity carbon reduction benefits that can be allocated per unit of electricity consumption within the target area.
[0010] Another embodiment of the present invention provides an indirect carbon emission rapid accounting system, comprising: The acquisition module is used to acquire generation-side data, load-side data and network topology data of the power grid in the target area. The generation-side data includes data of new energy units and thermal power units, and the load-side data includes the total electricity consumption in the target area and the electricity consumption of each user. An equivalent module is used to perform equivalent power flow calculations on the target area power grid based on the generation-side data, the load-side data, and the network topology data to obtain power flow calculation results; wherein, the equivalent power flow calculation is designed to equate the carbon emission intensity of each node in the new energy unit to the carbon emission intensity of the thermal power unit. The construction module is used to construct an equivalent lossless network mapping model of electricity carbon emissions on the load side and the generation side based on the power flow calculation results, so as to obtain the user-side carbon emission benchmark value under the all-thermal power scenario. The equivalent lossless network mapping model achieves network lossless conversion by allocating node losses to downstream branches and loads according to the power flow ratio and load ratio of downstream branches. The calculation module is used to calculate the regional average carbon reduction factor based on the data of the new energy units, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption in the target area. The calculation module is used to calculate the carbon emission reduction of each user based on the average carbon reduction factor and the electricity consumption of each user, and to obtain the actual indirect carbon emission of each user based on the carbon emission reduction and the user-side carbon emission benchmark. The integration module is used to integrate the actual indirect carbon emissions of each user to obtain the total indirect carbon emissions of the target area power grid on the user side.
[0011] As one preferred embodiment, the accounting module is further configured to: Obtain the total green electricity transaction volume of users within the target area and the green electricity transaction volume of each user; The average carbon reduction factor of the region is corrected based on the total amount of green electricity traded by the user, resulting in the corrected average carbon reduction factor. The carbon emission reduction of each user is calculated based on the electricity consumption and the green electricity trading volume of each user, and the actual indirect carbon emission of each user is obtained based on the carbon emission reduction and the user-side carbon emission benchmark. The total indirect carbon emissions of the target area power grid are obtained by summing up the actual indirect carbon emissions of each user.
[0012] As one preferred embodiment, the accounting module is further configured to: Determine the total amount of green electricity traded by users within the target area; The regional average carbon reduction factor is corrected based on the total amount of green electricity traded, and is expressed as follows: in, This is the average carbon reduction factor for this region; The power generation of all green power units in the region, The total electricity consumption of users within the region; This represents the difference between the carbon emission intensity of thermal power and the carbon emission intensity of new energy sources within the region. Purchase electricity for users through green electricity trading.
[0013] As one preferred embodiment, the power flow calculation results include the active power flow, branch power flow, branch losses, and load power of each node in the target area power grid; The equivalent module is specifically used for: The active power flow, the branch power flow, the branch loss, and the load power are respectively subjected to lossless conversion to obtain equivalent active power flow, equivalent branch power flow, equivalent branch loss, and equivalent load power. An equivalent lossless network mapping model is constructed based on the equivalent active power flow, the equivalent branch power flow, the equivalent branch loss, and the equivalent load power. Carbon flow tracing is performed based on the node carbon potential matrix in the equivalent lossless network mapping model to obtain the carbon emission benchmark value for each user in the full thermal power scenario.
[0014] As one preferred embodiment, the construction module is specifically used for: Extract the total power generation of all new energy generating units within the target area from the new energy generating unit data; Determine the first carbon emission intensity of the thermal power unit and the second carbon emission intensity of the new energy unit, and calculate the difference in carbon emission intensity between the thermal power unit and the new energy unit; The regional average carbon reduction factor is calculated based on the carbon emission intensity difference, the total power generation, and the total electricity consumption within the target area. The average carbon reduction factor is used to quantify the green electricity carbon reduction benefits that can be allocated per unit of electricity consumption within the target area.
[0015] Compared with the prior art, the beneficial effects of the embodiments of the present invention are at least one of the following: 1) This invention defines and calculates the regional average carbon reduction factor, which distributes the carbon reduction benefits generated by green electricity evenly among load nodes in the region. This breaks the problem of unfair green electricity benefits caused by differences in grid topology among users in different locations, ensures that users can fairly enjoy the rights and interests of green electricity consumption, and significantly enhances users' enthusiasm for participating in green electricity trading.
[0016] 2) This invention achieves dynamic adaptation of scenarios before and after green electricity trading by constructing an equivalent lossless network mapping model and performing a single power flow calculation. It eliminates the need to split the model or perform repeated calculations, significantly reducing computational complexity and time. At the same time, it accurately quantifies the carbon offset effect of green electricity trading, providing precise accounting support for the connection between the electricity market and the carbon market, and helping to achieve the goals of renewable energy consumption and emission reduction in the power industry. Attached Figure Description
[0017] Figure 1 This is a flowchart illustrating the indirect carbon emission rapid calculation method in one embodiment of the present invention; Figure 2 This is a schematic diagram of an indirect carbon emission rapid accounting system in one embodiment of the present invention; Figure label: Among them, 11. Acquisition module; 12. Equivalent module; 13. Construction module; 14. Calculation module; 15. Accounting module; 16. Integration module. Detailed Implementation
[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.
[0019] In the description of this application, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.
[0020] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. The terms "vertical," "horizontal," "left," "right," "upper," "lower," and similar expressions used herein are for illustrative purposes only and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.
[0021] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.
[0022] One embodiment of the present invention provides a rapid indirect carbon emission calculation method. For details, please refer to [link to documentation]. Figure 1 , Figure 1 The diagram shown is a flowchart of a rapid indirect carbon emission calculation method according to one embodiment of the present invention, which includes steps S1-S6: S1: Obtain the generation-side data, load-side data, and network topology data of the power grid in the target area, wherein the generation-side data includes data of new energy generating units and data of thermal power units, and the load-side data includes the total electricity consumption in the target area and the electricity consumption of each user; In this embodiment, power generation data is the core foundation for calculating carbon emissions. It is necessary to accurately distinguish the characteristic parameters of renewable energy units and thermal power units, specifically including data from both renewable energy units and thermal power units. The renewable energy unit data covers basic information on all renewable energy power generation units within the region, mainly including: The total power generation of new energy units: It needs to be counted separately according to wind power, photovoltaic, hydropower and other types to reflect the total supply of green electricity in the region, which is the key basis for calculating carbon reduction benefits; Carbon emission intensity of new energy units: usually taken as extremely low (such as photovoltaic and wind power which are close to zero emissions), needs to be determined according to the type of unit, technical parameters and regional power grid benchmark value, and is used to quantify the difference in carbon emissions with thermal power. Unit access node information: Clarify the connection position of new energy units in the power grid topology, and provide spatial correlation basis for carbon flow path tracing in subsequent power flow calculation.
[0023] Data on thermal power units focuses on the carbon emission characteristics of fossil fuel power generation, including: Carbon emission intensity of thermal power units: Calculated based on the unit's fuel type (coal power, gas power, etc.), power generation efficiency, and emission factors, it is the core parameter for measuring carbon emission benchmarks. Unit injected power: Real-time or time-period power generation output data, reflecting the active power contribution of thermal power to the power grid; Unit operating status data, such as start-up and shutdown status and output adjustment range, are used to accurately map the actual carbon emission level of thermal power plants.
[0024] The core value of power generation-side data lies in distinguishing the differences in carbon emission intensity between new energy sources and thermal power units, which is a prerequisite for subsequent calculation of carbon reduction factors and quantification of the environmental benefits of green electricity.
[0025] Load-side data needs to accurately link user electricity consumption behavior with carbon emission responsibility, specifically including: total electricity consumption within the target area, electricity consumption of each user, and data related to green electricity trading. The total electricity consumption within the target area represents the total electricity consumption of all users within the area during the calculation period, serving as the basic denominator for allocating regional carbon reduction benefits and the benchmark scale used to calculate the average carbon reduction factor. Each user's electricity consumption represents their actual electricity consumption data, which needs to be statistically analyzed by time dimension (e.g., hourly, daily) or user type (industrial, commercial, residential, etc.), and is the core basis for subsequent allocation of individual carbon emissions. If considering green electricity trading scenarios, the total electricity volume traded by each user and the electricity volume traded by each user must also be obtained to correct the average carbon reduction factor, ensuring that the emission reduction rights of green electricity purchasers are accurately measured.
[0026] Network topology data reflects the physical connections of the power grid and serves as the spatial framework for power flow calculation and carbon flow tracing. It primarily includes node information, branch information, and loss data. Node information includes the numbers, types (generator nodes, load nodes, tie nodes, etc.), and geographical locations of all bus nodes in the regional power grid, used to define the spatial units for carbon flow calculation. Branch information includes parameters of the transmission lines between nodes, such as resistance, reactance, transmission capacity, and actual active power flow, crucial for calculating branch losses and equivalent lossless network transformation. Loss data includes the power losses of each branch and node losses, which must be obtained using power flow calculation tools (such as MATPOWER) for the fair allocation of losses in the subsequent equivalent lossless network.
[0027] Network topology data determines the transmission path of carbon emissions from the generation side to the load side. By analyzing the connections between nodes and branches, the distribution pattern of carbon flow in the power grid can be accurately calculated, providing a structural basis for "loss allocation according to power flow proportion" in the construction of equivalent lossless networks and avoiding carbon flow tracking errors caused by missing topology information.
[0028] S2: Based on the power generation side data, the load side data, and the network topology data, perform equivalent power flow calculation on the target area power grid to obtain power flow calculation results; wherein, the equivalent power flow calculation is designed to equate the carbon emission intensity of each node in the new energy unit to the carbon emission intensity of the thermal power unit; It should be noted that the essence of equivalent power flow calculation is to transform the complex "new energy + thermal power" hybrid power generation scenario into an "all thermal power scenario" through hypothetical equivalence processing, thereby constructing a unified carbon flow calculation benchmark.
[0029] In this embodiment, the carbon emission intensity of each node in the renewable energy unit is equivalent to the carbon emission intensity of the thermal power unit. Specifically, in traditional carbon flow calculations, the carbon emission intensity of renewable energy units (such as wind power and photovoltaic power) is much lower than that of thermal power units. Directly including them in the calculation would complicate the carbon flow distribution due to differences in unit type and make it difficult to establish a fair baseline. Through equivalent processing, the carbon emission intensity of renewable energy nodes is forcibly set to be consistent with that of thermal power units. This ensures that the initial power flow calculation does not distinguish between the emission differences between renewable energy and thermal power, but only performs carbon flow path tracking based on the high emission intensity of thermal power. Finally, the power flow distribution results under the entire thermal power scenario are output, providing a reference for the subsequent determination of the "user-side carbon emission baseline value".
[0030] Equivalent power flow calculation requires integrating three types of data (generation side, load side, and network topology) and relying on specialized tools to complete the numerical solution. The specific process is as follows: Data input integration: Extract the injected power of new energy units and thermal power units, replace the carbon emission intensity of new energy units with the carbon emission intensity of thermal power units, and form a unified unit carbon emission intensity vector; use the total regional electricity consumption and the electricity consumption of each user as the load constraints for power flow calculation; based on node connection relationships, branch parameters (resistance, reactance), etc., construct a power grid physical structure model and clarify the power flow transmission path.
[0031] Power flow calculations need to be performed using power system simulation tools (such as MATPOWER), and the final output power flow calculation results include: Active power flow at each node in the target area power grid: reflects the actual active power flowing through each node; Branch power flow: describes the amount of power transferred between transmission lines; Branch loss: Power loss generated during power transmission; Load power: The actual power consumption of each user node. These results will serve as the raw data for the subsequent construction of the "equivalent lossless network mapping model," directly affecting the accuracy of carbon flow tracing.
[0032] The high proportion of renewable energy integration results in a power grid structure characterized by "multiple types and high volatility." If power flow calculations are performed directly based on actual carbon emission intensity (low for renewable energy and high for thermal power), separate models must be built for different unit types, complicating carbon flow tracking equations (such as the calculation of the nodal carbon potential matrix). After equivalent processing, the carbon emission intensity of all units is unified as that of thermal power units, significantly simplifying vector construction and reducing the dimensionality and complexity of power flow calculations.
[0033] In summary, equivalent power flow calculation transforms complex hybrid power generation scenarios into quantifiable all-thermal power benchmark scenarios through "hypothetical equivalence" and "precise numerical solutions." This simplifies the calculation process and provides a unified reference for subsequent fair allocation and rapid correction, making it a core technological support for achieving accurate accounting of indirect carbon emissions.
[0034] S3: Construct an equivalent lossless network mapping model for load-side and generation-side electricity carbon emissions based on the power flow calculation results, so as to obtain the user-side carbon emission benchmark value under the all-thermal power scenario. The equivalent lossless network mapping model achieves network lossless conversion by allocating node losses to downstream branches and loads according to the downstream branch power flow ratio and load ratio. Preferably, in one embodiment of the present invention, the power flow calculation results include the active power flow, branch power flow, branch loss and load power of each node in the target area power grid; The step of constructing an equivalent lossless network mapping model for load-side and generation-side electricity carbon emissions based on the power flow calculation results, in order to obtain a benchmark value for user-side carbon emissions under a full thermal power scenario, includes: The active power flow, the branch power flow, the branch loss, and the load power are respectively subjected to lossless conversion to obtain equivalent active power flow, equivalent branch power flow, equivalent branch loss, and equivalent load power. An equivalent lossless network mapping model is constructed based on the equivalent active power flow, the equivalent branch power flow, the equivalent branch loss, and the equivalent load power. Carbon flow tracing is performed based on the node carbon potential matrix in the equivalent lossless network mapping model to obtain the carbon emission benchmark value for each user in the full thermal power scenario.
[0035] In real power grids, transmission lines inevitably experience power losses (branch losses and node losses). If carbon flow tracing is directly performed based on lossy networks, users at different locations will bear unfair carbon emission responsibilities due to uneven loss distribution (e.g., nodes with large power flow may be over-allocated the carbon emissions corresponding to their losses). The core objective of constructing an equivalent lossless network is to "distribute node losses to downstream branches and loads according to the proportion of downstream power flow and load, thereby achieving lossless network transformation." Essentially, this eliminates the interference of physical network losses on carbon flow tracing through fair loss distribution, so that the transformed network retains the carbon flow transmission characteristics of the original power grid while simplifying it to a "lossless" state. This provides a unified and fair model carrier for calculating carbon emission benchmarks in all thermal power scenarios.
[0036] The power flow calculation results (active power flow, branch power flow, branch loss, and load power) are the raw data for lossless conversion. The conversion process requires processing the four types of parameters separately. The core basis is "allocating losses according to the power flow ratio and load ratio", as follows.
[0037] For each node in the power grid, the equivalent active power flow needs to be calculated by adding the unknown losses of that node to the actual active power flow, as shown in the formula: in, It is the node flowing through the equivalent network. The general trend of success; It is a node Unknown node losses.
[0038] The equivalent transformation of branch power flow needs to consider the impact of upstream node losses on downstream branches. That is, the equivalent power flow of a branch is the actual power flow plus the allocated node losses, as shown in the formula: in, For the active power flow of the branches in the equivalent network, For actual branch line current, This refers to the portion of the node loss allocated to that branch. The loss allocation ratio is strictly determined based on the proportion of the branch's power flow to the total power flow of the node. This ensures that the loss distribution of branch circuits is proportional to the magnitude of the power flow.
[0039] The equivalent power of a user load needs to be added to the node losses allocated to that load, as shown in the formula: in, The node load power in the equivalent network. This represents the actual load power. The allocation ratio for node losses to be distributed to this load is determined based on the proportion of the load power to the total power flow of the node: This conversion ensures that the losses borne by the user's load match the scale of their electricity consumption.
[0040] Unknown node losses are a key variable in lossless transformation and need to be solved using the node power balance equations. Based on the power balance relationship between the actual network and the equivalent network, the matrix equations are derived as follows: in, The upstream distribution matrix, Let be the node loss vector. Let be the branch loss vector. By solving this equation, the loss of each node can be obtained, thus completing the lossless transformation of all parameters.
[0041] The elements in can be represented as: After completing the lossless transformation of active power flow, branch power flow, and load power, the construction of the equivalent lossless network mapping model essentially involves integrating these transformed parameters into a logically self-consistent network model, whose core features include: The power relationships of all nodes and branches in the network satisfy the "lossless" condition (input power = output power + load power), eliminating the interference of losses on carbon flow transfer; The model preserves the original power grid topology (node connections, branch routing) to ensure that the carbon flow tracing path is consistent with the actual power grid. The equivalent parameters already include a fair allocation of losses, providing an unbiased data basis for subsequent carbon flow tracking.
[0042] After the equivalent lossless network is constructed, carbon flow tracing needs to be performed using the node carbon potential matrix to ultimately obtain the user-side carbon emission baseline value under the entire thermal power scenario. The specific process is as follows: Nodal carbon potential is a core indicator for measuring nodal carbon emission intensity. In a scenario of all-thermal power (where renewable energy is equivalent to thermal power), its matrix calculation formula is as follows: in, This is the nodal carbon potential matrix (unit: tCO2 / kWh). Let be the active flux matrix of the nodes. This is the branch power flow distribution matrix. Inject the distribution matrix into the unit. The carbon emission intensity vector of the unit (all thermal power carbon emission intensity is taken in the scenario of all thermal power plants). This matrix reflects the carbon emission "potential energy" of each node in a full thermal power scenario.
[0043] Based on the node carbon potential matrix, the carbon flow rate (i.e., the carbon emissions per unit of electricity consumption) of each user load can be further calculated. Since the equivalent lossless network has eliminated loss interference and the carbon potential matrix is constructed based on a full thermal power scenario, the final carbon emission benchmark value for each user is essentially "the amount of indirect carbon emissions that the user should bear when all power generation in the region is thermal power". This benchmark value will serve as the basis for comparison in subsequent calculations of actual carbon emissions (after deducting the emission reduction benefits of green electricity).
[0044] S4: Based on the data of the new energy units, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption in the target area, calculate the regional average carbon reduction factor; Preferably, in one embodiment of the present invention, the step of calculating the regional average carbon reduction factor based on the new energy unit data, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption in the target area includes: Extract the total power generation of all new energy generating units within the target area from the new energy generating unit data; Determine the first carbon emission intensity of the thermal power unit and the second carbon emission intensity of the new energy unit, and calculate the difference in carbon emission intensity between the thermal power unit and the new energy unit; The regional average carbon reduction factor is calculated based on the carbon emission intensity difference, the total power generation, and the total electricity consumption within the target area. The average carbon reduction factor is used to quantify the green electricity carbon reduction benefits that can be allocated per unit of electricity consumption within the target area.
[0045] In this embodiment, the regional average carbon reduction factor is a quantitative indicator that measures the average emission reduction benefit of green electricity replacing thermal power within a region. Essentially, it is a coefficient that fairly distributes the overall emission reduction of new energy power generation according to the scale of user electricity consumption. Its core functions include: Eliminate the problem of unfair distribution of green electricity benefits due to the different locations of users in the power grid, and ensure that all users enjoy the regional green electricity emission reduction results fairly according to their electricity consumption ratio; Simplify the calculation process of green electricity emission reduction benefits, avoid the individualized accounting based on complex carbon flow path tracing in traditional methods, and achieve rapid allocation; This provides benchmark parameters for subsequently revising emission reduction benefits based on green electricity trading data, and supports carbon emission accounting in multiple scenarios.
[0046] The calculation of the regional average carbon reduction factor needs to be based on three types of core data: the total power generation of new energy units, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption.
[0047] Specifically, the total power generation of all new energy units (wind power, photovoltaic, hydropower, etc.) within the target area is extracted from the new energy unit data. This data reflects the total supply of green electricity in the region and forms the basis for calculating emission reduction potential—the greater the amount of new energy power generation, the larger the scale of thermal power that can be replaced, and the higher the overall emission reduction benefits.
[0048] The carbon emission intensity difference is a core indicator for measuring the emission reduction efficiency per unit of electricity. The calculation process includes: Determine the first carbon emission intensity of thermal power units This refers to the carbon emissions generated by each 1 kWh of electricity generated by a thermal power unit (unit: tCO2 / kWh), which is determined based on the type of thermal power fuel (coal power, gas power, etc.), power generation efficiency, and regional emission factor benchmark values. Determine the second carbon emission intensity of new energy units New energy power generation (such as wind power and photovoltaic) has almost no carbon emissions, and the value is usually very low (close to 0). The specific value needs to be determined according to the type of unit and regional environmental protection standards. Calculate the strength difference: This value reflects the amount of carbon emissions that can be reduced by replacing thermal power with green electricity per unit.
[0049] The formula for calculating the regional average carbon reduction factor is: in, This represents the total electricity consumption (in kWh) of users within the target area. The derivation logic of this formula is as follows: Total regional green electricity emission reduction = Total renewable energy generation × Emission reduction benefit per unit of electricity = ; Emission reduction benefit per unit of electricity consumption = Total emission reduction from green electricity in the region ÷ Total electricity consumption = That is, the regional average carbon reduction factor is obtained. .
[0050] This calculation process achieves the goal of "fairly allocating total emission reductions according to electricity consumption scale", ensuring that users with more electricity consumption receive more emission reduction benefits.
[0051] S5: Calculate the carbon emission reduction of each user based on the average carbon reduction factor and the electricity consumption of each user, and obtain the actual indirect carbon emission of each user based on the carbon emission reduction and the user-side carbon emission benchmark value. This embodiment calculates the user's actual indirect carbon emissions by subtracting the user's share of carbon emission reductions from the baseline carbon emission value for the entire thermal power scenario. Wherein: The carbon emission baseline for a fully thermal power scenario is the theoretical carbon emission of a user assuming that all power generation in the region is thermal power. Carbon emission reductions are the emission reductions that users obtain through green electricity substitution or green electricity trading. Their calculation depends on the regional average carbon reduction factor (or the corrected factor) of step S4. Actual indirect carbon emissions truly reflect the carbon emission responsibility corresponding to users' electricity consumption behavior, taking into account both the environmental value of green electricity and the principle of location equity.
[0052] When green electricity trading is not involved, the calculation of carbon emission reductions directly relies on the regional average carbon reduction factor obtained in step S4, achieving an average distribution of emission reduction benefits among all users. The specific process is as follows: The regional average carbon reduction factor quantifies the green electricity emission reduction benefits that can be allocated per unit of electricity consumption. Therefore, the carbon emission reduction of an individual user is the product of their electricity consumption and the average carbon reduction factor, expressed as: in: Electricity consumption of user i within the region (unit: kWh); This refers to the unit benefit of the total emission reduction from green electricity in a region, allocated based on the total electricity consumption.
[0053] The user's actual indirect carbon emissions equal to the baseline carbon emissions under the all-thermal power scenario minus its carbon emission reduction, expressed as: in, The carbon emission baseline value for user i in the all-thermal power scenario obtained in step S3 (unit: tCO2) is calculated based on the proportion of electricity consumption. This calculation logic ensures that all users, regardless of their location in the power grid, fairly enjoy the regional green electricity emission reduction benefits according to their electricity consumption, avoiding "location discrimination" caused by differences in carbon flow paths.
[0054] The total indirect carbon emissions of each user are summed to obtain the total indirect carbon emissions of the region on the user side: Complete the accounting loop without considering green electricity trading scenarios.
[0055] When green electricity trading exists, the regional average carbon reduction factor should be adjusted based on the green electricity trading data to prioritize the emission reduction rights of green electricity buyers and avoid double counting of emission reduction benefits.
[0056] Preferably, in one embodiment of the present invention, after calculating the regional average carbon reduction factor based on the new energy unit data, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption in the target area, the method further includes: Obtain the total green electricity transaction volume of users within the target area and the green electricity transaction volume of each user; The average carbon reduction factor of the region is corrected based on the total amount of green electricity traded by the user, resulting in the corrected average carbon reduction factor. The carbon emission reduction of each user is calculated based on the electricity consumption and the green electricity trading volume of each user, and the actual indirect carbon emission of each user is obtained based on the carbon emission reduction and the user-side carbon emission benchmark. The total indirect carbon emissions of the target area power grid are obtained by summing up the actual indirect carbon emissions of each user.
[0057] In green electricity trading, users have clearly obtained corresponding emission reduction rights by purchasing green electricity. The benefits already traded should be deducted from the total emission reduction of green electricity in the region to avoid double sharing.
[0058] Preferably, in one embodiment of the present invention, the step of correcting the regional average carbon reduction factor based on the total amount of green electricity traded by the users to obtain the corrected average carbon reduction factor includes: Determine the total amount of green electricity traded by users within the target area; The regional average carbon reduction factor is corrected based on the total amount of green electricity traded, and is expressed as follows: in, This is the average carbon reduction factor for this region; The power generation of all green power units in the region, The total electricity consumption of users within the region; This represents the difference between the carbon emission intensity of thermal power and the carbon emission intensity of new energy sources within the region. Purchase electricity for users through green electricity trading.
[0059] When considering green electricity trading, a user's carbon emission reduction consists of two parts: direct emission reduction from green electricity trading and emission reduction from the allocation of remaining electricity, expressed as follows: Part One The green electricity purchased by users directly replaces thermal power, with emission reduction benefits calculated per unit. Calculate the full emission reduction amount to reflect the clear rights and interests in green electricity trading; Part Two The remaining green electricity emission reduction benefits of non-traded electricity are allocated according to the adjusted factor to ensure that non-traded electricity still enjoys fair allocation.
[0060] Actual indirect carbon emissions are the baseline value for all thermal power scenarios minus the total carbon emission reduction, expressed as: in, This is the baseline carbon emission value for user i under the all-thermal power scenario (consistent with the scenario without considering trading, as the baseline value is based on the all-thermal power assumption and is not affected by trading).
[0061] By summing up the actual indirect carbon emissions of each user, the total regional emissions after considering green electricity trading are obtained, thus achieving a closed-loop accounting system in the trading scenario.
[0062] S6: Integrate the actual indirect carbon emissions of each user to obtain the total indirect carbon emissions of the target area power grid on the user side.
[0063] This embodiment aggregates the actual indirect carbon emissions of individual users to form total data reflecting the overall carbon emission level of the power grid in the target area. This serves as the final verification of the previous data processing and calculation logic, and is also the core basis for supporting regional carbon emission reduction decisions and green electricity consumption assessments, achieving the accounting objectives of "accurate measurement, fair allocation, and macro-control".
[0064] One embodiment of the present invention provides a rapid indirect carbon emission calculation method. For details, please refer to [link to documentation]. Figure 2 , Figure 2 The diagram shown illustrates a rapid indirect carbon emission calculation system according to one embodiment of the present invention, which includes: The acquisition module 11 is used to acquire generation-side data, load-side data and network topology data of the power grid in the target area. The generation-side data includes data of new energy units and thermal power units, and the load-side data includes the total electricity consumption in the target area and the electricity consumption of each user. The equivalent module 12 is used to perform equivalent power flow calculation on the target area power grid based on the power generation side data, the load side data and the network topology data, and obtain the power flow calculation result; wherein, the equivalent power flow calculation is designed to convert the carbon emission intensity of each node in the new energy unit into the carbon emission intensity of the thermal power unit. Module 13 is used to construct an equivalent lossless network mapping model of electricity carbon emissions on the load side and the generation side based on the power flow calculation results, so as to obtain the user-side carbon emission benchmark value under the whole thermal power scenario. The equivalent lossless network mapping model achieves network lossless conversion by allocating node losses to downstream branches and loads according to the power flow ratio and load ratio of downstream branches. Calculation module 14 is used to calculate the regional average carbon reduction factor based on the new energy unit data, the difference in carbon emission intensity between thermal power units and new energy units, and the total electricity consumption in the target area. The calculation module 15 is used to calculate the carbon emission reduction of each user based on the average carbon reduction factor and the electricity consumption of each user, and to obtain the actual indirect carbon emission of each user based on the carbon emission reduction and the user-side carbon emission benchmark. Integration module 16 is used to integrate the actual indirect carbon emissions of each user to obtain the total indirect carbon emissions of the target area power grid on the user side.
[0065] Preferably, in one embodiment of the present invention, the accounting module is further configured to: Obtain the total green electricity transaction volume of users within the target area and the green electricity transaction volume of each user; The average carbon reduction factor of the region is corrected based on the total amount of green electricity traded by the user, resulting in the corrected average carbon reduction factor. The carbon emission reduction of each user is calculated based on the electricity consumption and the green electricity trading volume of each user, and the actual indirect carbon emission of each user is obtained based on the carbon emission reduction and the user-side carbon emission benchmark. The total indirect carbon emissions of the target area power grid are obtained by summing up the actual indirect carbon emissions of each user.
[0066] Preferably, in one embodiment of the present invention, the accounting module is further configured to: Determine the total amount of green electricity traded by users within the target area; The regional average carbon reduction factor is corrected based on the total amount of green electricity traded, and is expressed as follows: in, This is the average carbon reduction factor for this region; The power generation of all green power units in the region, The total electricity consumption of users within the region; This represents the difference between the carbon emission intensity of thermal power and the carbon emission intensity of new energy sources within the region. Purchase electricity for users through green electricity trading.
[0067] Preferably, in one embodiment of the present invention, the power flow calculation results include the active power flow, branch power flow, branch loss and load power of each node in the target area power grid; The equivalent module is specifically used for: The active power flow, the branch power flow, the branch loss, and the load power are respectively subjected to lossless conversion to obtain equivalent active power flow, equivalent branch power flow, equivalent branch loss, and equivalent load power. An equivalent lossless network mapping model is constructed based on the equivalent active power flow, the equivalent branch power flow, the equivalent branch loss, and the equivalent load power. Carbon flow tracing is performed based on the node carbon potential matrix in the equivalent lossless network mapping model to obtain the carbon emission benchmark value for each user in the full thermal power scenario.
[0068] Preferably, in one embodiment of the present invention, the building module is specifically used for: Extract the total power generation of all new energy generating units within the target area from the new energy generating unit data; Determine the first carbon emission intensity of the thermal power unit and the second carbon emission intensity of the new energy unit, and calculate the difference in carbon emission intensity between the thermal power unit and the new energy unit; The regional average carbon reduction factor is calculated based on the carbon emission intensity difference, the total power generation, and the total electricity consumption within the target area. The average carbon reduction factor is used to quantify the green electricity carbon reduction benefits that can be allocated per unit of electricity consumption within the target area.
[0069] Compared with the prior art, the beneficial effects of the embodiments of the present invention are at least one of the following: 1) This invention defines and calculates the regional average carbon reduction factor, which distributes the carbon reduction benefits generated by green electricity evenly among load nodes in the region. This breaks the problem of unfair green electricity benefits caused by differences in grid topology among users in different locations, ensures that users can fairly enjoy the rights and interests of green electricity consumption, and significantly enhances users' enthusiasm for participating in green electricity trading.
[0070] 2) This invention achieves dynamic adaptation of scenarios before and after green electricity trading by constructing an equivalent lossless network mapping model and performing a single power flow calculation. It eliminates the need to split the model or perform repeated calculations, significantly reducing computational complexity and time. At the same time, it accurately quantifies the carbon offset effect of green electricity trading, providing precise accounting support for the connection between the electricity market and the carbon market, and helping to achieve the goals of renewable energy consumption and emission reduction in the power industry.
[0071] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.
Claims
1. An indirect carbon emission rapid accounting method, characterized in that, The method comprises the following steps: obtain the power generation side data, load side data and network topology data of the target regional power grid, wherein the power generation side data includes new energy unit data and thermal power unit data, and the load side data includes total power consumption and user power consumption in the target region; based on the power generation side data, the load side data and the network topology data, perform equivalent power flow calculation on the target regional power grid to obtain power flow calculation results; wherein the equivalent power flow calculation is designed to equivalent the carbon emission intensity of each node in the new energy unit to the carbon emission intensity of the thermal power unit; construct an equivalent lossless network mapping model of load side and power side power carbon emission according to the power flow calculation results to obtain user side carbon emission benchmark value under the full thermal power scenario, wherein the equivalent lossless network mapping model realizes network lossless conversion by allocating node loss to downstream branch and load according to downstream branch power flow proportion and load proportion; based on the new energy unit data, the carbon emission intensity difference between thermal power unit and new energy unit, and the total power consumption in the target region, calculate the regional average carbon reduction factor; calculate the carbon emission reduction of each user according to the average carbon reduction factor and the user power consumption, and obtain the actual indirect carbon emission of each user according to the carbon emission reduction and the user side carbon emission benchmark value; integrate the actual indirect carbon emission of each user to obtain the total user side indirect carbon emission of the target regional power grid.
2. The indirect carbon emission quick accounting method according to claim 1, wherein, After calculating the regional average carbon reduction factor based on the new energy unit data, the carbon emission intensity difference between thermal power unit and new energy unit, and the total power consumption in the target region, the method further comprises the following steps: obtain the total green electricity trading amount of users in the target region and the green electricity trading amount of each user; correct the regional average carbon reduction factor based on the total green electricity trading amount of users to obtain the corrected average carbon reduction factor; calculate the carbon emission reduction of each user according to the user power consumption and the green electricity trading amount of each user, and obtain the actual indirect carbon emission of each user according to the carbon emission reduction and the user side carbon emission benchmark value; sum up the actual indirect carbon emission of each user to obtain the total user side indirect carbon emission of the target regional power grid.
3. The indirect carbon emission quick accounting method according to claim 2, wherein, The method for correcting the regional average carbon reduction factor based on the total green electricity trading amount of users to obtain the corrected average carbon reduction factor comprises the following steps: determine the total green electricity trading amount of users in the target region; correct the regional average carbon reduction factor based on the total green electricity trading amount of users, which is expressed as: wherein, is the average carbon reduction factor for the region; is the total electricity generation of all green power units in the region, is the total electricity consumption of all users in the region; is the difference between the carbon emission intensity of thermal power and the carbon emission intensity of new energy in the region; is the electricity purchased by the user in the green electricity transaction.
4. The indirect carbon emission quick accounting method according to claim 1, wherein, The power flow calculation results include the active power flow, branch power flow, branch loss and load power of each node in the target regional power grid; The method for constructing an equivalent lossless network mapping model of load side and power side power carbon emission according to the power flow calculation results to obtain user side carbon emission benchmark value under the full thermal power scenario comprises the following steps: perform lossless conversion on the active power flow, branch power flow, branch loss and load power respectively to obtain equivalent active power flow, equivalent branch power flow, equivalent branch loss and equivalent load power; construct an equivalent lossless network mapping model based on the equivalent active power flow, equivalent branch power flow, equivalent branch loss and equivalent load power; Carbon flow tracking is performed in the equivalent lossless network mapping model based on a node carbon potential matrix to obtain carbon emission benchmark values of each user in a full thermal power scenario.
5. The indirect carbon emission quick accounting method according to claim 1, wherein, The regional average carbon reduction factor is calculated based on the new energy unit data, the carbon emission intensity difference between the thermal power unit and the new energy unit, and the total power consumption in the target region, including: Extracting the total power generation of all new energy units in the target region from the new energy unit data; Determining the first carbon emission intensity of the thermal power unit and the second carbon emission intensity of the new energy unit, and calculating the carbon emission intensity difference between the thermal power unit and the new energy unit; Based on the carbon emission intensity difference, the total power generation and the total power consumption in the target region, the regional average carbon reduction factor is calculated, wherein the average carbon reduction factor is used to quantify the green electricity carbon emission reduction benefit that can be allocated per unit of power consumption in the target region.
6. An indirect carbon emission quick accounting system, characterized in that, Including: An acquisition module is configured to acquire power generation side data, load side data and network topology data of a target regional power grid, wherein the power generation side data includes new energy unit data and thermal power unit data, and the load side data includes total power consumption and user power consumption in the target region; An equivalent module is configured to perform equivalent power flow calculation on the target regional power grid based on the power generation side data, the load side data and the network topology data to obtain a power flow calculation result; wherein the equivalent power flow calculation is designed to equivalent the carbon emission intensity of each node in the new energy unit to the carbon emission intensity of the thermal power unit; A construction module is configured to construct an equivalent lossless network mapping model of load side and power generation side carbon emission based on the power flow calculation result to obtain user side carbon emission benchmark values in a full thermal power scenario, wherein the equivalent lossless network mapping model realizes network lossless conversion by allocating node loss to downstream branch and load according to downstream branch power flow proportion and load proportion; A calculation module is configured to calculate a regional average carbon reduction factor based on the new energy unit data, the carbon emission intensity difference between the thermal power unit and the new energy unit, and the total power consumption in the target region; An accounting module is configured to calculate the carbon emission reduction amount of each user according to the average carbon reduction factor and the user power consumption, and obtain the actual indirect carbon emission amount of each user according to the carbon emission reduction amount and the user side carbon emission benchmark value; An integration module is configured to integrate the actual indirect carbon emission amount of each user to obtain the total user side indirect carbon emission amount of the target regional power grid.
7. The indirect carbon emission quick accounting system of claim 6, wherein, The accounting module is further configured to: Obtain the total green electricity trading amount of users in the target region and the green electricity trading amount of each user; Based on the total green electricity trading amount of users, the regional average carbon reduction factor is corrected to obtain a corrected average carbon reduction factor; Calculate the carbon emission reduction amount of each user according to the user power consumption and the green electricity trading amount of each user, and obtain the actual indirect carbon emission amount of each user according to the carbon emission reduction amount and the user side carbon emission benchmark value; Summarize the actual indirect carbon emission amount of each user to obtain the total user side indirect carbon emission amount of the target regional power grid.
8. The indirect carbon emission quick accounting system of claim 7, wherein, The accounting module is further configured to: Determine the total green electricity trading amount of users in the target region; The regional average carbon reduction factor is corrected based on the total green electricity transaction electricity quantity, and is expressed as: wherein, is the average carbon reduction factor of the region; is the total power generation of all green power units in the region, is the total power consumption of all users in the region; is the difference between the carbon emission intensity of thermal power and the carbon emission intensity of new energy in the region; is the amount of electricity purchased by the user in the green electricity transaction.
9. The indirect carbon emission quick accounting system of claim 6, wherein, The power flow calculation result includes active power flow, branch power flow, branch loss and load power of each node in the target regional power grid; The equivalent module is specifically configured to: The active power flow, the branch power flow, the branch loss and the load power are losslessly converted respectively to obtain equivalent active power flow, equivalent branch power flow, equivalent branch loss and equivalent load power; An equivalent lossless network mapping model is constructed based on the equivalent active power flow, the equivalent branch power flow, the equivalent branch loss and the equivalent load power; Carbon flow tracking is performed in the equivalent lossless network mapping model based on a node carbon potential matrix to obtain carbon emission benchmark values of each user under a full thermal power plant scenario.
10. The indirect carbon emission quick accounting system of claim 6, wherein, The construction module is specifically configured to: Extract total power generation of all new energy units in the target region from the new energy unit data; Determine a first carbon emission intensity of the thermal power unit and a second carbon emission intensity of the new energy unit, and calculate a carbon emission intensity difference value between the thermal power unit and the new energy unit; Calculate a regional average carbon reduction factor based on the carbon emission intensity difference value, the total power generation and total power consumption in the target region, wherein the average carbon reduction factor is used to quantify green electricity carbon emission reduction benefits that can be allocated per unit of power consumption in the target region.