Partitioned pressure coupling power carbon emission factor dynamic accounting system and method

Abstract

The present application relates to the field of power system carbon emission accounting, and discloses a kind of partition voltage coupling's power carbon emission factor dynamic accounting method.The present application is first divided into geographical accounting partition and voltage grade, sets time granularity and completes the collection and pretreatment of multi-source data;Then construct partition and voltage double-layer power balance equation to establish power coupling relationship, construct partition voltage coupling carbon flow balance model, adopt power transfer distribution factor method to apportion net loss carbon emission, integrated as linear equation group and solved through sparse matrix technology, obtain the dynamic carbon emission factor of each partition and each voltage grade;After non-negativity check and carbon balance check correction, output factor, support low-carbon optimal dispatching.The present application improves the spatial resolution and time dynamics of carbon emission factor, and the net loss apportionment conforms to the physical law of power grid, which can meet the application requirements of refined low-carbon dispatching.

Description

Technical Field

[0001] This invention relates to the field of carbon emission accounting technology for power systems, specifically to a dynamic accounting method for power carbon emission factors that uses a zone-based voltage coupling. Background Technology

[0002] In the process of low-carbon transformation of the power system, the power carbon emission factor is an important parameter for low-carbon dispatch and carbon accounting. Existing carbon emission factors mostly use annual average values ​​at the administrative region level, which is relatively coarse in spatial dimension and fails to distinguish the differences in energy structure and losses across different geographical regions and voltage levels. In terms of time dimension, they are mostly statically updated, failing to reflect the dynamic fluctuations in daily power carbon emissions. Furthermore, existing accounting methods do not establish carbon flow coupling relationships between regions or different voltage levels. The allocation of carbon responsibility for inter-regional transmission and inter-voltage transfer is not clear enough. Carbon emissions corresponding to grid losses are often treated with simple allocation or direct calculation, which deviates from the actual physical characteristics of the power grid operation. The granularity and accuracy of the accounting results are insufficient to meet the needs of refined low-carbon optimization dispatch. Summary of the Invention

[0003] Firstly, a dynamic accounting method for electricity carbon emission factors based on regional voltage coupling includes: Divide geographical accounting zones and voltage levels, set time granularity, collect data from the power generation side, the power grid side and external sources, and perform preprocessing such as missing data completion and outlier removal; By constructing the power balance equations of the partition and the voltage balance equations, the power coupling relationship between partitions and voltage levels is established. A partition-voltage coupled carbon flow balance model is constructed and a carbon emission factor is introduced to express the carbon flow transfer relationship. The power transfer distribution factor method is used to allocate the network loss carbon emission. The coupled carbon flow balance equations are integrated into a linear equation system for solution to obtain the dynamic carbon emission factor of each partition and voltage level. The solution results are checked for nonnegativity and carbon balance, and abnormal results are corrected. The dynamic carbon emission factor of the partition and pressure is output, and the dynamic accounting of the power carbon emission factor coupled by partition and pressure is performed.

[0004] Optionally, the process of dividing geographic accounting zones and voltage levels, and setting time granularity, includes: Based on the physical topology of the power grid, geographical accounting zones are divided in combination with administrative boundaries and power supply areas; The voltage levels are calculated according to the standard voltage sequence of the power grid, and the power supply access and load supply range of each voltage level are clearly defined. Set the hourly accounting time granularity to divide the accounting cycle into multiple independent accounting periods.

[0005] Optionally, the preprocessing of collecting data from the power generation side, the power grid side, and external sources, and performing missing data completion and outlier removal, includes: Data on power generation, grid operation, and external auxiliary data are collected on a zone-by-zone, voltage-level, and time-by-time basis. Missing data is filled using an interpolation method that incorporates power flow physical constraints; Abnormal data is removed based on the physical threshold of power grid operation, and abnormal values ​​are corrected using data from adjacent time periods.

[0006] Optionally, the step of constructing the partitioned power balance equation and the voltage-divided power balance equation to establish the power coupling relationship between partitions and voltage levels includes: For a single time period in a single zone, an overall power balance equation for the zone is constructed based on the law of energy conservation, constraining the balance relationship between the zone's total power generation, input power and total power sales, grid loss power, and output power. For a single time period at a single voltage level within a single zone, a voltage-dividing power balance equation is constructed by combining the power transfer from the upper and lower voltage levels to constrain the balance of power inflow and outflow at each voltage level. By combining the power balance equations for all zones and all voltage levels, a two-layer coupled power balance equation set is formed.

[0007] Optionally, the construction of a partitioned pressure-coupled carbon flow balance model and the introduction of a carbon emission factor to express the carbon flow transport relationship includes: Carbon emissions from local power sources, inter-regional inputs, and inter-voltage transfers are calculated separately to obtain the total carbon inflow for each accounting unit. Load consumption, network losses, inter-regional outputs, and downstream transfers are taken as carbon outflow items, and carbon flow balance equations for each accounting unit are constructed in conjunction with the carbon emission factors to be determined. The carbon flow balance equations of all accounting units are combined to form a set of carbon flow balance equations that are divided into regions and coupled with pressure.

[0008] Optionally, the method of using the power transfer distribution factor to allocate carbon emissions from network losses includes: Based on the power grid topology and branch impedance parameters, the contribution coefficients of each power source node and load node to the network loss of each branch are calculated. Based on the contribution coefficient of each node, the carbon emissions from network losses are allocated to the corresponding power generation nodes and load nodes. The corresponding terms of the carbon flow balance equations are corrected based on the allocation results; the power transfer distribution factor method is a calculation method that quantifies the contribution of each node to the branch power loss based on the DC power flow distribution of the power grid.

[0009] Optionally, the step of integrating the coupled carbon flow balance equations into a linear equation system for solution, to obtain the dynamic carbon emission factor for each voltage level in each zone, includes: All carbon flow balance equations are rearranged into a standard linear equation system, generating the corresponding coefficient matrix, factor vector to be solved, and constant term vector; the coefficient matrix is ​​compressed using sparse matrix storage technology. The improved Gaussian elimination method was used to solve the linear equation system, and the dynamic carbon emission factor of each zone and voltage level was obtained.

[0010] Optionally, the step of performing nonnegativity verification and carbon balance verification on the solution results and correcting outlier results includes: Verify that all dynamic carbon emission factors are non-negative, and for results with non-positive values, backtrack to investigate the deviation between the data and the equation, and correct and recalculate. The deviation between the total carbon inflow and the total carbon outflow of each accounting unit is verified, and the parameters are corrected and recalculated for results that exceed the deviation threshold; the deviation threshold for the carbon balance verification shall not exceed one percent.

[0011] Optionally, the output segmented voltage dynamic carbon emission factor performs segmented voltage coupled dynamic accounting of the electricity carbon emission factor, including: The dynamic carbon emission factor is updated periodically according to the set time granularity to form a time-series factor dataset. The regional dynamic carbon emission factor will be applied to the calculation of carbon emissions from electricity consumption, the adjustment of power grid operation mode, and the optimization of cross-regional power dispatch. Optimize power output and load allocation based on the spatiotemporal distribution characteristics of carbon emission factors to achieve low-carbon optimized scheduling.

[0012] Secondly, a partitioned voltage-coupled dynamic accounting system for electricity carbon emission factors is provided to implement the partitioned voltage-coupled dynamic accounting method for electricity carbon emission factors as described above. The system includes: The boundary and data processing module is used to divide geographic accounting zones and voltage levels, set time granularity, and complete the collection and preprocessing of multi-source data. The partitioned voltage coupling calculation module is used to construct a two-layer power balance equation and a coupled carbon flow balance model, perform network loss carbon emission allocation and linear equation system solution, and output dynamic carbon emission factor. The verification and scheduling application module is used to perform double verification and anomaly correction on the solution results, output the dynamic carbon emission factor of each region and ensure the execution of low-carbon optimized scheduling.

[0013] This scheme first clarifies the accounting boundaries of different zones and voltage levels and completes multi-source data preprocessing, providing a unified spatial, voltage, and temporal benchmark and a qualified data foundation for subsequent accounting. Based on this, a two-layer power balance equation is constructed to establish the power coupling relationship between zones and voltage levels. Then, a coupled carbon flow balance model is built by embedding carbon flow transfer laws. The model terms are corrected using a network loss allocation method based on physical characteristics. Finally, a linear equation system is integrated to obtain the dynamic carbon emission factor, which is then verified and output for low-carbon dispatching. Each step is sequentially connected, with data transferred layer by layer, forming a complete link from boundary definition and power coupling to carbon flow solution. This improves the spatial resolution and temporal dynamics of the carbon emission factor, making the allocation of network loss carbon responsibility more consistent with power grid operation patterns, and providing finer-grained data support for low-carbon optimized dispatching. Attached Figure Description

[0014] Figure 1 This is a flowchart of a dynamic calculation method for electricity carbon emission factors based on partitioned voltage coupling according to the present invention. Detailed Implementation

[0015] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0016] In this embodiment, the proposed method for dynamic calculation of power carbon emission factors using zoned voltage coupling can be applied to power systems of various scales, including provincial power grids, municipal power grids, and industrial park power grids. It supports dynamic carbon emission factor calculation, electricity carbon metering, and low-carbon power grid operation scheduling. This solution encompasses the entire process of carbon flow calculation and scheduling under zoned voltage coupling scenarios, forming a complete technical path from boundary definition, data processing, electricity coupling, carbon flow modeling, network loss allocation, equation solving to verification and application. It can cover power grid levels with different geographical regions and voltage levels, achieving refined dynamic calculation of carbon emission factors and providing data and technical conditions for low-carbon operation of the power system.

[0017] This invention provides a method for dynamic calculation of electricity carbon emission factors using a partitioned voltage coupling method, such as... Figure 1 As shown, it includes: Divide geographical accounting zones and voltage levels, set time granularity, collect data from the power generation side, the power grid side and external sources, and perform preprocessing such as missing data completion and outlier removal; By constructing the power balance equations of the partition and the voltage balance equations, the power coupling relationship between partitions and voltage levels is established. A partition-voltage coupled carbon flow balance model is constructed and a carbon emission factor is introduced to express the carbon flow transfer relationship. The power transfer distribution factor method is used to allocate the network loss carbon emission. The coupled carbon flow balance equations are integrated into a linear equation system for solution to obtain the dynamic carbon emission factor of each partition and voltage level. The solution results are checked for nonnegativity and carbon balance, and abnormal results are corrected. The dynamic carbon emission factor of the partition and pressure is output, and the dynamic accounting of the power carbon emission factor coupled by partition and pressure is performed.

[0018] Specifically, the overall implementation process of this solution comprises three main parts. First, it involves defining the accounting boundaries and collecting and preprocessing multi-source data, clarifying three accounting dimensions: geographical zones, voltage levels, and time granularity. This includes collecting, completing, and cleaning various types of data to provide a unified benchmark and qualified data for subsequent calculations. Second, it conducts zone- and voltage-coupled carbon flow accounting. This involves first constructing a two-layer power balance equation to establish the power coupling relationship between zones and voltage levels, then constructing a coupled carbon flow balance model to quantify carbon flow transfer patterns. The model is then corrected using a network loss allocation method, and finally integrated into a linear equation system to solve for the dynamic carbon emission factors of each zone and voltage level. Finally, it performs result verification and scheduling applications. The solution results undergo double verification and anomaly correction, outputting time-series dynamic carbon emission factors to directly ensure the execution of the zone- and voltage-coupled dynamic calculation of power carbon emission factors.

[0019] In this embodiment of the application, the division of the accounting boundary includes three dimensions: spatial partitioning, voltage level, and time scale. These three dimensions together constitute a three-dimensional accounting framework, which clarifies the scope and granularity of the accounting and ensures the uniformity of the accounting process and the comparability of the results.

[0020] Specifically, the geographical accounting zoning is based on the physical topology of the power grid, combined with administrative boundaries and power supply areas. The zoning process prioritizes the natural electrical boundaries of the power grid, using the power supply coverage of key substations as the basis for division, while also considering administrative boundaries and power supply business areas to ensure the electrical independence and management convenience of each zone. Each zone has independent power access, load absorption, and inter-regional interconnection channels. Power exchange between zones is achieved through interconnection lines, and clear metering nodes are set at the zone boundaries for statistical analysis of inter-regional input and output power. The resulting zones do not have overlapping power supply areas or power supply blind spots, and can completely cover the entire power supply area of ​​the target power grid.

[0021] It should be noted that the voltage level classification covers the entire voltage sequence from high-voltage transmission to low-voltage distribution, and is set according to the standard voltage level system of the power grid. Different voltage levels undertake different grid functions: high voltage levels undertake large-capacity, long-distance power transmission, while medium and low voltage levels undertake power distribution and end-user power supply. Electrical connections and voltage transformations between voltage levels are achieved through transformers, with power being transferred step-by-step from high voltage levels to low voltage levels, forming a hierarchical power supply structure. During the classification process, the power access rules, load supply range, and upstream / downstream transfer relationships for each voltage level are clearly defined to ensure that the voltage level classification conforms to the actual operating logic of the power grid.

[0022] For example, the time granularity is set to match the dynamic characteristics of power grid operation, using an hourly calculation granularity to evenly divide the complete calculation cycle into multiple independent calculation periods. Each period independently performs power balance calculations and carbon flow calculations, with the calculation results from each period not interfering with each other, reflecting carbon emission fluctuations caused by changes in power output and load levels at different times. For power grid scenarios with a high proportion of renewable energy and significant peak-valley load differences, the time granularity can be further reduced to improve the time resolution of the calculation and capture the dynamic changes in carbon emissions more precisely.

[0023] In this embodiment of the application, the collection of multi-source data covers three categories: power generation side, power grid side, and external auxiliary data. These three categories of data correspond to the carbon flow source, transmission carrier, and auxiliary correction aspects, respectively, and together constitute the basic dataset for accounting.

[0024] Specifically, data from the power generation side is collected zone-by-zone, voltage-by-voltage, and time-by-time, covering all types of grid-connected power sources. The collected data includes real-time output, grid-connected electricity, fossil fuel consumption, unit rated parameters, start-up and shutdown status, and renewable energy curtailment for each power source. Among these, fuel consumption data from fossil fuel sources is the direct basis for calculating carbon emissions from power generation, while output data from renewable energy sources is the foundation for calculating the proportion of zero-carbon electricity. The collection frequency and time granularity are kept consistent across different types of power sources to ensure that the data corresponds to the same calculation period.

[0025] It should be noted that the grid-side data is also collected zone by zone, voltage level by voltage level, and time period by time, covering various parameters of grid operation. The collected data includes power flow data for each level of line, transformer load and loss data, inter-regional input and output power, interconnected power at the same voltage level, inter-voltage power transfer between upper and lower voltage levels, terminal power sales, line loss at each level, and branch impedance parameters. This data reflects the transmission, distribution, and loss processes of electricity in the grid, and forms the basis for constructing the power balance equation and carbon flow model.

[0026] For example, external auxiliary data includes carbon emission benchmarks for various power sources, carbon emission data from regions where electricity is imported across regions, time-period meteorological data, power grid maintenance plans, and load forecast data. External auxiliary data is used to correct relevant parameters in the calculation process and improve the accuracy of the results. For instance, meteorological data can be used to help verify the rationality of renewable energy output, and carbon emission data from electricity imported across regions is used to calculate the carbon inflow of imported electricity.

[0027] Specifically, the data preprocessing stage standardizes the original data to address issues such as missing dimensions, anomalies, temporal misalignments, and inconsistent units, ensuring the quality of the input data. Preprocessing includes four stages: unit unification, missing data completion, anomaly removal, and balance verification. The processed data meets the physical constraints of power grid operation and can be directly used for subsequent model building and calculations.

[0028] It should be noted that the unit unification process converts all electricity and power data into a unified standard unit, and aligns the time dimension to the set calculation period. This ensures that the time nodes and units of all data are completely consistent, avoiding calculation errors caused by inconsistent units or time misalignments. For data from different collection frequencies, aggregation or interpolation is used to align them to the same time period, ensuring time sequence consistency.

[0029] For example, the missing data completion process employs an interpolation method that incorporates physical constraints of power grid flow. During completion, not only are data change trends from adjacent time periods considered, but also the operating characteristics of similar power sources in the same region and physical conditions such as power grid balance constraints are adjusted to avoid results that violate power grid operating principles due to pure data fitting. For short-term data gaps, linear interpolation is used for completion; for long-term data gaps, calculations are performed based on the operating characteristics of similar equipment and overall power balance conditions to ensure data integrity.

[0030] Specifically, the outlier removal process identifies abnormal data based on physical thresholds for power grid operation. These physical thresholds include the maximum power output, maximum transmission capacity of lines, and the reasonable fluctuation range of load. Data exceeding these thresholds is considered outlier and is removed. The removed outlier data is then corrected using valid values ​​from adjacent time periods to ensure the continuity of the data sequence. Outlier identification strictly follows the physical laws of power grid operation, effectively filtering out outlier data caused by equipment failures, communication interruptions, and other factors.

[0031] It should be noted that the final step in data preprocessing is power balance verification. This involves verifying the power balance for a single zone and voltage level for a given time period to ensure that the power data conforms to the law of energy conservation. If the power deviation exceeds the allowable range, the data acquisition and preprocessing stages are traced back to identify the source of the deviation and correct it until the power balance error is controlled within a reasonable range, ensuring the physical consistency of the input data.

[0032] In this embodiment, after data preprocessing, a two-layer electrical balance equation for partitioning and voltage division is first constructed to establish the electrical coupling relationship between partitions and voltage levels. Electrical balance is the foundation of carbon flow balance. The two-layer electrical balance equation constructed based on the law of energy conservation can accurately characterize the flow process of electricity in space and voltage levels, providing a physical framework for the subsequent construction of the carbon flow model.

[0033] Specifically, the regional power balance equation is constructed for a single time period within a single region, constraining the balance of all electricity inflows and outflows within the region based on the law of conservation of energy. The left side of the equation represents the total electricity inflow for the region, including electricity fed into the grid from local power sources and electricity input from other regions; the right side represents the total electricity outflow for the region, including electricity sold to end users, electricity lost in the grid, and electricity exported to other regions. The regional power balance equation can constrain the power supply and demand balance of a single region at a macro level and is the foundation for the overall carbon flow accounting of the region.

[0034] The regional power balance equation can be expressed as follows: the sum of the total grid-connected power in a region and the total inter-regional input power equals the sum of the total power sold in the region, the total grid loss in the region, and the total inter-regional output power. That is:

[0035] in, For the first partition Total internet usage during the period; For the first partition Total electricity input across regions during the time period; For the first partition Total electricity sales during the period; For the first partition Total network loss during the time period; For the first partition The total electricity output across time zones is calculated based on the law of conservation of energy. All incoming electricity within a zone must equal the sum of all outgoing and lost electricity. The balance equations of all zones together constitute a macroscopic-level electricity balance constraint, ensuring the closure of electricity data at the zone level.

[0036] For example, the voltage-divided power balance equation, based on the regional balance, is refined to a single voltage level within a single region, and incorporates the power transfer from upstream and downstream voltage levels to construct a more granular power balance constraint. The left side of the voltage-divided power balance equation represents the total power inflow for that voltage level, including the power supplied to the grid by the current power source, the power input from other regions, and the power transferred downwards from the upstream voltage level. The right side of the equation represents the total power outflow for that voltage level, including the power sold to end users at that level, the power lost in the grid, the power output from other regions, and the power transferred downwards to downstream voltage levels. The voltage-divided power balance equation can characterize the power transfer relationship between different voltage levels, achieving power coupling along the voltage dimension.

[0037] The voltage divider power balance equation can be expressed as follows: the sum of the power supplied to the grid by the local power source, the power input to other regions, and the power transferred from the upstream power source equals the sum of the power sold by the local power source, the power lost by the local power source, the power output to other regions, and the power transferred to the downstream power source. That is:

[0038] in, For the first partition voltage level Electricity consumption during internet usage time period; For the first partition voltage level Electricity input across regions during different time periods; For the higher voltage level to Voltage level transfer power; For the first partition voltage level Electricity sales volume during specific time periods; For the first partition voltage level Power loss during specific time periods; For the first partition voltage level Power output across time periods and regions; for The equation transfers power from one voltage level to the next. The principle behind this equation is that energy conservation is satisfied within a single voltage level. Simultaneously, by connecting the power transfer terms in series, the power flow between different voltage levels is linked, creating a closed-loop coupling system that accurately reflects the actual process of power transfer from high to low voltage.

[0039] Specifically, the energy balance equations for all zones are combined with the voltage-level energy balance equations for all voltage levels in all zones to form a two-layer coupled energy balance equation set. This equation set includes energy constraints for all zones and voltage levels, comprehensively depicting the entire flow of electricity across spatial zones and voltage levels. The completed energy balance equation set undergoes a comprehensive verification to ensure that all equations hold true simultaneously and that energy data satisfies conservation constraints at each level.

[0040] In this embodiment, a carbon emission accounting mechanism is embedded into the two-layer power balance framework to construct a partitioned voltage-coupled carbon flow balance model. A carbon emission factor is introduced to explicitly express the transmission relationship of carbon flow. The carbon flow balance model uses power balance as a carrier, mapping each power quantity to a corresponding carbon emission quantity, quantifying the generation, transmission, transfer, loss, and output process of carbon flow along with power flow, and realizing the corresponding mapping between power flow and carbon flow.

[0041] Specifically, the total carbon inflow for each accounting unit is first calculated. Carbon inflow includes three categories: local power generation carbon emissions, inter-regional input carbon emissions, and inter-voltage transfer carbon emissions. Local power generation carbon emissions come from generators connected to the same voltage level within the region. For fossil fuel generators, carbon emissions are calculated based on fuel consumption or power generation and corresponding emission coefficients. Clean energy generators have no direct carbon emissions during operation, and their corresponding carbon emissions are zero. Inter-regional input carbon emissions come from carbon emissions carried by electricity imported from other regions, calculated based on the input electricity volume and the carbon emission intensity of the source region. Inter-voltage transfer carbon emissions come from carbon emissions carried by electricity transferred from the higher voltage level, calculated based on the transferred electricity volume and the carbon emission intensity of the higher voltage level. The total carbon inflow for the accounting unit is obtained by adding these three categories of carbon inflows.

[0042] It should be noted that the outflow path of the electricity corresponding to the carbon outflow item includes four categories: carbon emissions corresponding to end-load consumption, carbon emissions corresponding to grid losses, carbon emissions carried by electricity exported across regions, and carbon emissions carried by electricity transferred to lower-level voltages. Each type of carbon outflow corresponds to the product of the electricity outflow item and the carbon emission factor to be determined at this level, representing that the amount of carbon emissions carried by this part of the electricity is consistent with the carbon emission intensity at this level.

[0043] For example, the carbon flow balance equation for a single accounting unit follows the principle of carbon flow conservation, where the total carbon inflow equals the total carbon outflow. The left side of the equation represents the sum of the three types of carbon inflows, and the right side represents the sum of the four types of carbon outflows. The only unknown in the equation is the dynamic carbon emission factor corresponding to that accounting unit. The carbon flow balance equations of all accounting units are combined to form a system of zone- and voltage-coupled carbon flow balance equations. The unknown in this system is the carbon emission factor for all zones and all voltage levels.

[0044] Differentiated accounting for carbon emission characteristics of different types of power sources is adopted, with thermal power being the main source of carbon emissions, while new energy units achieve zero carbon emissions: Carbon emissions from thermal power plants: partition voltage level Carbon emissions from thermal power plants during specific time periods: ;in This refers to the on-grid electricity volume of thermal power plants for the corresponding time period, zone, and voltage level. It adopts the latest industry standard carbon emission factor for thermal power plants, which can be finely adjusted in real time according to the coal consumption characteristics of the unit.

[0045] Zero-carbon power generation carbon emissions: Clean energy units such as hydropower, wind power, photovoltaic power, nuclear power, and biomass power have no direct carbon emissions during operation, therefore... Only the indirect carbon loss during the power transmission process is accounted for.

[0046] Inter-regional carbon flow: The carbon emissions carried by inter-regional electricity imports are strongly correlated with the carbon emission levels of the source region. partition voltage level Carbon emissions from cross-regional imports during specific time periods: ;in Source of electricity partition Real-time carbon emission factors for different time periods accurately reflect the differences in the carbon attributes of imported electricity.

[0047] Transvoltage carbon flow: The carbon properties of power transferred between voltage levels are inherited from the higher voltage level. Transvoltage transfer carbon emissions: ; In the formula for Real-time carbon emission factors corresponding to the higher-voltage level of the voltage level enable precise traceability of carbon flow as it moves through the power hierarchy.

[0048] The carbon flow balance equation is expressed as follows: the sum of local power generation carbon emissions, inter-regional input carbon emissions, and inter-voltage transfer carbon emissions equals the sum of electricity sales and grid losses multiplied by the local carbon emission factor, plus inter-regional output electricity multiplied by the local carbon emission factor, and plus electricity transferred to lower levels multiplied by the local carbon emission factor. That is:

[0049] in, Carbon emissions from power sources For cross-regional carbon emissions, This is to transfer carbon emissions across pressure. For the first partition voltage level Time-based carbon emission factor. The principle of this equation is that carbon flow is generated and transmitted along with electricity flow. All carbon emissions flowing into a certain accounting unit will enter different outflow paths according to the distribution of electricity flow. The sum of carbon emissions from all outflow paths is equal to the sum of carbon emissions flowing in. The current carbon emission factor represents the amount of carbon emissions corresponding to a unit of electricity within the accounting unit. All outflowing electricity carries carbon emissions according to this intensity.

[0050] In this embodiment, to reasonably allocate the carbon emission responsibility corresponding to network losses, the power transfer distribution factor method is used to distribute the carbon emissions of network losses to each power source and load according to their physical contribution. Network losses are power losses generated during power transmission, and their corresponding carbon emission responsibility is directly related to the power source and load that caused the loss. The allocation method based on physical contribution is more in line with the operation law of the power grid and can avoid the responsibility deviation caused by average allocation or unilateral bearing.

[0051] Specifically, the first step in network loss allocation is to calculate the contribution coefficient of each power source node and load node to the network loss of each branch. Based on the topology of the power grid and the branch impedance parameters, the contribution coefficient of each node to the power loss of each branch is obtained through DC power flow calculation. The magnitude of the contribution coefficient reflects the degree of influence of that node on the network loss of the corresponding branch. The contribution coefficient is entirely determined by the physical parameters and operating status of the power grid, and there is no subjective bias in its assignment.

[0052] It should be noted that after obtaining the contribution coefficient of each node, the total network loss carbon emissions are calculated. Based on the proportion of each node's contribution coefficient, the total network loss carbon emissions are allocated to each power generation node and load node. Nodes with higher contribution proportions receive more network loss carbon emissions and bear greater responsibility for network loss carbon emissions. After allocation, the network loss carbon emissions allocated to each node are used to adjust relevant terms in the carbon flow balance equations, ensuring that network loss carbon responsibility is assigned to specific nodes and improving the rationality of the carbon flow accounting results.

[0053] For example, the carbon emissions from grid losses after allocation are incorporated into the carbon liability accounting systems of the generation side and the load side, respectively. The generation side bears the carbon liability for grid losses caused by power output, while the load side bears the carbon liability for grid losses caused by electricity consumption. This allocation method clarifies the responsible parties for grid loss carbon emissions, making the calculation of carbon emission factors more consistent with the actual division of responsibilities, and the accounting results more credible.

[0054] The power transfer distribution factor method is a calculation method that quantifies the contribution of each node to branch power loss based on the DC power flow distribution of the power grid. This method derives the sensitivity coefficient of each node's power change to branch power loss by using the relationship between branch impedance and node injected power. This coefficient serves as the quantitative basis for the contribution and can reflect the actual impact of each node on network loss from a physical perspective. The allocation result has clear physical meaning.

[0055] In this embodiment, after constructing the carbon flow balance equations and correcting for network loss allocation, the equations are integrated into a standard linear equation system. The corresponding numerical solution techniques are then used to solve the system, yielding the dynamic carbon emission factors for each zone and voltage level. The standardized linear equation system facilitates the use of mature numerical algorithms, ensuring both efficiency and accuracy, and is suitable for the computational needs of large-scale power grids.

[0056] Specifically, all carbon flow balance equations are first rearranged into a standard linear equation system, where the coefficient matrix multiplied by the vector to be solved equals the constant term vector. The elements of the coefficient matrix correspond to the carbon flow coupling relationships between each accounting unit, including coupling coefficients resulting from inter-regional power supply and voltage transfer. The vector to be solved is composed of the carbon emission factors of all accounting units arranged sequentially. The constant term vector consists of the known carbon inflow of each accounting unit. The rearranged linear equation system has a unique solution and can be stably solved using numerical methods.

[0057] It should be noted that, due to the large number of computational units in the partitioned and compressed system, most elements in the coefficient matrix are zero, making it a typical sparse matrix. To reduce storage overhead and computational load, sparse matrix storage technology is used to compress the coefficient matrix, storing only the positions and values ​​of non-zero elements. This eliminates redundant calculations caused by a large number of zero elements, effectively improving the solution efficiency of large-scale equation systems.

[0058] For example, the solution process employs an improved Gaussian elimination method, optimizing the elimination order by optimizing the storage structure of the sparse matrix, reducing filler elements in the calculation process, and further improving the solution speed. Strict convergence precision is set in the solution process to ensure the accuracy of the calculation results. For single-period calculations, the solution process can be completed in a short time, fully meeting the timeliness requirements of hourly dynamic updates.

[0059] Specifically, after the solution is completed, the carbon emission factor values ​​of all accounting units are obtained and organized in order of zone and voltage level to form the zone-by-zone voltage dynamic carbon emission factor results for that period. Due to different power supply structures, different zones have significantly different carbon emission factors. Zones with a high proportion of high-carbon power sources have higher factor values, while zones with a high proportion of clean energy sources have lower factor values. Within the same zone, carbon emission factors also differ between different voltage levels. Generally, the factor is relatively higher at higher voltage levels, while the factor at lower voltage levels varies with the allocation of transfer losses, which is consistent with the carbon flow variation pattern of power transmission at each level.

[0060] In this embodiment, after obtaining the solution for the carbon emission factor, double verification and anomaly correction are required to ensure the reliability of the results from both numerical rationality and physical consistency dimensions. Double verification can effectively filter out abnormal results that may occur during the solution process, ensuring that the output carbon emission factor conforms to physical laws and actual conditions.

[0061] Specifically, the first check is a non-negativity check. The carbon emission factor is a physical quantity characterizing the carbon emission intensity per unit of electricity, and its value cannot be negative. Therefore, the check verifies whether the carbon emission factor values ​​of all accounting units are greater than or equal to zero. If an abnormal result of less than zero occurs, the system automatically backtracks to the preceding data preprocessing, equation construction, and solution processes to check for data errors, equation construction deviations, or abnormal solution iterations. After locating the problem, the system corrects and recalculates until all factors meet the non-negativity requirement.

[0062] It should be noted that the second verification is a carbon balance verification. For each accounting unit, the difference between the total carbon inflow and the total carbon outflow is calculated, and the proportion of this difference to the total carbon inflow is calculated to determine whether it is within the allowable deviation threshold. The deviation threshold is set to no more than one percent to ensure the accuracy of the total carbon flow balance. If the deviation exceeds the threshold, the equation construction, network loss allocation, and other processes are traced back to check for parameter errors and calculation deviations. After correction, the solution is recalculated until all accounting units meet the carbon balance accuracy requirements.

[0063] For example, the result after all double checks pass is considered a valid calculation result and is stored in the results database. If there are abnormal results, the system will automatically record the abnormality type and the troubleshooting process, forming an abnormality handling log, which facilitates subsequent operation and maintenance and algorithm optimization. Through a closed-loop verification and correction mechanism, the accuracy and reliability of the calculation results at each time period can be guaranteed.

[0064] In this embodiment, the verified regional voltage-level dynamic carbon emission factors are organized and output in time series to form a time-series carbon emission factor dataset covering the entire region and all voltage levels. This directly ensures the dynamic calculation and execution of regional voltage-level coupled power carbon emission factors. The dynamically updated factors can reflect changes in the power grid's operating status in real time, providing data support for refined low-carbon dispatching.

[0065] Specifically, the entire process of data acquisition and preprocessing, model building, and solution verification is repeatedly executed according to a set time granularity to achieve dynamic updates of the carbon emission factor. For each time period, the latest carbon emission factor is calculated based on current grid operation data. The factor value dynamically changes with random group output variations, inter-regional power trading adjustments, and load fluctuations, accurately reflecting the real-time characteristics of electricity carbon emissions. The time-series factor dataset can be used to trace carbon emission levels at different times and to predict carbon emission trends in future periods.

[0066] It should be noted that dynamic carbon emission factors can be applied to multiple dispatch-related scenarios. In the scenario of electricity consumption carbon emission accounting, the corresponding dynamic carbon emission factor can be matched according to the user's region and voltage level to calculate the user's actual carbon emissions from electricity consumption, achieving refined measurement of user-side carbon responsibility. In the scenario of power grid operation optimization, the operation mode of the power grid can be optimized based on the differences in carbon emission factors at different regions and voltage levels, guiding the transmission of electricity from low-carbon areas to high-carbon areas and reducing the overall carbon emission level of the entire network.

[0067] For example, in cross-regional power dispatch scenarios, the amount and direction of cross-regional power transactions can be optimized by combining the carbon emission factors of each region, prioritizing the dispatch of power from low-carbon regions to supply loads in high-carbon regions, thereby improving the cross-regional absorption of clean energy. In power supply dispatch scenarios, the start-up, shutdown, and output allocation of generating units can be optimized based on changes in carbon emission factors, prioritizing the use of low-carbon emission units and reducing the output proportion of high-emission units, thus reducing system carbon emissions from the power supply side. In load-side dispatch scenarios, real-time carbon emission factor signals can be released to users, guiding them to increase electricity consumption during low-carbon periods and decrease it during high-carbon periods, thereby reducing peak system carbon emissions through demand response.

[0068] Specifically, by using refined factors for zoned and voltage-level distribution, dispatchers can pinpoint specific zones and voltage levels, enabling them to formulate more targeted low-carbon dispatch strategies and avoid dispatch biases caused by global averaging. For example, for high-carbon-emission industrial zones, external low-carbon electricity can be introduced in a targeted manner, increasing the proportion of local renewable energy consumption; for the low-voltage distribution network level, the access and dispatch of distributed power sources can be optimized to reduce the carbon emission intensity of the distribution network level. Layered and zoned dispatch strategies can achieve system carbon reduction goals more efficiently.

[0069] In this embodiment of the application, a dynamic calculation system for electricity carbon emission factors based on partitioned voltage coupling is also provided to implement the above-mentioned scheduling method. The system includes three main modules: a boundary and data processing module, a partitioned voltage coupling calculation module, and a verification and scheduling application module. The modules interact with each other through a standardized data interface to jointly complete the entire process from data input to scheduling application.

[0070] Specifically, the boundary and data processing module is responsible for configuring the accounting boundaries and processing multi-source data. The module has built-in functions for partitioning, voltage level configuration, and time granularity setting, allowing for flexible configuration of accounting dimensions based on the actual situation of the target power grid. The module interfaces with various data sources, automatically collecting data from the generation side, the power grid side, and external auxiliary data. It performs preprocessing operations such as dimension unification, missing data completion, anomaly removal, and balance verification, outputting standardized datasets for subsequent modules to use. The module also has data storage and management functions, storing historical data and accounting results, and supporting data querying and export.

[0071] It should be noted that the zone-based voltage-coupled calculation module is the main computing unit of the system, incorporating a two-layer power balance model, a coupled carbon flow balance model, a network loss amortization algorithm, and a linear equation solver. The module receives the preprocessed dataset, automatically constructs the two-layer power balance equations and the coupled carbon flow balance equations, performs network loss carbon emission amortization and equation correction, calls the solver to solve the linear equations, and outputs the dynamic carbon emission factor for each zone and voltage level. The module supports large-scale calculation scenarios, possesses high computational performance, and can complete all calculations for a single time period within a set time window.

[0072] For example, the verification and scheduling application module is responsible for verifying and correcting results and supporting scheduling applications. The module has built-in dual verification rules, automatically performing non-negativity and carbon balance verification on the calculation results, and automatically triggering correction and recalculation processes for abnormal results. The module provides the function of publishing and querying carbon emission factors, supporting factor output from multiple channels. The module also has built-in low-carbon scheduling assistance functions, capable of generating scheduling optimization suggestions based on dynamic carbon emission factors to assist scheduling personnel in making low-carbon operation adjustments. The module supports integration with existing scheduling systems, marketing systems, and carbon management systems, achieving interconnectivity of data and functions.

[0073] In this embodiment, the proposed solution can be applied to the low-carbon optimization dispatching of a regional power grid in a prefecture-level city. This regional power grid includes various power source types, involves inter-regional power exchange and multi-voltage level power transfer, and exhibits significant diurnal fluctuations in load and renewable energy output, thus validating the practical effectiveness of the zoned voltage coupling calculation method.

[0074] Specifically, the application process first divides the region into three independent accounting zones based on the distribution of key substations, administrative jurisdiction, and power supply area, corresponding to industrial parks, central urban areas, and suburban areas, respectively. Power is exchanged between the three zones via high-voltage interconnection lines, exhibiting typical inter-regional carbon flow interaction characteristics. The voltage level is set to four levels, covering all levels from the main transmission layer to the terminal distribution network layer, clearly defining the transfer relationships at each level, with power being transferred down from the highest voltage level to the terminal load. The time granularity is hourly, selecting a typical 24-hour workday as the accounting period, with independent accounting for each time period, preserving the dynamic characteristics brought about by diurnal peak and valley fluctuations and new energy output fluctuations.

[0075] It should be noted that, regarding the basic parameter settings, fossil fuel units adopt a regionally unified carbon emission benchmark coefficient, while the carbon emissions of new energy units are treated as zero. For electricity imported across regions, the dynamic carbon emission factor of the source region is used. All basic parameters conform to the actual operating level of the local power grid and industry-standard practices, ensuring the authenticity and comparability of the accounting results.

[0076] For example, after boundary delineation, full basic data is collected from the power grid dispatching system, power generation remote control system, marketing power consumption system, and meteorological monitoring system, and standardized preprocessing is carried out. Data gaps in certain time periods and abnormal data caused by equipment maintenance are supplemented and corrected, and power balance calibration is completed to ensure that the power balance error of each zone in all time periods is within a reasonable range and meets the physical consistency requirements.

[0077] Specifically, a two-layer power balance equation set was then constructed. Each of the three zones corresponds to a set of overall balance equations, and each of the four voltage levels in each zone corresponds to a set of voltage balance equations, for a total of fifteen sets of power balance equations. The equation parameters were updated periodically over twenty-four time periods. Through the power balance equations, the power interaction between zones and the power transfer between upstream and downstream voltage levels were clarified, establishing a complete power coupling relationship.

[0078] It should be noted that a coupled carbon flow balance model is constructed based on power balance. Carbon emissions from local power sources, inter-regional inputs, and inter-voltage transfers are calculated for each unit as carbon inflow terms; load consumption, network losses, inter-regional outputs, and downstream transfers are considered as carbon outflow terms. The carbon flow balance equations for each unit are constructed by introducing the carbon emission factor to be determined. Simultaneously, the power transfer distribution factor method is used to calculate the contribution coefficients of each power source and load to network losses, allocating network loss carbon emissions to the corresponding nodes according to their contribution ratio, and correcting the corresponding terms in the carbon flow balance equations.

[0079] For example, all carbon flow balance equations are rearranged into a standard linear system of equations, generating corresponding sparse coefficient matrices, vectors of factors to be solved, and vectors of constant terms. An improved Gaussian elimination method combined with sparse matrix techniques is then used to solve the equations. The solution for a single time period can be completed quickly, meeting the timeliness requirements for dynamic updates. After the solution is completed, the results are double-checked. Factors for all time periods meet the non-negativity requirement, and carbon balance deviations are within acceptable limits, confirming the validity of the calculation results.

[0080] Specifically, the calculation results show significant differences in carbon emission factors across different zones. Industrial park zones have relatively higher carbon emission factors due to their high proportion of local high-carbon power sources; suburban areas have abundant clean energy resources and relatively lower carbon emission factors; and central urban areas, reliant on external power supplies, have factor levels between the two. Within the same zone, carbon emission factors also exhibit hierarchical differences at different voltage levels, consistent with the carbon flow variation pattern of power transmission at different levels. Factors also fluctuate significantly throughout the day and night, with generally lower factors during the midday peak of renewable energy generation and generally higher factors during the nighttime when renewable energy output decreases, demonstrating the advantages of dynamic accounting.

[0081] It should be noted that, compared with the traditional global static average factor, the dynamic accounting results based on regional voltage can reflect the differences in three dimensions: region, voltage, and time. This allows for a more accurate reflection of the actual carbon emission levels of electricity consumption at different locations and times. Based on this refined factor, low-carbon dispatching can be implemented to formulate more targeted carbon reduction measures and improve dispatching effectiveness. For example, efforts can be made to increase the import of low-carbon electricity into high-carbon zones, optimize the local consumption of distributed power sources at the low-voltage level, and guide loads from peak hours to low-carbon periods, thereby promoting system carbon emission reduction from multiple dimensions.

[0082] It should be noted that current technologies in the field of electricity carbon emission accounting mostly adopt a global average calculation method, focusing on the calculation of annual or monthly carbon emission factors at a single level, and rarely covering the refined division of both spatial zoning and voltage levels. Some technologies involve carbon flow calculation, but they mostly directly apply the power flow calculation framework without establishing a dual-layer coupled power and carbon flow balance system of zoning and voltage division, and the carbon flow transfer relationship across regions and voltage levels is not clear enough. For the treatment of grid loss carbon emissions, most technologies use simple reduction or average allocation methods, without combining the physical characteristics of the power grid to quantify the contribution of each entity, and the physical meaning of the allocation results is weak.

[0083] Specifically, the coupled construction of two-layer power balance and carbon flow balance requires unifying the spatial dimension of partitioned interaction and the voltage dimension of hierarchical transfer into the same set of equations, while matching the corresponding carbon flow transfer rules. Existing technologies mostly handle partitioned balance or voltage level balance separately, without deeply coupling the two to form a unified accounting system. Embedding the power transfer distribution factor's network loss allocation method into the partitioned voltage-coupled carbon flow model requires correspondingly modifying the allocation method of network loss terms within the framework of the two-layer balance equations, so that the responsibility for network loss is assigned to the relevant entities in different partitions and voltage levels, rather than simply being superimposed on the overall loss. This combination is not a simple patchwork of existing technologies, but requires the establishment of a unified accounting unit system, connecting the transfer logic of power, loss, and carbon flow in both dimensions to form a closed calculation chain.

[0084] For example, sparse matrix solving techniques are primarily used in large-scale power flow calculations. Applying them to solving partitioned voltage-coupled carbon flow equations requires adjusting the storage structure and solution order to account for the sparse characteristics of the carbon flow coupling matrix. This necessitates improving computational efficiency while maintaining accuracy, meeting the timeliness requirements of hourly dynamic updates. The dynamic time-period verification mechanism also requires sequential linkage across the entire process of data acquisition, model updating, equation solving, and result verification to ensure valid results are output for each time period.

[0085] In this embodiment, the solution organically integrates multiple stages, including zone-based voltage and load dual-layer boundary delineation, multi-source data standardization preprocessing, dual-layer power balance coupling, carbon flow balance model construction, physical network loss allocation, efficient sparse matrix solution, dual verification correction, and dynamic scheduling application, forming a complete technology chain from boundary definition to scheduling application. Each stage is interconnected and data is linked, with the output of one stage serving as the input of the next. Each stage is adapted to the zone-based voltage and load scenario, collectively achieving refined, dynamic, and physical carbon emission factor calculation, providing finer-grained data support for low-carbon optimized scheduling.

[0086] Furthermore, this solution boasts strong scenario adaptability, allowing for flexible adjustment of the calculation granularity based on the scale and structure of the target power grid. For large-scale power grids such as provincial-level grids, the number of zones and voltage level levels can be increased to refine the calculation units and ensure the calculation accuracy of each region and voltage level within the province. For small-scale power grids at the park level, zones and voltage levels can be appropriately merged to reduce the number of calculation units, improve computational efficiency, and retain the calculation logic of zone-based voltage levels. The time granularity of the calculation can also be flexibly adjusted according to dispatching needs. In addition to the hourly level, it can also be set to the fifteen-minute or half-hour level to adapt to different levels of granular dispatching requirements.

[0087] Specifically, in power grid scenarios with a high proportion of renewable energy, the dynamic accounting feature of this solution can better adapt to the randomness and volatility of renewable energy output. Renewable energy output changes rapidly with weather conditions, leading to significant fluctuations in the grid's carbon emission intensity. Static average factors cannot reflect this volatility, while time-period dynamic accounting can update the carbon emission factor in real time following changes in renewable energy output, accurately reflecting the carbon reduction effect brought about by renewable energy consumption. Simultaneously, it can be combined with renewable energy forecast data to calculate the carbon emission factor for future periods in advance, providing a basis for proactive low-carbon dispatching.

[0088] It should be noted that this solution supports dynamic adjustment of the accounting boundaries. When new power sources, lines, zones, or voltage levels are added to the power grid, corresponding accounting units and connection relationships can be added to the model, quickly adapting to changes in the power grid structure without reconstructing the overall accounting framework. Model parameters support periodic updates; for example, emission factors and equipment parameters can be adjusted based on the latest industry standards and actual equipment measurement data to ensure that the accounting results always reflect the actual situation of the power grid.

[0089] For example, this solution can also play a role in power grid planning scenarios. Planners can adjust parameters such as regional power supply structure and power grid topology to simulate and calculate the regional voltage carbon emission factors under different planning schemes, evaluate the low-carbon benefits of different planning schemes, and select the scheme with better carbon emission levels. For example, they can evaluate the improvement effect of new renewable energy bases on the carbon emission factors of each region, evaluate the enhancement effect of new transmission channels on inter-regional low-carbon power transmission, and evaluate the impact of distribution network upgrades on low-voltage level carbon emissions, thereby optimizing power grid planning schemes from a low-carbon perspective.

[0090] Specifically, in carbon trading and green electricity certification scenarios, dynamic carbon emission factors based on regional and voltage levels can provide more accurate measurement data. Participants in carbon trading can accurately calculate their carbon emission responsibilities based on the factors applicable to their respective regions and voltage levels, improving the fairness of carbon trading measurement. Green electricity certification can combine dynamic factors to calculate the emission reductions corresponding to green electricity, clarifying the actual carbon reduction effect of green electricity consumption and enhancing the transparency and acceptance of green electricity products.

[0091] It should be noted that the system has a robust access control and data security mechanism. Users with different roles have different data access permissions. Power generation companies can only view their own relevant accounting data, power grid companies can view the operational data of the entire network, and regulatory authorities can view all data within their authorized scope. This ensures both data sharing and data privacy. Data transmission and storage are encrypted to prevent data leakage and tampering, thus guaranteeing data security.

[0092] For example, the system supports integration with various existing power business systems, enabling automatic data acquisition and result push. It can interface with dispatch automation systems to automatically acquire real-time operational data; it can interface with marketing systems to automatically acquire user electricity consumption data and push corresponding carbon emission accounting results; and it can interface with carbon management systems to automatically output accounting data to support carbon management operations. The system integration uses standardized interface protocols, ensuring good compatibility and enabling rapid integration into the existing power information system.

[0093] Specifically, the accounting results are traceable, with complete source data, model parameters, calculation processes, and verification records for each time period. When there are doubts about the accounting results, the entire accounting process can be traced back to pinpoint the parameters and calculation procedures at each stage, verifying the accuracy of the results. Traceability meets the compliance requirements of carbon verification, auditing, and other scenarios, enhancing the credibility of the accounting results.

[0094] It should be noted that this scheme fully complies with relevant standards in the power industry and general specifications for carbon emission accounting during the design process. The accounting methods and parameter selections all meet industry-standard requirements, ensuring the standardization and comparability of the accounting results. For regions with local standards, local parameters can be adjusted accordingly to adapt to local accounting rules and improve the scheme's regional adaptability.

[0095] For example, in actual deployment, either centralized or distributed deployment can be adopted. For smaller regional power grids, centralized deployment can be used, with all modules deployed on a central server for unified management and maintenance. For larger, cross-regional power grids, distributed deployment can be used, with corresponding data acquisition and computing nodes deployed in each region. The central node performs aggregate calculations and unified scheduling, improving computing efficiency and system reliability. Both deployment methods can achieve complete functionality, and the choice can be made based on the actual power grid scale and management architecture.

[0096] Specifically, the system's operation and maintenance are intelligent, capable of real-time monitoring of the operational status of each module, automatically identifying anomalies and performing preliminary fault location, assisting maintenance personnel in quickly troubleshooting problems. The system has comprehensive logging capabilities, recording all data operations, calculation processes, and user access in detail, facilitating subsequent auditing and problem investigation. The system also features version management, with corresponding version records for model and algorithm updates, allowing for traceability of algorithm iterations and ensuring the consistency and comparability of accounting methods.

[0097] In this embodiment, the network loss allocation process can also select different allocation granularities according to actual needs. It can be allocated to aggregation nodes at the zone and voltage level, or further allocated to individual generating units and load nodes. The finer the allocation granularity, the clearer the division of carbon responsibility. Adjusting the allocation granularity does not change the overall accounting framework; only the calculation granularity of the contribution coefficient and the equation correction method need to be adjusted accordingly, demonstrating good scalability.

[0098] It should be noted that the carbon emission factor output supports multiple formats. It can output time-series factor data in numerical tabular form for batch calculations and system integration; or it can output a visualized spatiotemporal distribution map, intuitively showing the spatial and temporal distribution patterns of the carbon emission factor, facilitating dispatchers to quickly grasp the carbon flow distribution status of the entire network. The visualization can be combined with geographic information and power grid topology to more intuitively present the carbon emission differences between different regions and voltage levels.

[0099] For example, in demand response operations, differentiated incentive signals can be designed based on dynamic carbon emission factors. During periods of high carbon emission factors, the incentives for demand response are increased to guide users to reduce their electricity load; during periods of low carbon emission factors, users are guided to increase their electricity consumption to utilize surplus clean energy. By combining carbon signals with price signals, users can be more effectively guided to participate in low-carbon demand response, thereby improving the carbon reduction benefits of demand-side resources.

[0100] Specifically, in the carbon assessment scenario of fixed asset investment projects, dynamic carbon emission factors based on regional voltage levels can provide accounting parameters that are more closely aligned with the actual situation of the project. For projects connected to different regions and at different voltage levels, using the corresponding location's carbon emission factors to calculate electricity consumption carbon emissions can more accurately assess the actual carbon emission level of the project, avoid the assessment bias caused by using a global average factor, and improve the scientific rigor of carbon assessment.

[0101] It should be noted that this scheme can support multi-objective optimal dispatching of the power grid. Based on traditional economic and safety dispatching, a low-carbon dispatching objective is added. The carbon emission level of the dispatching scheme is quantified based on a dynamic carbon emission factor that is used for regional and voltage-based dispatching. Under the premise of meeting safety and economic constraints, the optimized dispatching scheme reduces system carbon emissions. Multi-objective dispatching can balance the relationship between safety, economy, and low carbon, achieving comprehensive optimal operation of the power grid.

[0102] For example, at the distribution network level, the operation strategies of distributed generation and energy storage can be optimized based on the carbon emission factor of voltage division. When the carbon emission factor at the distribution network level is high, the output of distributed generation and the discharge of energy storage can be increased, reducing the amount of electricity purchased from the upper-level grid and thus reducing the carbon emissions of the distribution network. When the carbon emission factor at the distribution network level is low, electrical energy can be stored or surplus electricity can be consumed, improving the local consumption level of clean energy. Through hierarchical scheduling optimization, the carbon reduction potential on the distribution network side can be tapped.

[0103] Specifically, at the transmission network level, inter-regional power transmission plans and main grid operation modes can be optimized based on the carbon emission factors of different regions. Priority should be given to transmitting electricity from low-carbon regions to high-carbon regions, increasing the proportion of low-carbon power transmission in inter-regional channels, and optimizing the overall carbon flow distribution of the network. Simultaneously, the topology operation mode of the main grid can be optimized to reduce network losses in high-carbon areas and improve the low-carbon efficiency of the transmission process.

[0104] Furthermore, this solution can be extended to the entire carbon footprint accounting chain. For electricity users, it can not only calculate the carbon emissions of end-use electricity, but also trace the carbon emission composition of electricity in each stage of generation, transmission, and distribution, clarifying the carbon responsibility of each stage and realizing carbon footprint tracking throughout the entire electricity consumption chain. The entire carbon footprint chain can help users gain a more comprehensive understanding of the sources of carbon emissions from electricity consumption and formulate more targeted emission reduction measures.

[0105] It should be noted that the calculation accuracy of this scheme is directly related to data quality. Therefore, multiple verification mechanisms will be implemented during the data acquisition phase to ensure the accuracy of the input data. Simultaneously, model parameters will be periodically calibrated using measured data, such as emission factor parameters, using actual carbon emission monitoring data to ensure that the deviation between the model calculation results and actual conditions remains within a reasonable range. Model calibration continuously improves the accuracy of the calculation results and adapts to changes in the characteristics of power grid operation.

[0106] For example, in a zone with multiple fossil fuel units, carbon emissions for different fuel types can be calculated separately, and then aggregated to obtain the total carbon emissions from power generation. The emission coefficients for different fuels use the standard values ​​corresponding to those fuels, which can more accurately reflect the carbon emission characteristics of different fuels. For units equipped with carbon capture devices, the emission coefficients can be adjusted accordingly to reflect the actual carbon emission levels.

[0107] Specifically, the carbon emission factor for cross-regional electricity imports can be either a real-time factor from the sending region or a factor agreed upon in the trading contract, adapting to different trading scenarios. For medium- and long-term electricity trading, agreed-upon annual or monthly factors can be used; for spot electricity trading, real-time dynamic factors can be used to ensure that cross-regional carbon flow accounting matches the trading mechanism.

[0108] It should be noted that the carbon flow transfer between upper and lower voltage levels follows the rule of unidirectional transfer from high voltage to low voltage, which conforms to the general operation of the power grid. For scenarios where there is reverse power flow from low voltage to high voltage, such as distributed generation power flowing back to the upper-level grid, the direction of the transfer item can be adjusted accordingly to reverse the carbon flow from the low-voltage side to the high-voltage side, adapting to bidirectional power flow scenarios. The model has the capability to handle bidirectional power flow and can adapt to distribution network scenarios with high distributed generation access.

[0109] For example, in special operating scenarios such as holidays and extreme weather, the dynamic accounting capability of this solution can better adapt to changes in the power grid's operating status. Holiday load levels differ significantly from weekday loads, and under extreme weather conditions, both renewable energy output and load levels fluctuate significantly. Static factors cannot reflect carbon emission changes in these special scenarios, while time-period dynamic accounting can track changes in operating status in real time, outputting accurate factors for the corresponding scenarios, and ensuring scheduling and accounting needs under special circumstances.

[0110] Specifically, the system has historical data statistical analysis capabilities, enabling it to statistically analyze carbon emission factors over historical periods and generate daily, monthly, quarterly, and annual statistical reports. It analyzes the changing trends and influencing factors of carbon emissions, providing data support for emission reduction planning and policy formulation. Statistical analysis can be conducted from multiple dimensions, including zoning, voltage levels, and time periods, comprehensively presenting the spatiotemporal distribution characteristics of power grid carbon emissions.

[0111] It should be noted that this solution fully considers computational efficiency during implementation, employing optimization techniques such as sparse matrices to ensure that the timeliness requirements for dynamic updates can be met even in large-scale power grid scenarios. As the number of computational units increases, the computational load grows approximately linearly, without experiencing explosive growth, demonstrating good scalability.

[0112] The following is an example illustrating a specific embodiment.

[0113] This embodiment selects a regional power grid in a prefecture-level city in central my country as the sole accounting object. This power grid includes multiple types of power sources such as thermal power, photovoltaic power, wind power, and hydropower. It exhibits significant cross-regional power interaction, voltage transfer between upstream and downstream levels, and fluctuations in day and night loads and new energy sources. It is very suitable for verifying the technical advantages of this invention, namely "regional voltage division, dynamic accounting, carbon flow coupling, and network loss sharing".

[0114] 1.1 Space Partitioning Settings (3 Independently Calculated Partitions) Based on the location of the 220kV hub substations in the city's power grid, administrative jurisdiction, power supply business scope, and electrical topology decoupling characteristics, the area is divided into 3 independent accounting zones with no overlapping or omissions in the zone boundaries and an electrical closed loop: (1) Zone A: High-tech Industrial Park Zone, with 220kV High-tech Substation and 500kV Municipal Main Substation as the core, the load is mainly high-energy-consuming industry and high-end manufacturing load, and the zone is equipped with self-owned thermal power and distributed photovoltaic power. (2) Zone B: Central urban area zone, with the 220kV urban substation and the 220kV eastern suburbs as the core. The load is mainly commercial, residential and public service loads. There are no large thermal power plants. The power source is mainly distributed photovoltaic and external power reception. (3) Zone C: Suburban ecological zone, with 220kV county transformer as the core, with dispersed loads and abundant centralized wind and hydropower resources in the zone, serving as a local clean energy output zone.

[0115] The three regions are interconnected via 500kV / 220kV inter-regional interconnection lines, providing a typical inter-regional carbon flow interaction scenario.

[0116] 1.2 Voltage Level Settings (4 Standard Voltage Levels) This embodiment adopts a commonly used four-level voltage system in engineering, covering the entire transmission and distribution hierarchy: 500kV (main transmission layer), 220kV (regional power supply layer), 110kV (intermediate distribution layer), and 10kV (terminal distribution network layer). The hierarchical transfer relationships are clearly defined: 500kV to 220kV, 220kV to 110kV, and 110kV to 10kV. Inter-regional interconnection and mutual power supply can be achieved within the same voltage level.

[0117] 1.3 Time Scale Setting A typical working day cycle was selected, and an hourly time granularity was adopted. A total of 24 continuous accounting periods (t=1~24) were set up, each corresponding to the power grid operation status from 00:00 to 23:00 on the same day, and the carbon emission factor was independently and dynamically calculated for each period.

[0118] 1.4 Basic Fixed Parameter Settings The benchmark coefficient for carbon emissions from thermal power plants is uniformly adopted as the average measured value of the regional power grid. =0.982tCO2 / MWh; the carbon emissions of all new energy units (wind power, photovoltaic, hydropower) are 0; the initial factor of the source of cross-regional power input adopts the dynamic factor disclosed by the provincial power grid.

[0119] 2. Implementation Plan Boundary Definition and Ledger Review Complete the three-dimensional boundary solidification strictly according to step S1 to form a traceable accounting ledger: 1. Spatial Boundaries: Clearly define the power supply range of each of the three zones, the 12 inter-zone interconnection lines, the rated capacity of the lines, the permissible direction of power flow, and the boundary node numbers; 2. Voltage Boundaries: Clarify the power supply, load coverage, and transformer upstream and downstream correspondence for each voltage level. Statistics show that: 500kV is a pure transmission level with no terminal loads, and 10kV is a pure distribution level with no large power sources. 3. Time boundary: 24 time periods are calculated independently, without daily average, and the peak and valley of day and night and the fluctuation characteristics of new energy output are preserved.

[0120] 3. Multi-source data acquisition and preprocessing This embodiment collects all data from the power grid EMS energy management system, the generator-side remote control system, the marketing electricity consumption system, and the meteorological monitoring system, and completes standardized preprocessing.

[0121] 3.1 Core Basic Data List (1) Generation side data: Zone A includes two 300MW coal-fired power units and 120MW distributed photovoltaic power; Zone B has no coal-fired power, but includes 80MW of urban distributed photovoltaic power; Zone C includes 150MW of centralized wind power, 60MW of run-of-river hydropower, and 30MW of village-level photovoltaic power. The on-grid power, real-time output, and start-stop status of each unit are collected hourly.

[0122] (2) Grid side data: Statistics on cross-regional input / output power, cross-voltage transfer power, terminal power sales, line loss, transformer loss and total grid line loss for the three zones and four voltage levels in each time period.

[0123] (3) External data: hourly irradiance, wind speed, ambient temperature, and carbon emission factor of electricity input from the provincial external grid.

[0124] 3.2 Data Preprocessing Implementation For scenarios where photovoltaic power output is zero in the early morning, wind power fluctuates slightly at night, and telemetry data is missing in some periods, the LSTM completion algorithm with physical constraints on power flow is used to repair the data; data of equipment failure and maintenance abnormalities are removed; power balance calibration is completed, and the power balance error of a single zone is controlled within 0.5% in all periods, meeting the physical consistency requirements.

[0125] 4. Example Construction of Two-Layer Electricity Balance Equation In this embodiment, a total of 15 sets of power balance equations are constructed, consisting of 3 overall balance equations for the three zones and 3 voltage level voltage division equations for the three zones. The equation parameters are updated periodically over 24 time periods.

[0126] 4.1 Example of parameters for a typical time period (t=12, midday peak period for new energy generation) Taking the typical period of high photovoltaic output at noon (12:00 noon) as an example, the power balance parameters of the core area are listed (unit: MWh): Zone A power parameters: Local thermal power grid connection power. =428; Cross-regional input =126; Terminal electricity sales =412; Network loss =23; Cross-regional output =119; Substituting into the partition balance equation satisfies: 428+126=412+23+119, the energy balance is established.

[0127] Zone B power parameters: Local solar grid connection =89; Cross-regional input =215; Terminal electricity sales =276; Network loss =14; Cross-regional output =14; the equilibrium holds.

[0128] Partition C power parameters: local wind, solar, water, total internet usage =263; Cross-regional input =38; Terminal electricity sales =128; Network loss =16; Cross-regional output =157; the equilibrium holds.

[0129] 4.2 Example of voltage divider charge balance Taking the 220kV voltage level of Zone A and the t=12 time period as an example: the upstream 500kV transfer power is 102MWh, the local 220kV thermal power grid connection is 216MWh, and the inter-regional input is 68MWh; the downstream 110kV transfer power is 186MWh, the local 220kV power sales are 152MWh, the grid loss is 9MWh, and the inter-regional output is 39MWh. Substituting into the voltage division balance equation, a complete match is achieved, realizing a hierarchical power closed loop.

[0130] 5. Example calculation of the partitioned pressure-coupled carbon flow equilibrium model Based on the above electricity data, carbon emissions and carbon flow transfer calculations are carried out on a unit-by-unit and level-by-level basis.

[0131] 5.1 Calculation of carbon emissions from local power sources Only zone A has thermal power output. During the t=12 time period, the on-grid electricity generated by thermal power in zone A is 428 MWh. The carbon emissions from thermal power are: =428×0.982=420.296tCO2; Zones B and C have no thermal power, so local carbon emissions are 0; all new energy units in the three zones have 0 carbon emissions.

[0132] 5.2 Example Calculation of Carbon Flow Across Zones and Pressure Zones During time period t=12, zone B receives 126 MWh of electricity from the external grid, with an average external grid factor of 0.865 tCO2 / MWh. The carbon emissions from this inter-regional input are... =126×0.865=108.99tCO2; The A500kV power transfer to the 220kV power supply in zone A is 102MWh, with a real-time CO2 factor of 0.912tCO2 / MWh at 500kV. The carbon emissions from the cross-voltage power transfer are [not specified]. =102×0.912=93.024tCO2.

[0133] 5.3 Example of a single-unit carbon flow equilibrium equation Taking zone A-220kV-t12 as an example, by substituting all carbon inflow and outflow parameters, a complete and solvable carbon flow balance equation is constructed. The left side of the equation represents local thermal power carbon emissions + inter-regional input carbon + upstream carbon transfer, while the right side represents load carbon, grid loss carbon, output carbon, and downstream carbon transfer. The only unknown is the carbon emission factor to be determined for this unit. .

[0134] 6. Detailed Implementation Process of Fair Sharing of Carbon Emissions from PTDF Network Losses This embodiment abandons the traditional average allocation method and uses the PTDF power transfer distribution factor to carry out refined physical allocation. The steps are complete and replicable. Step 1: Import the local power grid topology, branch impedance, and node parameters to construct a DC power flow model and calculate the PTDF contribution matrix of each power source node and load node to each loss branch. Step 2: Statistics show that the total grid loss during the t=12 period is 53 MWh, and the total grid loss carbon emissions are 41.26 tCO2. Step 3: Calculations based on contribution coefficients show that thermal power contributes 68.2% to grid losses, industrial and commercial heavy loads contribute 21.5%, and residential and renewable energy sources contribute 10.3%. Step 4: Accurately allocate the carbon emissions from network losses to the corresponding nodes according to their contribution ratio, revise the original carbon flow balance equation, eliminate the accounting deviation caused by average allocation, and realize "whoever causes the loss, bears the carbon responsibility".

[0135] 7. Detailed implementation of matrix construction and solution of the system of equations For the 3-zone × 4 voltage levels in this embodiment, a total of 12 calculation units are generated for each time period, and a 12-dimensional linear equation system is integrated into a standard sparse matrix AX=B.

[0136] The coefficient matrix A has a dimension of 12×12 and is a sparse coupling matrix. Non-zero elements represent the carbon flow coupling relationship between partitioned mutual supply and voltage transfer. Vector X is the carbon emission factor to be determined for 12 units. Vector B is the total fixed carbon inflow for each unit.

[0137] Employing an improved Gaussian elimination and sparse matrix compression solution technique, the solution time for a single time period is less than 0.3 seconds, fully meeting the requirements for hourly dynamic updates. It outputs dynamic factor results across all dimensions for 24 time periods.

[0138] 8. Result verification, correction, and complete output of results 8.1 Double check result 1. Non-negativity check: In this embodiment, all 288 carbon emission factor values ​​in 12 groups × 24 time periods are greater than 0, with no abnormal negative values ​​or zero values; 2. Carbon balance verification: The maximum error between total carbon inflow and total carbon outflow over the entire period is 0.72%, which is strictly controlled within the ±1% patented accuracy index, ensuring that the calculation results are true and valid.

[0139] 8.2 Core Results Output for Typical Time Periods (Quantitative Comparison) 1. Peak period (t=12, high energy consumption): Zone A (industrial zone): 500kV factor 0.912tCO2 / MWh, 220kV factor 0.876tCO2 / MWh, 110kV factor 0.821tCO2 / MWh, 10kV factor 0.793tCO2 / MWh; 2. Zone B (central urban area) has no thermal power and relies on external power, with a factor between 0.752 and 0.815 tCO2 / MWh; 3. Zone C (Clean Energy Counties) has sufficient wind and hydropower output, with the lowest overall factor, ranging from 0.216 to 0.358 tCO2 / MWh; 4. Nighttime period (t=2, new energy returns to zero): The factors in all three zones rise overall, with the C factor in zone C rising to 0.621~0.689tCO2 / MWh, reflecting dynamic fluctuation characteristics.

[0140] To demonstrate the superiority of this invention, the calculation results of this method are compared with those of the traditional provincial static average factor method: 1. Traditional methods use a uniform static factor of 0.785tCO2 / MWh across the city, which cannot distinguish between industrial zones, urban areas, and clean energy districts and counties, nor can they distinguish between high and low voltage levels. 2. This invention can accurately depict the regional differences between high-carbon industrial zones, medium-carbon urban areas, and low-carbon suburban counties, as well as the hierarchical differences between high-voltage power transmission and low-voltage power distribution, while also realizing dynamic changes between day and night. 3. After combining PTDF network loss allocation, the user carbon responsibility accounting error has been reduced from more than 12% to less than 1%, and the accounting accuracy has been greatly improved.

[0141] This invention also provides a partitioned voltage-coupled dynamic calculation system for electricity carbon emission factors, used to implement the partitioned voltage-coupled dynamic calculation method for electricity carbon emission factors as described above. The system includes: The boundary and data processing module is used to divide geographic accounting zones and voltage levels, set time granularity, and complete the collection and preprocessing of multi-source data. The partitioned voltage coupling calculation module is used to construct a two-layer power balance equation and a coupled carbon flow balance model, perform network loss carbon emission allocation and linear equation system solution, and output dynamic carbon emission factor. The verification and scheduling application module is used to perform double verification and anomaly correction on the solution results, output the dynamic carbon emission factor of each region and ensure the execution of low-carbon optimized scheduling.

[0142] Those skilled in the art will understand that the embodiments of this application are not limited to the above-described examples. Various modifications and variations can be made to the above technical details without departing from the spirit and essence of this application, and all such modifications and variations fall within the protection scope of this application. Further details are omitted here.

Claims

1. A method for dynamic calculation of electricity carbon emission factors using a partitioned voltage coupling system, characterized in that, include: Divide geographical accounting zones and voltage levels, set time granularity, collect data from the power generation side, the power grid side and external sources, and perform preprocessing such as missing data completion and outlier removal; By constructing the power balance equations of the partition and the voltage balance equations, the power coupling relationship between partitions and voltage levels is established. A partition-voltage coupled carbon flow balance model is constructed and a carbon emission factor is introduced to express the carbon flow transfer relationship. The power transfer distribution factor method is used to allocate the network loss carbon emission. The coupled carbon flow balance equations are integrated into a linear equation system for solution to obtain the dynamic carbon emission factor of each partition and voltage level. The solution results are checked for nonnegativity and carbon balance, and abnormal results are corrected. The dynamic carbon emission factor of the partition and pressure is output, and the dynamic accounting of the power carbon emission factor coupled by partition and pressure is performed.

2. The method for dynamic calculation of electricity carbon emission factors by voltage coupling in a segmented manner according to claim 1, characterized in that, The process of dividing geographic accounting zones and voltage levels, and setting time granularity, includes: Based on the physical topology of the power grid, geographical accounting zones are divided in combination with administrative boundaries and power supply areas; The voltage levels are calculated according to the standard voltage sequence of the power grid, and the power supply access and load supply range of each voltage level are clearly defined. Set the hourly accounting time granularity to divide the accounting cycle into multiple independent accounting periods.

3. The method for dynamic calculation of electricity carbon emission factors by segmented voltage coupling according to claim 2, characterized in that, The preprocessing of collecting data from the power generation side, the power grid side, and external sources, and performing missing data completion and outlier removal, includes: Data on power generation, grid operation, and external auxiliary data are collected on a zone-by-zone, voltage-level, and time-by-time basis. Missing data is filled using an interpolation method that incorporates power flow physical constraints; Abnormal data is removed based on the physical threshold of power grid operation, and abnormal values ​​are corrected using data from adjacent time periods.

4. The method for dynamic calculation of electricity carbon emission factors by segmented voltage coupling according to claim 1, characterized in that, The construction of the zoned energy balance equation and the voltage-divided energy balance equation establishes the energy coupling relationship between zones and voltage levels, including: For a single time period in a single zone, an overall power balance equation for the zone is constructed based on the law of energy conservation, constraining the balance relationship between the zone's total power generation, input power and total power sales, grid loss power, and output power. For a single time period at a single voltage level within a single zone, a voltage-dividing power balance equation is constructed by combining the power transfer from the upper and lower voltage levels to constrain the balance of power inflow and outflow at each voltage level. By combining the power balance equations for all zones and all voltage levels, a two-layer coupled power balance equation set is formed.

5. The method for dynamic calculation of electricity carbon emission factors by voltage coupling in a segmented manner according to claim 4, characterized in that, The construction of a partitioned pressure-coupled carbon flow balance model and the introduction of a carbon emission factor to express the carbon flow transport relationship includes: The carbon emissions from local power generation, carbon emissions from cross-regional power input, and carbon emissions from cross-voltage power transfer are calculated separately to obtain the total carbon inflow for each accounting unit. By taking load consumption, network loss, inter-regional output, and downstream power transfer as carbon outflow items, and combining them with the carbon emission factors to be determined, carbon flow balance equations are constructed for each accounting unit. The carbon flow balance equations of all accounting units are combined to form a set of carbon flow balance equations that are divided into regions and coupled with pressure.

6. The method for dynamic calculation of electricity carbon emission factors by voltage coupling in a segmented manner according to claim 5, characterized in that, The method of allocating carbon emissions from grid losses using the power transfer distribution factor method includes: Based on the power grid topology and branch impedance parameters, the contribution coefficients of each power source node and load node to the network loss of each branch are calculated. Based on the contribution coefficient of each node, the carbon emissions from network losses are allocated to the corresponding power generation nodes and load nodes. Correct the corresponding terms of the carbon flow balance equation set based on the allocation results; The power transfer distribution factor method is a calculation method that quantifies the contribution of each node to the power loss of the branch based on the DC power flow distribution of the power grid.

7. The method for dynamic calculation of electricity carbon emission factors by voltage coupling in a segmented manner according to claim 6, characterized in that, The process of integrating the coupled carbon flow balance equations into a linear equation system for solution yields the dynamic carbon emission factors for each zone and voltage level, including: All carbon flow balance equations are rearranged into a standard linear equation system, generating the corresponding coefficient matrix, factor vector to be solved, and constant term vector; the coefficient matrix is ​​compressed using sparse matrix storage technology. The linear equations were solved using an improved Gaussian elimination method to obtain the dynamic carbon emission factors for each zone and voltage level.

8. The method for dynamic calculation of electricity carbon emission factors by voltage coupling in a segmented manner according to claim 1, characterized in that, The process of performing nonnegativity verification and carbon balance verification on the solution results and correcting abnormal results includes: Verify that all dynamic carbon emission factors are non-negative; for results with non-positive values, backtrack to investigate the deviation between the data and the equation, and correct and recalculate. The deviation between the total carbon inflow and the total carbon outflow of each accounting unit is verified, and the parameters are corrected and recalculated for results that exceed the deviation threshold; the deviation threshold for the carbon balance verification shall not exceed one percent.

9. The method for dynamic calculation of electricity carbon emission factors by voltage coupling in a segmented manner according to claim 1, characterized in that, The output segmented voltage dynamic carbon emission factor performs segmented voltage coupled dynamic accounting of the electricity carbon emission factor, including: The dynamic carbon emission factor is updated periodically according to the set time granularity to form a time-series factor dataset. The regional dynamic carbon emission factor will be applied to the calculation of carbon emissions from electricity consumption, the adjustment of power grid operation mode, and the optimization of cross-regional power dispatch. Optimize power output and load allocation based on the spatiotemporal distribution characteristics of carbon emission factors to achieve low-carbon optimized scheduling.

10. A dynamic accounting system for electricity carbon emission factors based on partitioned voltage coupling, characterized in that, The system is used to implement the power carbon emission factor dynamic calculation method with partitioned voltage coupling as described in any one of claims 1 to 9, the system comprising: The boundary and data processing module is used to divide geographic accounting zones and voltage levels, set time granularity, and complete the collection and preprocessing of multi-source data. The partitioned voltage coupling calculation module is used to construct a two-layer power balance equation and a coupled carbon flow balance model, perform network loss carbon emission allocation and linear equation system solution, and output dynamic carbon emission factor. The verification and scheduling application module is used to perform double verification and anomaly correction on the solution results, output the dynamic carbon emission factor of each region and ensure the execution of low-carbon optimized scheduling.

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