Method for measuring regional carbon emissions considering location fairness

Abstract

The application provides a kind of area carbon emission metering method considering position fairness, comprising obtaining the network parameters of target power system, source load operation data, unit carbon emission intensity data and clean energy unit planning construction level information, solving power system power flow distribution, based on carbon emission flow theory Mathematical model of coupling of power flow-carbon flow is constructed, also includes: constructing network loss carbon emission allocation model with adjustable allocation proportion coefficient, respectively tracing carbon emission to power supply side and load side;Determine the corresponding shared area, build low-carbon benefit sharing virtual network;Based on linear superposition theorem, the low-carbon benefit sharing virtual network is decomposed from the original power flow network corresponding to the mathematical model of coupling of power flow-carbon flow, to obtain the remaining natural distribution network;Solving the node carbon flow rate of each network, the reconstruction of the whole network carbon emission distribution is completed by linear superposition, to obtain the carbon emission metering result of target power system considering position fairness.

Description

Technical Field

[0001] This invention belongs to the field of low-carbon operation and carbon emission metering technology of electric power systems, and specifically relates to a regional carbon emission metering method that takes into account location fairness. Background Technology

[0002] As a large-scale interconnected energy transmission and conversion system, the power system has a natural spatiotemporal separation between power production and consumption. Power loss is inevitable during power grid transmission. The carbon emission intensity varies significantly between different regions and different types of power sources. This makes the carbon emissions throughout the entire life cycle of power deeply coupled with the physical operating characteristics and power flow distribution patterns of the power system.

[0003] While the current mainstream average carbon emission factor method is simple to implement and easy to calculate, its technical essence is to treat the entire interconnected power grid as an indiscriminate carbon emission black box. It completely ignores the spatiotemporal dynamic characteristics of power flow distribution in the power system. It cannot reflect the impact of the spatial layout of different power sources and the power output structure at different times on carbon emission intensity, nor can it establish the correspondence between carbon emissions and actual power flow transmission paths and source-load nodes. As a result, the metering results cannot accurately reflect the actual carbon emission responsibilities of different nodes and different users, making it difficult to achieve accurate traceability of carbon emission responsibilities. It also cannot provide quantitative data with physical guidance for user-side energy optimization and grid-side low-carbon dispatch.

[0004] In analytical methods based on carbon emission flow theory, the allocation of carbon emissions from network losses is one of the core technical challenges. Active power loss in power networks is an inevitable physical quantity generated during power transmission. Its generation is directly related to power output characteristics, load consumption characteristics, grid structure parameters, and system operation modes. Existing research either simply allocates all carbon emissions corresponding to network losses to a single entity on the power source or load side, violating the physical mechanism of network loss generation and leading to a disconnect between carbon emission responsibility allocation and the actual physical process; or it performs loss allocation based on complex power flow tracking, which, influenced by the phase characteristics of complex power, easily results in negative active power loss allocation. This result completely contradicts the basic physical laws of active power transmission in power systems, rendering the carbon emission measurement results related to losses meaningless.

[0005] Meanwhile, existing carbon emission tracking methods are constrained by the natural distribution of power flows, resulting in an inherent flaw of proximity effect. This means that electricity is preferentially transmitted along the path of least impedance, limiting the low-carbon benefits of renewable energy units to their nearest surrounding nodes. However, the carbon emission intensity of nodes surrounding thermal power units remains consistently high, and the carbon flow distribution is entirely determined by the physical impedance characteristics of the power grid. This makes it impossible to technically constrain and regulate the carbon emission radiation range of clean energy units. Furthermore, the development and construction of clean energy in the power system exhibits a clear hierarchical planning characteristic. The coverage of low-carbon benefits from clean energy units constructed by entities at different levels needs to match the planning and construction level. Existing methods cannot establish a correspondence between the coverage of low-carbon benefits and the planning level of clean energy, making it difficult to achieve a reasonable distribution of the low-carbon benefits from clean energy development at different levels within the corresponding regions.

[0006] These technical issues directly constrain the accuracy, physical consistency, and regional equity of carbon emission measurement in the power system, and urgently require new technical solutions. Summary of the Invention

[0007] To address the shortcomings and deficiencies of existing technologies, this invention provides a regional carbon emission measurement method that considers locational fairness. This method is based on the theory of carbon emission flows in power systems and the superposition theorem of linear networks, closely coupling the physical characteristics of power flow transmission in power systems to achieve accurate measurement and fair allocation of carbon emissions throughout the entire process of electricity production, transmission, and consumption. Addressing the core pain points of existing carbon emission measurement methods, such as the disconnect between the network loss carbon emission allocation mechanism and the physical mechanism, and the tendency to result in negative allocation of active power losses, this invention constructs a network loss carbon emission allocation model with an adjustable allocation ratio coefficient. It employs a two-way power flow tracking method (both with and against the current flow) to achieve flexible and accurate allocation of carbon emission responsibility corresponding to network active power losses on the power source and load sides, ensuring consistency between loss-related carbon emission measurement results and the physical operation of the power system. Addressing the inherent proximity effect of existing carbon emission flow tracking methods, this invention adapts to the hierarchical scheduling architecture of the power system and the hierarchical planning characteristics of clean energy. It decouples the power network into multiple virtual networks and constructs a low-carbon benefit sharing virtual network that matches the planning hierarchy of clean energy. This achieves technical constraints on the carbon emission radiation range of clean energy units, breaking the limitations of natural power flow distribution on the coverage of low-carbon benefits and ensuring fair sharing of low-carbon benefits from clean energy development at different levels within the corresponding regions. Simultaneously, it can be adapted to green electricity trading scenarios by synchronously splitting corresponding virtual networks, solving industry problems such as double-counting of green electricity environmental benefits and difficulty in attributing network loss carbon emissions in trading scenarios. This invention performs carbon emission flow distribution calculations on each of the split virtual networks separately, and then reconstructs the carbon emission distribution of the entire network through linear superposition. This not only achieves locational fairness in regional carbon emission measurement, but also accurately tracks carbon flow transmission paths and completes full-link traceability of carbon emission responsibility. The spatial granularity of the measurement results can be flexibly matched with the power system dispatching level, providing accurate and scientific quantitative support for carbon accounting, carbon emission responsibility allocation, carbon market operation, low-carbon dispatching, and clean energy planning in the power industry.

[0008] The specific technical solution adopted by this invention to solve its technical problem is as follows:

[0009] A regional carbon emission measurement method considering location equity includes acquiring network parameters, source-load operation data, unit carbon emission intensity data, and clean energy unit planning and construction hierarchy information of the target power system; solving for the power flow distribution of the power system; constructing a power flow-carbon flow coupling mathematical model based on carbon emission flow theory; and further includes:

[0010] A network loss carbon emission allocation model with an adjustable allocation ratio coefficient is constructed. A two-way power flow tracing method with and against the power flow is adopted to trace the carbon emissions corresponding to the active power loss of the network to the power supply side and the load side respectively. During the tracing process, the real part of the calculation result is taken to eliminate the negative allocation result of active power loss caused by the complex power phase characteristics. The allocation of network loss carbon emission responsibility to the power supply side and the load side is completed according to the adjustable allocation ratio coefficient.

[0011] Based on the planning and construction level of the clean energy units, the corresponding sharing area is determined. According to the active power ratio of each load in the sharing area, the active power output of the corresponding clean energy units is allocated to each load in the sharing area to construct a low-carbon benefit sharing virtual network. Based on the linear superposition theorem, the low-carbon benefit sharing virtual network is decomposed from the original power flow network corresponding to the power flow-carbon flow coupling mathematical model to obtain the remaining natural distribution network.

[0012] Carbon emission flow distribution is calculated for the low-carbon benefit sharing virtual network and the remaining natural distribution network respectively. The node carbon flow rate of each network is solved. The carbon emission distribution of the entire network is reconstructed by linear superposition, and the carbon emission measurement results of the target power system considering location fairness are obtained.

[0013] Furthermore, the adjustable sharing ratio coefficient is the proportion of network loss carbon emission responsibility borne by the load side. Its value is calculated and determined based on at least one of the technical indicators of the target power system, such as line load rate, source-load distribution ratio, and grid structure parameters, or is determined by the carbon emission responsibility management agency.

[0014] Furthermore, the planning and construction level of the clean energy units corresponds to the dispatch level of the power system dispatching system.

[0015] Furthermore, when tracing the carbon emissions corresponding to the active power loss of the network, the network loss power in the power flow tracking model is replaced with the solved network loss carbon flow rate, and then bidirectional tracking calculations are carried out for both upstream and downstream power flows.

[0016] Furthermore, it also includes green electricity trading adaptation steps: obtaining green electricity trading contract data of the target power system, splitting the actual power flow into trading power flow and non-trading natural power flow based on the power transmission distribution factor, and constructing a green electricity trading virtual network; based on the linear superposition theorem, separating the green electricity trading virtual network from the original power flow network, and synchronously updating the remaining natural distribution network.

[0017] Furthermore, in the calculation of carbon emission flows in the green electricity trading virtual network, the carbon emission factor of the trading volume corresponding to the medium- and long-term green electricity trading under the certificate-electricity integration mode is calculated as 0, while the trading volume corresponding to the spot green electricity trading is calculated using the average carbon emission factor of the participating clearing units.

[0018] Furthermore, regarding the carbon emissions from branch network losses between the green electricity trading virtual network and the remaining natural distribution network, the allocation is based on the power flow distribution: if the power flow of the branch in the remaining natural distribution network is 0 or negative, the green electricity trading virtual network does not bear the network loss of the branch; if the power flow is positive, the carbon emissions from the branch network losses are allocated according to the proportion of the power flow of the remaining natural distribution network to the total active power flow of the branch.

[0019] Furthermore, when simultaneously splitting the green electricity trading virtual network and the low-carbon benefit sharing virtual network, the active power of the units in the remaining naturally distributed network is the total active power of the units minus the active power they participate in green electricity trading and the shared active power, and the active power of the loads in the remaining naturally distributed network is the total active power of the loads minus the active power they participate in green electricity trading and the shared active power.

[0020] Furthermore, the reconfiguration of the carbon emission distribution across the entire network follows the principle of conservation of the total direct and indirect carbon emissions of the power system, and the total carbon emissions of the entire system do not change with the process of network splitting and superimposed reconfiguration.

[0021] Furthermore, a system for a regional carbon emissions measurement method that considers locational equity includes a processor and a memory storing a computer program, wherein the processor executes the computer program to implement the method described above.

[0022] A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0023] Compared to existing technologies, this invention and its preferred solution closely couple with the physical characteristics of power flow transmission in power systems, effectively solving the core problem in existing carbon emission metering methods where the allocation of carbon emissions from network losses is disconnected from physical mechanisms, easily leading to calculation results that do not conform to physical laws. It achieves a flexible and reasonable allocation of carbon emission responsibility corresponding to network active power losses between the power source and load sides, significantly improving the physical consistency and accuracy of carbon emission metering results and providing a reliable technical basis for carbon emission responsibility allocation. It breaks through the inherent proximity effect limitation of existing carbon emission flow tracking methods, enabling technical constraints on the carbon emission radiation range of clean energy units. Adapting to the industry characteristics of hierarchical power system dispatch architecture and hierarchical clean energy planning, it achieves fair sharing of low-carbon benefits from clean energy development at different levels within corresponding regions, fundamentally ensuring the locational fairness of regional carbon emission metering. It enables precise tracking and tracing of carbon emissions across the entire process of electricity production, transmission, and consumption. This provides quantifiable data with physical guidance for low-carbon grid dispatch, user-side energy optimization, and coordinated carbon reduction across power sources, grids, and loads. It is also flexibly adaptable to market-based applications such as green electricity trading, effectively solving industry challenges such as double-counting of green electricity environmental benefits and difficulty in attributing carbon emissions from grid losses in trading scenarios. This ensures the scientific rigor and fairness of carbon accounting across different trading scenarios. Furthermore, it allows for flexible matching of the spatial granularity of carbon emission measurement with the power system dispatching hierarchy, ensuring both measurement accuracy and engineering practicality. It provides scientific and stable technical support for regional power system carbon planning, low-carbon operation scheme development, power industry carbon accounting, and carbon market operation, comprehensively improving the scientific rigor, fairness, and practicality of regional carbon emission measurement. This provides a solid foundation for the low-carbon transformation of the power industry. Attached Figure Description

[0024] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0025] Figure 1 This is a power system power flow-carbon flow model diagram according to an embodiment of the present invention;

[0026] Figure 2 This is a flowchart illustrating the calculation process of a location-fair regional carbon emission measurement method according to an embodiment of the present invention. Detailed Implementation

[0027] To make the features and advantages of the present invention more apparent and understandable, specific embodiments are described below in detail:

[0028] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0029] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0030] This embodiment provides a regional carbon emission measurement method that considers locational fairness. This method is based on the carbon emission flow theory of the power system and the superposition theorem of linear networks, and closely couples the physical characteristics of power flow transmission in the power system to achieve accurate measurement and fair allocation of carbon emissions throughout the entire process of power generation, transmission and consumption.

[0031] First, this method introduces an adjustable allocation coefficient to construct a network loss sharing model. By setting virtual nodes, the active power loss of power network lines is equivalent to a virtual load. Combining the two-way power flow tracking method with and against the current flow, a proportional sharing allocation mechanism based on active power network losses is proposed to achieve accurate and adjustable allocation of network active power losses on the power source and load sides. This process is based on the physical laws of active power transmission in the power system to carry out loss sharing. It can not only fully reflect the impact of power transmission on loss distribution, but also effectively overcome the technical defects of existing complex power flow tracking methods that are prone to negative active power allocation. It avoids the deviation in carbon emission responsibility allocation caused by unreasonable loss allocation and ensures the consistency between loss-related carbon emission measurement results and the physical operation of the power system.

[0032] Secondly, this method is adapted to the hierarchical dispatch architecture of the power system, and performs hierarchical decoupling decomposition of the actual power flow network based on the superposition theorem. On the one hand, according to the physical power flow characteristics corresponding to green electricity trading, a virtual network for green electricity trading and a basic power flow network are obtained; on the other hand, according to the planning and construction hierarchy of clean energy units, the network is further decomposed into a shared network and a naturally distributed network, completing the decoupling and separation of shared units and shared loads, and constructing a corresponding virtual network model. Through the above network decomposition operation, the carbon emission radiation range of clean energy units at different levels can be clearly defined, realizing the technical constraint on the carbon flow distribution of shared units, and solving the proximity effect defect of existing carbon emission flow tracking methods caused by the constraint of natural power flow distribution.

[0033] Based on this, this method uses carbon emission flow theory to calculate the carbon emission distribution of each decomposed virtual network, solves the node carbon flow rate of the green electricity trading virtual network, the sharing network and the natural distribution network, and then reconstructs the carbon emission distribution of the entire network through linear superposition. This enables the reasonable sharing of low-carbon benefits of clean energy units at different levels in the corresponding regions and ensures the locational fairness of regional carbon emission measurement.

[0034] This method strictly adheres to the principle of conservation of total direct and indirect carbon emissions in the power system, achieving multi-dimensional technological breakthroughs while ensuring the accuracy of carbon emission measurement results. Through an adjustable allocation coefficient and a loss-sharing mechanism based on bidirectional power flow tracking, it effectively solves the core technical problems of unfair network loss allocation and negative active power distribution in existing technologies. This enables flexible and reasonable allocation of active power losses between power sources and loads, providing a precise and reliable technical basis for the division of carbon emission responsibilities. By using a network layering decoupling method adapted to a hierarchical dispatch architecture, it clarifies the scope of low-carbon benefit sharing for clean energy units at each level, ensuring the consistency of carbon emission factors among users within the corresponding sharing area. This promotes the fair sharing of low-carbon benefits from clean energy across multi-level power grids and achieves a reasonable division of regional carbon emission responsibilities. Simultaneously, this method can accurately track the transmission path of carbon flow in the power network, clarify the carbon flow allocation relationship from each generating unit to different load nodes, and achieve intuitive source tracing of indirect carbon emissions. This provides precise quantitative data support for grid low-carbon dispatch decisions and user-side energy consumption optimization, contributing to coordinated emission reduction across all aspects of the power system. By combining network decomposition and carbon flow superposition and reconstruction, this method effectively overcomes the inherent spatial proximity effect of carbon emission flow tracking, achieving controllable constraints on the carbon emission radiation range of shared generating units. It matches the spatial granularity of carbon emission measurement with the power system dispatch hierarchy, avoiding the increased measurement complexity caused by excessive refinement while accurately reflecting the differences in carbon emission levels between different regions. This provides a scientific and technical reference for regional power system carbon planning and the formulation of low-carbon operation schemes. In summary, this method can comprehensively improve the scientific rigor, fairness, and practicality of regional carbon emission measurement, providing stable and reliable technical support for the low-carbon transformation of the power system.

[0035] The implementation of the present invention will be further demonstrated and described below with reference to the accompanying drawings through more specific embodiments:

[0036] 1. Carbon Emission Flow Tracking Model for Power Systems

[0037] Energy losses in power grid lines significantly impact the measurement of indirect carbon emissions from the power grid. To understand the distribution of carbon flow rates within the system and achieve comprehensive carbon emission analysis across the entire power source-grid-load chain, it is necessary to calculate and trace the carbon flow rates of network losses, thereby clarifying the responsibility for allocating these losses. Accurate network loss tracking methods help clarify the allocation of power system costs and improve resource allocation efficiency. Reasonable allocation of network loss carbon emissions helps clarify carbon emission responsibilities and promotes coordinated carbon reduction across the power system's power source-grid-load chain.

[0038] Figure 1 The power flow-carbon flow model diagram of the power system is shown below. Based on the basic definition of carbon emission flow and combined with the power flow calculation results, the carbon flow rate distribution of the system can be obtained. Assuming there are n nodes, p generator nodes, and m branches in the power grid, the equation for solving the carbon flow rate distribution of the system is as follows:

[0039]

[0040]

[0041]

[0042] In the formula: R U-N The generator-node carbon flow correlation matrix represents the contribution of the carbon flow rate injected by all generator units in the system to the carbon flow rate at any node in the system; diag indicates the conversion of a vector into a diagonal matrix; E G P is the carbon emission intensity vector of the generator set; N Let P be the node active power flux matrix, an n×n dimensional matrix representing the node injected power; B Let P be the active power flow distribution matrix of the branch, which is an n×n dimensional matrix; the superscripts "T" and "-1" indicate matrix transpose and inversion, respectively; G The active power injection distribution matrix of the unit is a p×n dimensional matrix; R U-L The generator-load carbon flow correlation matrix represents the contribution of carbon emission flows injected by all generator units in the system to the carbon flow rate at each load node; ζ N P is an n-dimensional row vector with all elements equal to 1. L Let R be the load active power distribution matrix, which is an n×n dimensional matrix; L,i Let be the load carbon flow rate of node i.

[0043] The nodal load carbon flow rate obtained by solving the above formulas (1)-(3) This represents the carbon emission flow rate corresponding to a load node under ideal conditions, neglecting network losses. However, in actual power grid operation, active power losses on lines generate additional carbon emissions, requiring power flow tracing to trace these emissions back to the corresponding power source and load. The core principle of power flow tracing is based on the law of power conservation, tracing the source and destination of power at nodes. This invention replaces the physical quantity tracked in the power flow tracing model from active power to the corresponding network loss carbon flow rate, thereby achieving full-link traceability of network loss carbon emissions. The specific derivation process is as follows:

[0044] Based on the power flow tracing theory, a network loss carbon flow rate tracing method is derived. The network loss power in the power flow tracing model is replaced with the solved network loss carbon flow rate, thereby avoiding the unreasonable phenomenon that the source tracing result is negative due to the excessive phase difference of some complex power.

[0045] The proposed static network loss carbon flow rate tracking method is as follows, tracing back to the power source. carbon flow rate of network loss For:

[0046]

[0047] In the formula: Re represents the real part of the result; For nodes Injected power; for Upstream distribution matrix; For the first The output of the Taiwanese unit; For nodes Flow to Node The complex power; For nodes The set of upstream nodes.

[0048] Tracing back to the load carbon flow rate of network loss for:

[0049]

[0050] In the formula: for Downstream distribution matrix; For nodes The set of downstream nodes; For the first The power of each load.

[0051] The carbon flow rate can be traced back to both the source and load sides using the power flow tracing method, thus allocating the responsibility for grid loss carbon emissions to both sides. To this end, an adjustable parameter λ is introduced to characterize the allocation ratio coefficient, with a value range of [0,1]. This coefficient represents the proportion of carbon emission responsibility borne by the corresponding load. The specific value is affected by the system operating conditions and can be calculated based on objective technical indicators such as grid line load rate, source-load distribution ratio, and grid structure parameters. Alternatively, it can be determined by the superior agency responsible for carbon emissions, taking into account technical indicators. The corresponding grid loss carbon flow rates for the load and power source are as follows:

[0052]

[0053] The carbon flow rate traced back to the load and the carbon flow rate traced back to the power source can be expressed as:

[0054]

[0055] In the formula: The carbon flow rate is traced back to load i; The carbon flow rate of the network loss is traced back to unit k.

[0056] As a further preferred implementation method, the adjustable allocation ratio coefficient λ is calculated using a multi-factor weighted normalization method, and the specific calculation formula is as follows:

[0057]

[0058] In the formula: , , Let be the weighting coefficient, satisfying + + =1, the weighting coefficient can be set according to the power grid operation characteristics and management needs; This is a normalization factor based on line load rate, and its value is the ratio of the average line load rate of the entire network to the benchmark load rate, where the benchmark load rate is 70% of the rated load rate of the power grid. It is a normalization coefficient based on the source-load distribution ratio, and its value is the ratio of the total active power of the entire network load to the total active power of the power source. The normalization coefficient is based on the grid structure parameters and is taken as the ratio of the average unit impedance of the entire network lines to the reference unit impedance. The reference unit impedance is taken as the rated unit impedance of the main power grid line. The adjustable sharing ratio coefficient λ has a value range of 0≤λ≤1.

[0059] As a further preferred implementation method, when the power grid is in peak load operation, the weighting coefficient is increased. The value of [value] is adjusted to strengthen the impact of line load rate on the allocation ratio; when the power grid is operating under conditions of high renewable energy generation, the weighting coefficient is increased. The value of is used to strengthen the influence of the source load distribution ratio on the allocation ratio.

[0060] 2 Carbon Emission Accounting Model for Green Electricity Trading in the Power System

[0061] The environmental value of green electricity is becoming increasingly prominent. However, in trading scenarios, carbon emission measurement is prone to double-counting of environmental benefits, necessitating the development of a scientific measurement method that combines trading characteristics with accounting principles. From the perspective of trading scenario classification, the core model of green electricity trading is "certificate-electricity integration," meaning that users simultaneously obtain accompanying green certificates when purchasing green electricity, thus acquiring both the energy and environmental value of the green electricity. Furthermore, it is necessary to consider various green certificate trading scenarios, such as power generators purchasing green certificates and users purchasing "certificate-electricity separation" green certificates, clarifying the differences in carbon emission deduction mechanisms under different scenarios.

[0062] The accounting must adhere to four core principles: First, the "green electricity and green certificate binding principle," meaning that the real-time green certificate quantity of new energy power plants should be consistent with their green electricity production; second, the "one-time incentive principle for environmental attributes," meaning that after green certificates are used for deduction, the corresponding green electricity loses its zero-carbon attribute; third, the "unbiased principle for total carbon emissions," meaning that the carbon emission responsibility for deductions must be borne by other entities to ensure the balance of the total carbon emissions of the system; and fourth, the "principle of fairness in carbon accounting," ensuring fair accounting for similar users through the averaging of emission factors.

[0063] As a further preferred implementation method, the specific steps for separating transaction flow and non-transaction natural flow based on the power transmission distribution factor are as follows:

[0064] The first step is to calculate the power transmission distribution factor matrix of the target power system, where the elements PTDF are... ij This represents the change in active power flow in branch i when node j injects a unit of active power. Its calculation is based on the impedance matrix of the power grid nodes and the branch parameters, and is a well-known calculation method in this field.

[0065] The second step is to determine the injected power of the power supply nodes and the outflow power of the load nodes based on the green electricity trading contract, and then calculate the power flow distribution of the trading power in each branch of the network by combining the power transmission distribution factor matrix.

[0066] The third step is to subtract the transaction flow from the actual total active flow of each branch to obtain the non-transactional natural flow, thus completing the decoupling and separation of the transaction flow and the non-transactional natural flow.

[0067] In terms of specific measurement methods, power flow needs to be decomposed first. Based on medium- and long-term green electricity transactions, such as directional power supply contracts signed between users and new energy power plants and spot green electricity transactions, the actual power flow is decomposed into transaction flow and non-transactional natural flow using the power transmission distribution factor. Specifically, after obtaining the network-wide "certificate-power integration" green electricity transaction contract data, the source loads related to the transaction can be separated from the original power flow network using the superposition theorem.

[0068]

[0069]

[0070] In the formula: Let i be the power of the remaining natural network load. Let i be the load power of load i; The load power of load i participating in green electricity trading; The power of the remaining natural network unit k; Let k be the active power of unit k; The active power of unit k participating in the green electricity trading contract.

[0071] In medium- and long-term green electricity trading, due to its "point-to-point" nature, the carbon emission factor of the traded electricity can be directly calculated as 0, and users do not need to bear the carbon emission responsibility for this portion. Spot green electricity trading uses the average carbon emission factor of the participating clearing units for calculation. For the "certificate-electricity separation" green certificate trading scenario, if a power generator purchases green certificates to offset its own carbon emissions, the corresponding carbon emission intensity of the power generator is reduced, and the unit's carbon emission vector is adjusted accordingly. If a user purchases green certificates separately, only the carbon emissions corresponding to the non-traded natural current flow can be offset; the carbon emissions from the green electricity trading portion cannot be offset repeatedly, ensuring the overall carbon emission balance of the system. Subsequently, the carbon emission calculation for non-traded electricity is based on the carbon emission flow calculation results, combined with the separated natural current flow and unit carbon emission information, to obtain the real-time carbon emission factor for non-traded electricity. If there is a transfer of carbon emission responsibility caused by green certificate trading, the unit's carbon emission vector is adjusted accordingly to ensure that the metering results reflect the responsibility allocation in real time.

[0072] To address the difficulty in attributing network loss carbon emissions resulting from green electricity trading, this invention proposes a network loss attribution method based on power flow distribution. After obtaining the remaining natural network power flow distribution, if nodes i and j are connected by branches in the actual power flow distribution and there is network loss power... If the current flow direction of the branch is determined, and the current flow between nodes i and j is 0 or negative in the remaining natural current flow, the green electricity transaction will not bear the network loss of the branch. Otherwise, if the current flow is positive, the network loss will be shared according to the proportion of the current flow.

[0073]

[0074]

[0075] In the formula: The power loss to be borne by the natural distribution of the remaining power flow; max(a,b) represents taking the larger value of a and b; This represents the active power flow of branch ij in the residual power flow natural distribution network; This indicates the active power loss of the branch circuits borne by the green electricity trading network.

[0076] 3. Regional Sharing Model of Low-Carbon Benefits in Power Systems

[0077] Carbon emission responsibility allocation methods based on the natural distribution of tidal currents follow the "local consumption" characteristic, meaning that power generated by power plants will prioritize supplying local consumption, resulting in users in the locations of clean energy power plants receiving more significant low-carbon benefits. Therefore, considering the principle of fairness, the low-carbon benefits of clean energy power sources built at different levels should be shared within that level.

[0078] The specific implementation method is as follows: Based on the obtained lossless network, the shared units and shared loads are split to obtain a shared network and a naturally distributed network, thereby constraining the power flow and carbon flow of the units. Then, the carbon emission flow of the two parts of the network is calculated according to the carbon emission flow theory, and finally the two calculation results are superimposed to reconstruct the carbon emission distribution.

[0079] To separate shared generating units from shared loads in the network, information on the shared generating units and shared loads must first be obtained. The definition of the shared area is determined by the region where the shared generating unit is located and the entity that invested in and constructed the unit. This can be adapted to the current five-level dispatch system. For example, the low-carbon benefits generated by clean energy generating units planned and constructed under the leadership of a municipal power grid company should be shared by the entire city, while the low-carbon benefits generated by clean energy generating units planned and constructed under the leadership of a provincial power grid company should be shared by the entire province.

[0080] As a further preferred implementation method, the technical definition rules for the shared area are as follows:

[0081] 1. Hierarchical Matching Rules: The administrative / dispatch boundaries of the shared area strictly correspond to the hierarchical level of the planning and construction entity of the shared unit. Specifically: For cross-regional clean energy units planned and constructed under the leadership of the national energy authority, the shared area is the corresponding cross-provincial and cross-regional power receiving range; for clean energy units planned and constructed under the leadership of a provincial power grid company, the shared area is the entire power supply range of that provincial power grid; for clean energy units planned and constructed under the leadership of a municipal power grid company, the shared area is the entire power supply range of that municipal power grid; for clean energy units planned and constructed under the leadership of a district / county or lower-level entity, the shared area is the power supply business range corresponding to that entity.

[0082] 2. Node attribution rules: Load nodes within the shared area are all metering load nodes that are electrically connected to the power grid and fall within the jurisdiction of the corresponding dispatching level;

[0083] 3. Boundary Locking Rule: Once the boundary of the shared area is determined, it shall remain fixed within a metering cycle and shall not be adjusted according to the dynamic changes in the power flow distribution of the power grid.

[0084]

[0085] In the formula: N represents the shared power of shared load i; N is the set of nodes in the level to which unit k belongs; This represents the shared active power of unit k.

[0086] Given a fixed shared generating unit power, the shared load power is allocated based on the proportion of the original load power within the shared area, thus constructing a point-to-area virtual network of shared generating units and shared loads. After the virtual network is constructed, the natural distribution network can be obtained using the superposition theorem. If this is calculated simultaneously with the green electricity trading split, then:

[0087]

[0088]

[0089] As a further preferred implementation method, the construction of the green electricity trading virtual network and the low-carbon benefit sharing virtual network follows the linear network superposition theorem. The two virtual networks are in a parallel and decoupled relationship, with no fixed order of construction. They can be constructed simultaneously and split at once, or constructed separately and split sequentially. Regardless of the construction order, the power balance rules of the remaining natural distribution network follow formulas (13)-(14). The total active power and total carbon emissions of the entire network remain constant. The splitting process does not change the physical power flow distribution and total carbon emission level of the power grid.

[0090] The carbon emission flow distribution of the decomposed networks was solved using the carbon emission flow theory from the previous section.

[0091]

[0092]

[0093]

[0094] In the formula: Carbon flow rate under shared load; The load carbon flow rate of the remaining natural network; Inject power into the remaining natural network nodes; Carbon emissions from the reconfigured load nodes.

[0095] Based on the construction of the above model, such as Figure 2 As shown, the specific implementation steps of the regional carbon emission measurement method considering location fairness proposed in this embodiment of the invention are as follows:

[0096] Step 1: Based on the network parameters and source-load data of the power system, solve the power flow distribution of the power system, and generate a mathematical model of power flow-carbon flow coupling based on carbon emission flow theory.

[0097] Step 2: Acquire contract data for green electricity trading, regionally shared unit and shared area data in parallel, and simultaneously generate a point-to-point green electricity virtual power flow network for the "certificate and electricity integration" trading model, and generate a point-to-area low-carbon shared virtual power flow network for shared units and shared loads according to the load ratio to allocate low-carbon benefits. Using the superposition theorem, split the above two parallel generated virtual power flow networks from the original power flow network solved in Step 1 at one time to obtain the final remaining natural distribution network.

[0098] Step 3: Solve the carbon emission flow distribution of the virtual power flow network for green electricity trading, the virtual power flow network for low-carbon benefit sharing, and the final remaining natural network using the power flow-carbon flow coupling model. Then, combine the carbon emission flows of the above three networks according to the superposition theorem to obtain the carbon emission flow distribution of the power system including green electricity trading and low-carbon benefit sharing.

[0099] Based on the same inventive concept, this invention also provides a computer device, comprising: one or more processors, and a memory for storing one or more computer programs; the programs include program instructions, and the processor executes the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, used to implement one or more instructions, specifically for loading and executing one or more instructions stored in a computer storage medium to implement the above-described method.

[0100] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, performs the above-described method. This storage medium can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0101] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0102] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

[0103] This invention is not limited to the preferred embodiment described above. Anyone inspired by this invention can derive other various methods for measuring regional carbon emissions that take into account location fairness. All equivalent variations and modifications made within the scope of the claims of this invention shall fall within the scope of this invention.

Claims

1. A regional carbon emission measurement method considering location equity, comprising acquiring network parameters, source-load operation data, unit carbon emission intensity data, and clean energy unit planning and construction hierarchy information of the target power system; solving the power flow distribution of the power system; and constructing a power flow-carbon flow coupled mathematical model based on carbon emission flow theory, characterized in that... Also includes: A network loss carbon emission allocation model with an adjustable allocation ratio coefficient is constructed. A two-way power flow tracing method with and against the power flow is adopted to trace the carbon emissions corresponding to the active power loss of the network to the power supply side and the load side respectively. During the tracing process, the real part of the calculation result is taken to eliminate the negative allocation result of active power loss caused by the complex power phase characteristics. The allocation of network loss carbon emission responsibility to the power supply side and the load side is completed according to the adjustable allocation ratio coefficient. Based on the planning and construction level of the clean energy units, the corresponding sharing area is determined. According to the active power ratio of each load in the sharing area, the active power output of the corresponding clean energy units is allocated to each load in the sharing area to construct a low-carbon benefit sharing virtual network. Based on the linear superposition theorem, the low-carbon benefit sharing virtual network is decomposed from the original power flow network corresponding to the power flow-carbon flow coupling mathematical model to obtain the remaining natural distribution network. Carbon emission flow distribution is calculated for the low-carbon benefit sharing virtual network and the remaining natural distribution network respectively. The node carbon flow rate of each network is solved. The carbon emission distribution of the entire network is reconstructed by linear superposition, and the carbon emission measurement results of the target power system considering location fairness are obtained.

2. The regional carbon emission measurement method considering location equity according to claim 1, characterized in that: The adjustable sharing ratio coefficient is the proportion of carbon emission responsibility for network losses borne by the load side. Its value is calculated and determined based on at least one of the technical indicators of the target power system, such as line load rate, source-load distribution ratio, and grid structure parameters, or is determined by the carbon emission responsibility management agency.

3. The regional carbon emission measurement method considering location equity according to claim 1, characterized in that: The planning and construction level of the clean energy units corresponds to the dispatch level of the power system dispatching system.

4. The regional carbon emission measurement method considering location equity according to claim 1, characterized in that: When tracing the carbon emissions corresponding to the active power loss of the network, the network loss power in the power flow tracking model is replaced with the solved network loss carbon flow rate, and then bidirectional tracking calculations are carried out for both upstream and downstream power flows.

5. The regional carbon emission measurement method considering location equity according to claim 1, characterized in that: It also includes green electricity trading adaptation steps: obtaining green electricity trading contract data of the target power system, splitting the actual power flow into trading power flow and non-trading natural power flow based on the power transmission distribution factor, and constructing a green electricity trading virtual network; based on the linear superposition theorem, separating the green electricity trading virtual network from the original power flow network, and synchronously updating the remaining natural distribution network.

6. The regional carbon emission measurement method considering location equity according to claim 5, characterized in that: In the calculation of carbon emission flows in the green electricity trading virtual network, the carbon emission factor of the trading volume corresponding to the medium- and long-term green electricity trading under the integrated certificate and electricity trading model is calculated as 0, while the trading volume corresponding to the spot green electricity trading is calculated using the average carbon emission factor of the clearing units.

7. The regional carbon emission measurement method considering location equity according to claim 5, characterized in that: Regarding the carbon emissions from branch network losses between the green electricity trading virtual network and the remaining natural distribution network, the allocation is based on power flow distribution: if the power flow of the branch in the remaining natural distribution network is 0 or negative, the green electricity trading virtual network does not bear the network loss of the branch; if the power flow is positive, the carbon emissions from the branch network losses are allocated according to the proportion of the power flow of the remaining natural distribution network to the total active power flow of the branch.

8. The regional carbon emission measurement method considering location equity according to claim 5, characterized in that: When splitting the green electricity trading virtual network and the low-carbon benefit sharing virtual network, the active power of the units in the remaining naturally distributed network is the total active power of the units minus the active power participating in green electricity trading and the shared active power. The active power of the loads in the remaining naturally distributed network is the total active power of the loads minus the active power participating in green electricity trading and the shared active power.

9. The regional carbon emission measurement method considering location equity according to claim 1, characterized in that: The reconfiguration of the carbon emission distribution across the entire network follows the principle of conservation of the total direct and indirect carbon emissions of the power system, and the total carbon emissions of the entire system do not change with the process of network splitting and superimposed reconfiguration.

10. A regional carbon emission metering system that considers locational equity, characterized in that, It includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the method steps of any one of claims 1 to 9.

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