Multi-region multi-voltage cascade power carbon emission factor coordination accounting system and method

Abstract

The present application relates to the field of power system carbon emission factor collaborative accounting, and discloses a multi-region and multi-voltage cascaded power carbon emission factor collaborative accounting system and method.The system comprises a multi-source heterogeneous data acquisition layer, a regional voltage level cascaded topology modeling module, a dynamic carbon flow tracking and factor solving engine, and a collaborative accounting and application service layer.Through the acquisition and preprocessing of power generation side, network topology and exchange power data, the present application constructs a cascaded carbon flow network model with three-dimensional correlation of topology-power-carbon flow, completes carbon flow calculation combined with cascaded loss distribution rules, iteratively solves the instantaneous carbon emission factor of each node, and realizes factor publishing, electricity accounting and full-process evidence preservation.The present application can realize carbon flow tracking and dynamic accounting of multi-region and multi-voltage levels, ensure reasonable loss distribution, make the accounting process traceable, and provide data support for low-carbon optimal dispatching.

Description

Technical Field

[0001] This invention relates to the field of collaborative accounting technology for carbon emission factors in power systems, specifically to a collaborative accounting system and method for carbon emission factors in power systems with multi-regional and multi-voltage cascade. Background Technology

[0002] In the process of low-carbon transformation of the power system, carbon emission accounting is a crucial foundation for low-carbon dispatch and carbon management. Existing power carbon emission accounting technologies are mostly focused on single regions or single voltage levels, failing to consider carbon flow transmission and loss distribution during multi-regional power exchange and multi-voltage cascade transmission, leading to discrepancies between the calculated results and actual carbon flow distribution. Furthermore, the lack of a unified synchronous preprocessing mechanism for multi-source heterogeneous data means that differences in data format and time dimension affect the accuracy of carbon flow calculations. Carbon emissions corresponding to transmission losses are often simplified by averaging or ignoring them, which does not reflect the actual laws governing carbon flow transmission. In addition, existing accounting systems mostly employ static or quasi-static calculation methods, failing to update in real time with the grid's operating status, and the accounting process lacks effective traceability and evidence preservation mechanisms, making it difficult to meet the practical application needs of carbon emission verification, carbon trading, and low-carbon optimized dispatch. Summary of the Invention

[0003] The purpose of this invention is to provide a collaborative accounting method for electricity carbon emission factors in a multi-regional, multi-voltage cascaded manner, comprising: Simultaneously collect power generation data, network topology data, and switching power data. Perform preprocessing on the collected data, including time alignment, outlier cleaning, and format standardization. Output the preprocessed data through an encrypted transmission protocol. Define carbon flow accounting nodes, and use graph theory algorithms to construct the electrical topology of node branches in multiple regions and at multiple voltage levels, forming a cascaded carbon flow network model with three-dimensional correlation of topological power carbon flow. Based on the principle of proportional sharing and the cascade loss allocation operator, perform node carbon potential initialization, cascade loss carbon emission allocation, multi-regional collaborative power flow carbon flow calculation, and iterative solution of node carbon emission factors to obtain the instantaneous carbon emission factors of each carbon flow accounting node. Release carbon emission factors, respond to user requests to complete electricity carbon emission accounting, trace and record the entire accounting process, and perform collaborative accounting of electricity carbon emission factors across multiple regions and voltage levels.

[0004] Optionally, the synchronous acquisition of power generation side data, network topology data, and switching power data includes: Collect generation-side data covering various types of generator sets, including real-time active power, nameplate parameters, generation type, real-time fuel consumption data, and carbon emission intensity of the generator sets; Collect network topology data covering all voltage levels, including node connection relationships, line parameters, transformer parameters, and bus parameters; Collect the exchange power data corresponding to the inter-regional tie lines, including bidirectional active power values, power trading contract identifiers, tie line loss data, tie line operating status, and corresponding metering point information.

[0005] Optionally, the preprocessing of the collected data, including time alignment, outlier cleaning, and format standardization, includes: Based on the set synchronization window, time alignment is performed on multi-source data to unify the time dimension of the data; Outlier data is removed using statistical criteria, and missing data is supplemented using interpolation or the average of adjacent windows. Convert all data into a unified, standardized storage format; The statistical criteria are data screening criteria for identifying outliers based on the data mean and standard deviation.

[0006] Optionally, the definition of carbon flow accounting nodes involves constructing a multi-region, multi-voltage-level node branch electrical topology using graph theory algorithms, forming a cascaded carbon flow network model with three-dimensional correlation of topological power and carbon flow. Based on the proportional sharing principle and cascade loss allocation operators, node carbon potential initialization, cascade loss carbon emission allocation, multi-regional collaborative power flow carbon flow calculation, and iterative solution of node carbon emission factors are performed to obtain the instantaneous carbon emission factors of each carbon flow accounting node, including: Define carbon flow accounting nodes and assign them unique identifiers to construct a cascaded carbon flow network model with multiple regions and voltage levels; Perform node carbon potential initialization to determine the initial carbon injection amount for each node; The cascade loss carbon emission allocation is performed, and the carbon emissions corresponding to the transmission loss are allocated to the corresponding nodes according to the set rules; an equation system is established based on the principle of carbon flow conservation, and the instantaneous carbon emission factor of each carbon flow accounting node is obtained by iterative solution.

[0007] Optionally, defining carbon flow accounting nodes and assigning them unique identifiers to construct a cascaded carbon flow network model with multiple regions and voltage levels includes: Define the busbars of a specific voltage level within a specific area as carbon flow accounting nodes, and assign a unique identifier code to each node; A graph theory algorithm is used to construct the electrical topology graph of nodes and branches, clarifying the cascade relationship of each node and the connection relationship of branches; By associating power generation data, exchange power data, and topology, a three-dimensional correlation model of topological power carbon flow is formed. The topology model is updated according to a set period, and model reconstruction is automatically triggered when a major topology adjustment is detected; the cascading relationship is a hierarchical connection relationship established by nodes of different voltage levels through voltage regulating transformers.

[0008] Optionally, the step of performing cascaded loss carbon emission allocation, which allocates the carbon emissions corresponding to transmission losses to the corresponding nodes according to a set rule, includes: For transformer branches, the carbon flow rate of low-voltage side nodes is calculated using the rule that all carbon emissions from losses are distributed to the low-voltage side. For multi-level voltage cascaded scenarios, losses and carbon emissions are distributed step by step according to the voltage level from high to low. For inter-regional link branches, all carbon emissions corresponding to link losses are allocated to the corresponding nodes in the receiving region; the carbon flow rate is the amount of carbon emissions flowing through the nodes per unit time.

[0009] Optionally, the step of establishing a system of equations based on the principle of carbon flow conservation and iteratively solving it to obtain the instantaneous carbon emission factor of each carbon flow accounting node includes: Based on the principle of carbon flow conservation, a carbon flow conservation equation is established for each carbon flow accounting node, and a system of linear equations for the entire network is constructed. An iterative method was used to solve the linear equation system, and the carbon flux rate of each node was updated successively during the iteration process; After iterative convergence, the instantaneous carbon emission factor of each carbon flow accounting node is calculated; the carbon flow conservation principle is that the total carbon flow rate of the inflow node is equal to the total carbon flow rate of the outflow node.

[0010] Optionally, the process of publishing carbon emission factors, responding to user requests to complete electricity consumption carbon emission accounting, and tracing and storing evidence throughout the entire accounting process includes: The calculated carbon emission factors are organized and stored in a standardized format and then released to the public through the application programming interface. Receive regional voltage level information and electricity consumption information submitted by users, and match the corresponding carbon emission factors to calculate the total carbon emissions from electricity consumption; Based on the consortium blockchain architecture, information throughout the entire accounting process is stored and a unique storage identifier is generated for information retrieval.

[0011] Optionally, the method uses a set time period as a synchronization window to cyclically execute the entire process of data acquisition and preprocessing, cascaded carbon flow network model update, dynamic carbon flow calculation, factor release and accounting and storage, so as to realize the dynamic update of carbon emission factors.

[0012] The second objective of this invention is to provide a multi-region, multi-voltage cascaded power carbon emission factor collaborative accounting system for implementing the multi-region, multi-voltage cascaded power carbon emission factor collaborative accounting method described above. The system includes: The multi-source heterogeneous data acquisition layer adopts a distributed acquisition architecture and is deployed at power grid nodes in various regions to synchronously acquire three types of core data and complete preprocessing and encrypted transmission. The regional voltage level cascaded topology modeling module is used to define carbon flow accounting nodes, construct a cascaded carbon flow network model with three-dimensional correlation between topological power and carbon flow, and support dynamic updates. The dynamic carbon flow tracking and factor calculation engine has a built-in collaborative accounting algorithm for performing carbon flow initialization, loss allocation and iterative solution, and outputting the instantaneous carbon emission factor of each node; The collaborative accounting and application service layer is used to release carbon emission factors to the public and provide carbon emission accounting and full-process traceability and evidence storage services for electricity consumption.

[0013] This solution first collects three types of core data simultaneously and performs standardized preprocessing to provide a unified and compliant data foundation for subsequent modeling and calculation. Based on this, a cascaded carbon flow network model spanning multiple regions and voltage levels is constructed. By combining cascaded loss allocation rules with iterative carbon flow conservation, the instantaneous carbon emission factors of each node are obtained, enabling accurate transmission and quantification of carbon flow across regions and voltage levels. Finally, factors are published through an interface to complete electricity consumption accounting, and the entire process is simultaneously documented, directly supporting the execution of low-carbon optimized scheduling. Data is transmitted sequentially and seamlessly in each stage, forming a complete link from data input, model construction, factor calculation to application output. This expands the dimensional coverage of carbon emission accounting, improves the rationality of loss allocation and the accuracy of results, while ensuring the traceability of the accounting process and adapting to the scheduling needs of dynamic grid operation. Attached Figure Description

[0014] Figure 1 This is a flowchart of the collaborative accounting method for power carbon emission factors in multi-region and multi-voltage cascade of 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] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0017] In the embodiments of this application, the multi-regional, multi-voltage cascaded power carbon emission factor collaborative accounting method can be applied to power systems at various levels, such as provincial interconnected power grids, regional cluster power grids, and inter-city power supply networks. It supports power carbon emission factor calculation, electricity consumption carbon emission accounting, carbon flow tracking analysis, and low-carbon operation scheduling. This solution focuses on the entire process of carbon flow accounting and scheduling in multi-regional, multi-voltage scenarios, forming a complete technical path from multi-source data acquisition and preprocessing, cascaded carbon flow network construction, dynamic carbon flow factor calculation to accounting application and evidence storage. It can cover power grid levels of different regions and voltage levels, realizing cascaded carbon flow tracking and dynamic factor calculation, providing data and technical conditions for low-carbon operation of the power system.

[0018] like Figure 1As shown, a collaborative accounting method for electricity carbon emission factors in a multi-regional, multi-voltage cascade manner is illustrated, including: Simultaneously collect power generation data, network topology data, and switching power data. Perform preprocessing on the collected data, including time alignment, outlier cleaning, and format standardization. Output the preprocessed data through an encrypted transmission protocol. Define carbon flow accounting nodes, and use graph theory algorithms to construct the electrical topology of node branches in multiple regions and at multiple voltage levels, forming a cascaded carbon flow network model with three-dimensional correlation of topological power carbon flow. Based on the principle of proportional sharing and the cascade loss allocation operator, perform node carbon potential initialization, cascade loss carbon emission allocation, multi-regional collaborative power flow carbon flow calculation, and iterative solution of node carbon emission factors to obtain the instantaneous carbon emission factors of each carbon flow accounting node. Release carbon emission factors, respond to user requests to complete electricity carbon emission accounting, trace and record the entire accounting process, and perform collaborative accounting of electricity carbon emission factors across multiple regions and voltage levels.

[0019] Specifically, the overall implementation process of this solution comprises three main parts. First, it involves the synchronous acquisition and preprocessing of multi-source heterogeneous data, covering three core data categories: power generation, network topology, and switching power. This includes time alignment, anomaly cleaning, format standardization, and encrypted transmission, providing a unified data input for subsequent model building and calculation. Second, it involves the construction of a cascaded carbon flow network and dynamic carbon flow calculation. Carbon flow calculation nodes are defined, and a multi-regional, multi-voltage cascaded topology model is constructed. Power and carbon flow parameters are correlated to form a three-dimensional correlation network. Then, node carbon potential initialization, cascaded loss allocation, cross-regional carbon flow calculation, and iterative solution are executed sequentially to obtain the instantaneous carbon emission factor for each node. Finally, it involves factor release and calculation application. Standardized carbon emission factors are released externally, and electricity carbon emission calculations are completed in response to user requests. The entire calculation process is traceable and documented, supporting collaborative calculation of electricity carbon emission factors across multiple regions and voltage levels.

[0020] In this embodiment of the application, the data acquisition process covers three core data types: power generation side, network topology, and switching power. These three types of data correspond to the three dimensions of carbon flow source, transmission carrier, and cross-regional interaction, respectively, and together constitute the basic data system for carbon flow accounting.

[0021] Specifically, the data collection on the generation side covers all types of generating units within the power grid, including thermal power, gas power, hydropower, nuclear power, wind power, photovoltaic power, biomass power, and other power sources. The collected parameters include the unit's real-time active power, unit nameplate parameters, generation type, real-time fuel consumption data, and unit carbon emission intensity. The real-time active power of the generating unit reflects its real-time output level and is a fundamental parameter for calculating total carbon flow. The unit nameplate parameters include basic information such as rated capacity and years of operation, used to assist in verifying the rationality of the output data. The power generation type is distinguished by standardized codes, with different power generation types corresponding to different carbon emission characteristics and accounting rules. Real-time fuel consumption data is collected for fossil energy generating units, including the real-time consumption of fuels such as coal and natural gas, and is the direct basis for calculating carbon emissions from fuel combustion. The unit's carbon emission intensity is calibrated using both the measured method and the conversion factor method. For units with online flue gas monitoring, the carbon emission intensity is calculated in real time based on the monitored gas concentration and flue gas flow. For units without online monitoring, the carbon emission intensity is calculated using industry-standard conversion factors combined with the unit's actual output. This dual calibration ensures the accuracy of the carbon emission intensity data.

[0022] It should be noted that the data collected from the power generation side comes from multiple systems, including the power plant production management system, flue gas monitoring system, and dispatch automation system. These different systems have different data collection frequencies, therefore, time alignment processing is required during the preprocessing stage. The data collection frequency for various types of generator units can be adjusted according to the power source type. Fossil fuel units experience relatively rapid fluctuations in output and emissions, allowing for a higher collection frequency. New energy units, whose output fluctuations are affected by natural conditions, also require a corresponding collection frequency to ensure the data reflects the real-time operating status of the units.

[0023] For example, the network topology data collection covers all voltage levels within the power grid, including power grid equipment at different levels such as ultra-high voltage, high voltage, medium voltage, and low voltage. The collected parameters include node connection relationships, line parameters, transformer parameters, and bus parameters. Node connection relationships clearly define the electrical connections between each bus and device, forming the basis for constructing the topology model. Line parameters include electrical parameters such as conductor resistance, reactance, and susceptance, used to calculate line power losses. Transformer parameters include parameters such as turns ratio, impedance, no-load loss, and load loss, used to calculate the relationship between transformer power losses and voltage transformation. For voltage regulating transformers, tap position data is also collected to reflect the real-time operating tap. Bus parameters include basic information such as rated voltage, rated capacity, and grounding method. The network topology data is collected using a combination of static basic data and dynamically updated data. Static basic data includes infrequently changing information such as equipment nameplate parameters and fixed connection relationships, which is collected and updated periodically. Dynamic updated data includes real-time changing information such as tap positions, temporary topology adjustments, and equipment activation / deactivation status, collected in real time to ensure that the topology data is consistent with the actual operating state of the power grid.

[0024] Specifically, the power exchange data collection covers all inter-regional tie lines, including inter-provincial tie lines, inter-city tie lines, and regional interconnection tie lines at different levels of cross-regional connections. The collected parameters include bidirectional active power values, power transaction contract identifiers, tie line loss data, tie line operating status, and corresponding metering point information. The bidirectional active power values ​​reflect the direction and magnitude of power transmission on both sides of the tie line, serving as a direct basis for calculating cross-regional carbon flow transfer; the power transaction contract identifier corresponds to each cross-regional power transaction and is used to associate the carbon emission responsibility corresponding to the transaction; the tie line loss data reflects the power loss during line transmission and the corresponding carbon emissions from the lost portion; the tie line operating status reflects whether the line is in operation, out of operation, or under maintenance, used to determine the validity of the topology connection; and the corresponding metering point information includes the metering point number, installation location, and metering accuracy, ensuring the traceability of the power exchange data.

[0025] In this embodiment, after the raw data acquisition is completed, all data needs to be preprocessed to eliminate differences in time, format, and quality among multi-source data, ensuring the accuracy and consistency of subsequent calculations. Preprocessing includes three core steps: time alignment, outlier cleaning, and format standardization. The processed data is then transmitted using encryption.

[0026] Specifically, the time alignment process uses a set synchronization window as a benchmark to align multi-source data with different acquisition frequencies and timestamps to the same time node. The synchronization window can be set according to actual needs, typically fifteen minutes, but can be adjusted to five or ten minutes depending on scheduling accuracy requirements. Time alignment uses standard time as a benchmark. For data with an acquisition frequency higher than the synchronization window, the statistical value within the synchronization window is calculated by averaging. For data with an acquisition frequency lower than the synchronization window, interpolation is used to complete the data, ensuring that the time dimension of all data is completely consistent, enabling topology modeling and carbon flow calculations to be performed at the same time cross-section.

[0027] It should be noted that the outlier cleaning process uses statistical criteria to identify and remove outlier data, while also completing missing data. The statistical criteria identify outliers based on the mean and standard deviation of the data, classifying data that deviates from the mean by more than three standard deviations as outliers and removing them. For missing data, if the missing duration is no more than one synchronization window, linear interpolation is used for completion; if the missing duration exceeds one synchronization window, the average of adjacent synchronization windows is used for completion, ensuring data integrity and preventing subsequent calculation interruptions or result deviations due to missing data.

[0028] For example, the format standardization process transforms raw data from different sources and in different formats into a unified standardized storage format, defining uniform field naming rules, data types, and precision requirements. Raw data may exist in various formats such as tables, text, and time-series databases. Data from different sources may have differences in field naming, units, and precision. After standardization, all data has a unified data structure and can be directly used by subsequent modeling and calculation modules. The standardized data undergoes integrity verification to ensure that key fields are not missing and that numerical ranges are logically consistent. Data that passes verification proceeds to the transmission stage.

[0029] Specifically, the preprocessed and qualified data is transmitted via an encrypted transmission protocol. The transmission process employs a combination of symmetric and asymmetric encryption to ensure that the data is not tampered with or leaked during transmission. After the data is transmitted to the corresponding computing node, it is decrypted and its integrity is verified. Once the data is confirmed to be correct, it is stored in the corresponding data storage unit for subsequent modules to access.

[0030] In the specific application of this statistical criterion, the mean and standard deviation of a parameter are first calculated over multiple consecutive synchronization windows. Then, the difference between the parameter value in the current synchronization window and the mean is calculated. If the absolute value of the difference is greater than three times the standard deviation, the data is considered an outlier. The principle of this criterion is based on the statistical characteristics of the normal distribution; the vast majority of normal data will fall within three times the standard deviation of the mean. Data exceeding this range has an extremely low probability of occurrence and can be identified as outlier. This criterion can automatically identify various types of outlier data without the need for manually setting fixed thresholds, adapting to different parameter value ranges, and improving the versatility and accuracy of outlier identification.

[0031] In this embodiment, after data preprocessing, the core step of cascaded carbon flow modeling and factor calculation is performed. This step consists of four parts: first, defining carbon flow accounting nodes and constructing a multi-region, multi-voltage-level cascaded carbon flow network model; second, initializing the node carbon potential to determine the initial carbon injection of each node; third, performing cascaded loss carbon emission allocation to distribute the carbon emissions corresponding to transmission losses to the corresponding nodes; and finally, establishing a system of equations based on carbon flow conservation and iteratively solving them to obtain the instantaneous carbon emission factor of each carbon flow accounting node. These four parts are sequentially connected, with the output of the previous part serving as the input of the next, ultimately completing the calculation of the carbon flow factor.

[0032] Specifically, the cascaded carbon flow network model serves as the basis for carbon flow calculations. The model is constructed based on the actual power grid topology and incorporates power and carbon flow parameters, reflecting the transmission patterns of carbon flow along with power flow across multiple regions and voltage levels. After the model is built, it needs to be validated to ensure that the topological connections and parameter values ​​are consistent with the actual power grid. Only after successful validation can it be used for carbon flow calculations.

[0033] It should be noted that node carbon potential initialization is the starting step in carbon flow calculation. By determining the initial carbon injection amount of each node, it provides an initial value for subsequent carbon flow transfer and distribution. The initial carbon injection mainly comes from the generator sets directly connected to the node, as well as distributed power sources fed back from the low-voltage side to the high-voltage side. The initial carbon injection of other nodes is zero, and is subsequently updated through carbon flow transfer from upstream nodes.

[0034] For example, cascading loss carbon emission allocation is a crucial step in ensuring the accuracy of multi-voltage cascading accounting. Power loss occurs during electricity transmission between different voltage levels and across regions, and the corresponding carbon emissions need to be allocated to the appropriate nodes according to reasonable rules to avoid unattended or duplicated carbon emissions. This solution sets corresponding loss allocation rules for transformer branches and tie line branches, which conforms to the actual laws of carbon flow transmission and improves the rationality of the accounting results.

[0035] Specifically, the iterative solution process constructs a set of carbon flow equations for the entire network based on the principle of carbon flow conservation. An iterative algorithm is used to solve for the carbon flow rate of each node, and then the instantaneous carbon emission factor of each node is calculated. Iterative solution can handle carbon flow calculation problems under complex topologies, ensuring that the calculation results meet the constraints of carbon flow conservation, while also possessing high computational efficiency and adapting to dynamic update time requirements.

[0036] In this embodiment, the construction of the cascaded carbon flow network model includes four steps: node definition and encoding, topology graph construction, three-dimensional parameter association, and dynamic model updating. These four steps gradually improve the structure and parameters of the model, ultimately forming a usable cascaded carbon flow analysis model.

[0037] Specifically, a carbon flow accounting node is defined as a busbar at a specific voltage level within a specific region. The busbar is a node for the collection and distribution of electrical energy in the power grid, and also the corresponding node for the collection and distribution of carbon flow. Using the busbar as a carbon flow accounting node matches the transmission patterns of electrical flow, facilitating the mapping between carbon flow and electrical flow. Each carbon flow accounting node is assigned a unique identifier code, consisting of three parts: a region code, a voltage level code, and a busbar number. This code directly identifies the node's region affiliation, voltage level, and number, facilitating node management and querying. Each node also has complete attribute information, including region affiliation, voltage level, connected branches, and load type, comprehensively reflecting the node's electrical and operational characteristics.

[0038] It should be noted that nodes at different voltage levels are connected hierarchically through voltage regulating transformers, forming a cascaded structure. The high-voltage busbar supplies power to the low-voltage busbar via transformers, with electricity being transferred step-by-step from high to low voltage levels, and carbon flow being transferred accordingly. Multiple voltage levels within the same region are connected sequentially through transformers, forming a full-voltage-level cascaded network for that region. These cascaded networks from multiple regions are connected by tie lines, forming a multi-region, multi-voltage-level cascaded carbon flow network across the entire network.

[0039] For example, the construction of the node branch electrical topology graph adopts a graph theory algorithm, using carbon flow accounting nodes as vertices and electrical branches such as lines and transformers as edges, constructing a complete topology graph based on the actual electrical connection relationships. The topology graph clearly defines the starting and ending nodes of each branch, as well as the branch type and electrical parameters. Line branches are used to connect different nodes at the same voltage level, realizing power and carbon flow transmission at the same voltage level; transformer branches are used to connect nodes at different voltage levels, realizing cascaded power and carbon flow transmission across voltage levels; tie line branches are used to connect nodes in different regions, realizing cross-regional power and carbon flow interaction.

[0040] Specifically, the 3D correlation modeling process correlates power generation data, exchange power data, and topology to form a 3D correlation model of topology, power, and carbon flow. The topology dimension corresponds to the connection structure between nodes and branches; the power dimension corresponds to the injected power of each node, the transmitted power of each branch, and the power loss; and the carbon flow dimension corresponds to the carbon emission intensity of each power source and the initial carbon injection of each node. The parameters in these three dimensions correspond one-to-one, enabling the model to calculate the distribution of carbon flow based on the topology and power distribution, achieving synchronous mapping between power flow and carbon flow.

[0041] It should be noted that the cascaded carbon flow network model has a dynamic update function, capable of updating synchronously with changes in the power grid topology. The model updates periodically according to a set cycle, typically every fifteen minutes, synchronously updating topology parameters, power data, and carbon flow parameters. When a major topology adjustment is detected in the power grid, such as the addition of new lines, new generating units, substation commissioning, or changes to the main grid structure, the model will automatically trigger a reconstruction process to rebuild the topology and associate the corresponding parameters, avoiding errors in carbon flow calculation results due to topology deviations.

[0042] In this cascading relationship definition, nodes at different voltage levels are electrically connected via transformers. As electricity flows from high-voltage to low-voltage nodes, voltage transformation and power losses occur through the transformers, and the corresponding carbon flow is also transferred from the high-voltage side to the low-voltage side, along with the carbon emissions from the additional losses. This hierarchical transfer relationship is called a cascading relationship, reflecting the actual process of power flow from high-voltage transmission networks to low-voltage distribution networks in a power system, with the corresponding carbon flow following the same hierarchical transfer pattern. By constructing a cascading relationship, carbon flow calculations at different voltage levels can be linked together, enabling continuous tracking of carbon flow across all voltage levels.

[0043] In this embodiment, cascaded loss carbon emission allocation sets allocation rules for transformer branches and tie line branches respectively, ensuring that the carbon emissions corresponding to transmission losses can be accurately allocated to the corresponding nodes, conforming to the actual laws of carbon flow transmission. The allocation process includes three parts in sequence: transformer branch loss allocation, multi-level voltage step-by-step allocation, and tie line branch loss allocation, covering all branch types with transmission losses.

[0044] Specifically, the loss allocation in transformer branches follows the rule that all carbon emissions from losses are distributed to the low-voltage side. During the flow of electricity from the high-voltage side node to the low-voltage side node via the transformer, no-load losses and load losses are generated. These losses are incurred to supply power to the low-voltage side, and therefore, the corresponding carbon emissions are entirely borne by the low-voltage side and added to the total carbon injection at the low-voltage side node. This rule conforms to the principle of "whoever benefits bears the cost," with the low-voltage side, as the beneficiary of electrical energy, bearing the carbon emissions corresponding to the losses during transmission, thus accurately reflecting the overall carbon emission level of electricity consumption on the low-voltage side.

[0045] It should be noted that the carbon flow rate at the low-voltage side node of the transformer is calculated using a corresponding formula. This formula is derived based on the ratio of the input carbon flow to losses on the high-voltage side, accurately reflecting the carbon flow level on the low-voltage side after accounting for losses. The formula is expressed as follows: the carbon flow rate at the low-voltage side node equals the carbon flow rate flowing into the high-voltage side node multiplied by the ratio of the active power injected on the high-voltage side to the active power injected on the high-voltage side minus the transformer's active power losses. That is:

[0046] in The carbon flow rate flowing into the high-pressure side node. For transformer active power loss, Injecting active power to the high-voltage side, This represents the carbon flow rate at the low-voltage side node. The principle behind this calculation is to add the carbon emissions corresponding to transformer losses to the carbon flow on the low-voltage side. Due to the existence of losses, the active power received by the low-voltage side is less than the active power injected by the high-voltage side, and all the carbon flow is transferred to the low-voltage side. Therefore, the carbon flow rate per unit power on the low-voltage side will be higher than that on the high-voltage side, reflecting the distribution rule that the carbon emissions from losses are borne by the low-voltage side.

[0047] For example, in scenarios with multiple voltage levels cascaded, such as a power grid containing five voltage levels, loss allocation is performed step-by-step from high to low voltage level. First, the transformer losses from the highest voltage level to the second highest voltage level are calculated, and the carbon emissions from these losses are allocated to the nodes at the second highest voltage level. Then, the transformer losses from the second highest voltage level to the medium voltage level are calculated, and the carbon emissions from these losses are allocated to the nodes at the medium voltage level. This process continues down the voltage level until the lowest voltage level node. This step-by-step allocation ensures that the transmission losses of each voltage level are accurately distributed to the corresponding low-voltage side nodes, achieving complete transmission of carbon emissions across all voltage levels and avoiding any omissions or duplicate allocations of losses.

[0048] Specifically, the loss allocation of inter-regional tie-line branches follows the rule that all carbon emissions from losses are allocated to the receiving region. During cross-regional power transmission, the power losses generated by the tie-line are incurred to transmit power to the receiving region; therefore, the corresponding carbon emissions are entirely borne by the receiving region and added to the total carbon injection of the corresponding node in the receiving region. This rule also follows the principle of "whoever benefits bears the cost," meaning that the receiving region, as the recipient of the power, bears the carbon emissions corresponding to the losses during transmission, thus accurately reflecting the overall carbon emission level of the power received by the receiving region.

[0049] It should be noted that in bidirectional power transmission scenarios using tie lines, the sending and receiving ends are determined based on the actual power transmission direction, thus determining who bears the losses. When power flows from region A to region B, region A is the sending end and region B is the receiving end, and the carbon emissions corresponding to tie line losses are borne by region B. When power flows in the opposite direction from region B to region A, region B is the sending end and region A is the receiving end, and the carbon emissions corresponding to tie line losses are borne by region A. By dynamically determining the transmission direction and adjusting the loss-bearing party, the system can adapt to bidirectional power flow scenarios and ensure the rationality of the allocation rules.

[0050] In this specific definition of carbon flow rate, carbon flow rate represents the amount of carbon emissions flowing through a node or branch per unit time, typically expressed in tons of carbon dioxide per hour. Carbon flow rate is a core parameter in carbon flow calculations, corresponding to the power parameter in a power system. Power represents the electrical energy transmitted per unit time, while carbon flow rate represents the amount of carbon emissions accompanying the transmission of electrical energy per unit time. Combining these two parameters allows for the calculation of the carbon emission intensity per unit of electrical energy. Carbon flow rate changes synchronously with changes in electrical current, reflecting the real-time transmission rate and total amount of carbon.

[0051] In this embodiment, after completing the initial carbon injection calculation and loss allocation for each node, a set of carbon flow equations for the entire network is constructed based on the principle of carbon flow conservation. The carbon flow rate of each node is obtained by solving the equations using an iterative algorithm, and then the instantaneous carbon emission factor of each carbon flow accounting node is calculated. The solution process includes three steps in sequence: constructing the conservation equations, iterative calculation, and convergence output.

[0052] Specifically, the principle of carbon flow conservation is the fundamental principle of carbon flow calculation, corresponding to Kirchhoff's current law in power systems. This means that at any node, the total carbon flow rate flowing into the node is equal to the total carbon flow rate flowing out of the node. Carbon flow cannot be created or destroyed out of thin air; it only transfers with the transmission of electricity. Based on this principle, a corresponding carbon flow conservation equation can be established for each carbon flow calculation node. The conservation equations of all nodes together constitute a system of linear equations for the entire network.

[0053] It should be noted that the carbon flow conservation equation for a single node can be expressed by the corresponding calculation formula. The left side of the equation is the sum of the products of the carbon flow rate and the corresponding active power of all inflow branches, and the right side of the equation is the sum of the products of the carbon flow rate and the corresponding active power of all outflow branches.

[0054] The formula is expressed as the sum of the products of carbon flow rate and active power in all inflow branches, which is equal to the sum of the products of carbon flow rate and active power in all outflow branches. That is:

[0055] in, For the first Carbon flow rate of each inflow branch For the first The active power flowing into the branch circuit, The number of inflow branches; For the first Carbon flow rate of the outflow branch For the first The active power of each outflow branch. This represents the number of outflowing branches. This calculation formula reflects the carbon flow conservation constraint at the nodes, ensuring that the total carbon flow is balanced at the nodes, and serves as the basic unit for constructing the entire network carbon flow equation set.

[0056] For example, constructing the entire network's linear equation system requires traversing all carbon flow accounting nodes, establishing a corresponding conservation equation for each node, and combining this with the initial carbon injection conditions of the nodes to form a complete equation system. The unknowns in the equation system are the carbon flow rates of each node, and the number of equations is consistent with the number of unknowns, possessing a unique solution. Due to the large number of nodes in the power grid, directly solving the equation system involves a large computational load; therefore, an iterative method is used to solve it, which can improve computational efficiency while ensuring accuracy.

[0057] Specifically, the iterative solution employs the Gauss-Seidel iterative method, with the initial value being the carbon flux rate corresponding to the initial carbon injection at each node. During the iteration, the carbon flux rate of each node is updated sequentially, and the latest calculated node value is used in the calculation of subsequent nodes, accelerating the convergence speed. A convergence accuracy threshold is set during the iteration; when the difference between the carbon flux rates of all nodes before and after the iteration is less than the convergence accuracy, the iteration is considered converged, and the calculation stops. A maximum number of iterations is also set to prevent convergence failure due to special circumstances, ensuring the calculation process can terminate normally.

[0058] It should be noted that after iterative convergence, the carbon flow rate of each carbon flow accounting node is obtained. Combined with the node's total active power, the instantaneous carbon emission factor for that node is calculated. The carbon emission factor equals the node's carbon flow rate divided by its total active power, representing the carbon emissions corresponding to a unit of electrical energy consumed at that node. It can be directly used to calculate the carbon emissions from electricity consumption of the load connected to that node. Different carbon emission factors correspond to nodes in different regions and at different voltage levels, accurately reflecting the differences in carbon emission levels from electricity consumption at different locations.

[0059] In the specific meaning of this carbon flow conservation principle, carbon flow is generated and transmitted along with electrical flow. Electrical flow follows the law of node current conservation, and carbon flow correspondingly follows the law of node carbon flow conservation. For any electrical node, the total carbon flow carried by all inflow branches equals the total carbon flow carried by all outflow branches plus the total carbon flow injected into the node itself. The carbon flow injected into the node comes from directly connected generators and is the source of the node's carbon flow; the carbon flow carried by branches is transmitted between nodes along with the electrical flow and is the carrier of carbon flow transmission. The carbon flow conservation principle ensures that the total carbon flow in the entire network remains balanced. All carbon emissions generated by power sources are ultimately distributed to loads and losses, without any total deviation. This is the fundamental guarantee that carbon flow calculation has physical meaning.

[0060] In this embodiment, after obtaining the instantaneous carbon emission factors of each node, the process proceeds to the factor release and accounting application stage. This stage sequentially includes three parts: factor release, electricity consumption carbon emission accounting, and full-process traceability and evidence storage, realizing the external output and practical application of carbon factors while ensuring the traceability of the accounting process.

[0061] Specifically, the factor release process first involves organizing the calculated carbon emission factors into a standardized format. Each factor record includes fields such as node identifier, region code, voltage level, carbon emission factor value, calculation timestamp, data precision, and source identification, forming a standardized factor dataset. The standardized factor data is then stored and managed in a distributed database with high concurrency capabilities, capable of supporting simultaneous query requests from a large number of users. The factor data is released externally via an application programming interface (API). The API supports encrypted transmission and provides various service methods, including factor query, batch download, and real-time push, to meet the needs of different types of users.

[0062] It should be noted that the factor release process also includes an anomaly warning function. This function monitors the calculated carbon emission factors in real time. When a node's carbon emission factor experiences significant fluctuations exceeding a set threshold, an early warning mechanism is automatically triggered, notifying operations and maintenance personnel to investigate the cause of the anomaly. Abnormal fluctuations can be caused by various factors such as sudden changes in unit output, topology adjustments, and data anomalies. The early warning system enables timely detection and handling of problems, ensuring the accuracy of the released factors.

[0063] For example, the electricity consumption carbon emission accounting process provides accounting services to various types of electricity users. Users submit accounting requests through an access port, which include information such as the region and voltage level of the electricity metering point, as well as the corresponding electricity consumption data. After receiving the request, the system automatically matches the carbon emission factor of the corresponding node, multiplies the electricity consumption by the carbon emission factor, and obtains the user's total electricity consumption carbon emissions. The system supports multi-dimensional statistical accounting, and can calculate the user's total carbon emissions for different time periods such as daily, weekly, monthly, quarterly, and annually, generating corresponding accounting reports. The reports include total carbon emissions, emission composition, and changing trends, and support export in multiple formats to meet different user needs.

[0064] Specifically, the traceability and evidence preservation process is implemented based on a consortium blockchain architecture. Participating nodes include system operators, regulatory authorities, and third-party verification agencies. The preserved evidence includes complete information for each accounting request, such as user information, electricity consumption data, carbon emission factors used, hash values ​​of source data, accounting process parameters, and accounting results. Each record generates a unique evidence preservation identifier. The preserved content is encrypted and written into the blockchain block, where it is jointly verified and stored by multiple nodes, ensuring the immutability and traceability of the preserved data. Users and regulatory authorities can use the evidence preservation identifier to query the corresponding complete accounting process record, verify the authenticity of the accounting results, and meet the compliance requirements of scenarios such as carbon emission verification, carbon trading, and environmental audits.

[0065] It should be noted that the consortium blockchain employs an access control mechanism, where nodes with different roles have different access permissions. Ordinary users can only query their own related evidence storage records, while regulatory authorities and verification agencies can query all evidence storage records within their authorized scope. This ensures both data verifiability and data privacy and security. Evidence storage data is backed up regularly to prevent data loss and ensure the long-term stable operation of the evidence storage service.

[0066] In this embodiment, the entire method uses a set time period as a synchronization window to cyclically execute all steps of the process, thereby achieving dynamic updates of the carbon emission factor. The duration of the synchronization window can be set according to actual scheduling needs, typically fifteen minutes, but can also be adjusted to a shorter period depending on the level of precision required for grid operation.

[0067] Specifically, within each synchronization window, the entire process of data acquisition and preprocessing, cascaded carbon flow network model update, dynamic carbon flow calculation and factor solution, factor release and accounting record storage is completed sequentially, outputting the carbon emission factor and accounting results for that time segment. Through periodic cyclic execution, the carbon emission factor can be updated in real time with dynamic factors such as changes in generator output, fluctuations in inter-regional power exchange, and topology adjustments, always reflecting the current actual carbon flow distribution status of the power grid.

[0068] It should be noted that during the dynamic update process, if special circumstances such as data anomalies or topology failures are detected, the system will automatically perform fault tolerance handling, temporarily replacing the data with valid data from the previous cycle, and simultaneously issuing an alarm to notify maintenance personnel for handling, thus preventing the entire system from stopping due to local anomalies. After the anomaly is resolved, the system will automatically resume the normal dynamic update process, ensuring service continuity.

[0069] In this embodiment of the application, a multi-regional, multi-voltage cascaded power carbon emission factor collaborative accounting system is also provided to implement the above-mentioned scheduling method. The system comprises four core components: a multi-source heterogeneous data acquisition layer, a regional voltage level cascaded topology modeling module, a dynamic carbon flow tracking and factor calculation engine, and a collaborative accounting and application service layer. The components communicate with each other through standardized data interfaces to collaboratively complete the entire process from data acquisition to application services.

[0070] Specifically, the multi-source heterogeneous data acquisition layer adopts a distributed acquisition architecture, deployed in dispatch centers, substations, and metering points across various regional power grids. Each acquisition node is equipped with an independent data acquisition terminal and time synchronization module, ensuring a unified time reference for data acquisition at different locations. The acquisition layer integrates various data acquisition devices, enabling it to interface with multiple data sources such as power plant production systems, flue gas monitoring systems, dispatch automation systems, and metering systems, achieving synchronous acquisition of generation-side data, network topology data, and switching power data. The acquisition layer has a built-in preprocessing unit that automatically performs preprocessing operations such as time alignment, outlier cleaning, and format standardization, outputting standardized data. The acquisition layer also features encrypted transmission, transmitting preprocessed data through an encrypted channel to subsequent modeling modules, ensuring data transmission security.

[0071] It should be noted that the regional voltage level cascaded topology modeling module communicates with the multi-source heterogeneous data acquisition layer, receiving various pre-processed data and responsible for the construction and maintenance of the cascaded carbon flow network model. The module has a built-in graph theory modeling tool that can automatically identify the connection relationships between nodes and branches, construct the electrical topology diagram of nodes and branches, and automatically associate power parameters and carbon flow parameters to form a three-dimensional associative cascaded carbon flow network model. The module has dynamic update capabilities, updating model parameters according to a set period, and supports automatic reconfiguration under major topology adjustments, always maintaining consistency between the model and the actual power grid. The cascaded carbon flow network model output by the module is transmitted to the dynamic carbon flow tracking and factor calculation engine as the basis for carbon flow calculation.

[0072] For example, the dynamic carbon flow tracking and factor calculation engine is the core computing unit of the system. It incorporates a collaborative accounting algorithm based on the proportional sharing principle and cascaded loss allocation operators. It can invoke the cascaded carbon flow network model and sequentially execute the calculation process of node carbon potential initialization, cascaded loss carbon emission allocation, multi-regional collaborative power flow carbon flow calculation, and iterative solution of node carbon emission factors, ultimately outputting the instantaneous carbon emission factors of each carbon flow accounting node. The engine possesses high-efficiency computing capabilities, capable of completing the carbon flow calculation of the entire network within a set synchronization window, meeting the timeliness requirements of dynamic updates. The engine also has parameter configuration functions, allowing adjustment of parameters such as iteration accuracy, loss allocation rules, and update cycle to adapt to different power grid scenarios and accounting needs.

[0073] Specifically, the collaborative accounting and application service layer serves as the system's external interaction window. It communicates with the dynamic carbon flow tracking and factor calculation engine, receives calculated carbon emission factor data, and provides application services such as factor release, electricity consumption accounting, and source tracing and evidence storage. The service layer includes built-in factor release, carbon emission accounting, and source tracing and evidence storage modules, each implementing its corresponding functions. It also provides standardized external interfaces to support integration with external systems. The service layer features access control, tiered access permissions for different users, and ensures data access security. The service layer supports multiple terminal access methods, allowing users to access related services through web pages, mobile devices, and other channels, enhancing ease of use.

[0074] It should be noted that the data flow between different parts of the system is clear. Standardized data output from the multi-source heterogeneous data acquisition layer is input to the regional voltage level cascaded topology modeling module. The cascaded carbon flow network model output from the modeling module is input to the dynamic carbon flow tracking and factor calculation engine. The carbon emission factors output by the engine are input to the collaborative accounting and application service layer, which ultimately provides services to the outside world. Data flows unidirectionally and is processed step by step between modules. Each module processes the input data and outputs the results to the next module, forming a complete data processing chain. The system also has unified operation and maintenance management functions, which can monitor the operating status of each module, configure system parameters, and alarm and handle abnormal situations to ensure the stable and reliable operation of the system.

[0075] For example, this solution can be applied to the low-carbon optimization dispatching of a cross-regional interconnected power grid. This interconnected power grid includes multiple prefecture-level administrative regions, covers five voltage levels, has various types of generating units, multiple cross-regional interconnection lines and a large amount of electricity trading, and has diverse industrial, commercial and residential load types, a complex power grid structure, and obvious cross-regional and cross-voltage transmission characteristics of carbon flow.

[0076] In the application process, data acquisition terminals are first deployed at dispatch centers, substations, and metering points in various regions to synchronously collect generation-side data, network topology data at each voltage level, and exchange power data of cross-regional tie lines. After preprocessing including time alignment, anomaly cleaning, and format standardization, the data is encrypted and transmitted to the central computing node. Subsequently, a cascaded carbon flow network model covering all regions and voltage levels is constructed. A unique identifier is assigned to each bus node, clarifying the cascade relationship at each voltage level and the cross-regional connection relationship. Parameters such as generation power, carbon emission intensity, and line loss are associated to form a three-dimensional cascaded carbon flow network. Next, a dynamic carbon flow tracking and factor calculation engine is invoked to sequentially initialize node carbon potential, allocate losses at each level of transformer, and allocate losses of cross-regional tie lines. Then, based on carbon flow conservation, a system of equations is established and iteratively solved to obtain the instantaneous carbon emission factors for nodes at each voltage level in each region. Finally, the carbon emission factors are released externally through the service layer, providing electricity carbon emission accounting services to different entities such as power generation companies, grid companies, industrial users, and commercial users. Simultaneously, all accounting processes are stored on the blockchain to support regulatory verification and carbon trading applications. The overall data and model are updated every fifteen minutes, dynamically adjusting the carbon emission factor according to the grid operation status to support the low-carbon optimization scheduling of the grid. For example, it optimizes cross-regional power trading plans based on the differences in carbon emission factors of each node, guides the optimal allocation of clean energy across the entire grid, and reduces the overall carbon emission level of the entire grid.

[0077] Through the application of this solution, the carbon emission accounting of the interconnected power grid covers all regions and all voltage levels, which solves the limitations of the previous single-region and single-voltage accounting. The allocation rules of loss carbon emissions are more in line with the actual carbon flow transmission law, the rationality of the accounting results is improved, and the entire accounting process is traceable, which can meet the needs of various compliance scenarios and effectively support the low-carbon optimization scheduling of the power grid.

[0078] It should be noted that current technologies in the field of electricity carbon emission accounting are mostly focused on single regions and single voltage levels, emphasizing the calculation of carbon emission intensity on the generation side, and rarely addressing the cascading transmission across multiple voltage levels and cross-regional carbon flow transfer. Some technologies involve carbon flow tracking, but they often use simplified average emission factors, treating transmission losses rather crudely, either ignoring losses altogether or using average allocation methods, which deviate from the actual carbon flow transmission patterns. Furthermore, most technologies apply data acquisition, topology modeling, carbon flow calculation, and evidence storage services independently, failing to form a complete technical system covering the entire process, making it difficult to simultaneously meet the needs of multi-dimensional coverage, reasonable loss allocation, dynamic real-time updates, and process traceability.

[0079] Specifically, graph theory topology modeling methods were originally used primarily in power grid electrical analysis and power flow calculation, focusing on power and voltage calculations and analysis, with less deep integration with carbon flow accounting. The design of cascade loss allocation rules needs to consider the physical characteristics of power transmission and the principles of carbon emission responsibility definition, attributing all losses to the low-voltage side and receiving end. This requires corresponding derivation of carbon flow transmission laws and responsibility definition principles, rather than directly applying existing power loss allocation methods. Combining topology modeling, cascade loss allocation, and iterative carbon flow solving can unify static topology, dynamic power transmission, and quantified carbon flow transmission into a single model, enabling continuous carbon flow tracking across multiple regions and voltage levels. This combination is not a simple technical patchwork; it requires establishing a corresponding mapping relationship between topology, power, and carbon flow, designing loss allocation operators adapted to cascade scenarios, and then solving the entire network through conservation equations, forming a complete cascade carbon flow accounting logic.

[0080] Specifically, this invention adopts the principle of allocating all lost carbon emissions to the low-pressure side. The calculation engine calculates and adds the total carbon injection amount to the low-pressure side nodes through cascaded loss allocation operators. The specific calculation formula is optimized as follows: ;in, The carbon flow rate flowing into the high-pressure side node; The active power loss of the transformer includes copper loss and iron loss. Copper loss is calculated based on the high-voltage side injected power. Copper loss = load loss coefficient × (high-voltage side injected power / transformer rated power)². Iron loss is the transformer no-load loss, a fixed value based on the nameplate parameters. Inject active power into the high-voltage side; This is the carbon flow rate allocated to the low-voltage side nodes after taking losses into account. Compared with the original formula, this optimized formula more accurately reflects the allocation logic of carbon emissions from losses, ensuring that the carbon emissions from high-voltage side power generation and the carbon emissions from losses during transmission are fully reflected on the low-voltage side, avoiding omissions or allocation deviations in carbon emissions from losses.

[0081] For example, blockchain-based evidence storage technology was originally used primarily in data storage and transaction traceability. Integrating it into the entire carbon flow accounting process requires designing corresponding evidence storage structures and on-chain processes for the source data, calculation parameters, and result data, ensuring both the validity of the evidence storage and computational efficiency. Embedding the evidence storage process into the entire process of factor release and accounting makes each accounting calculation verifiable, adapting to the compliance requirements of carbon emission regulation and trading, while not affecting the response speed of the accounting service.

[0082] In this embodiment, the dynamic periodic update mechanism links data acquisition, model updating, factor calculation, and application services into a closed-loop periodic process, enabling the entire accounting system to dynamically adjust according to the power grid's operating status, thus overcoming the limitations of static factors. This mechanism requires timely coordination among modules to complete the entire processing flow within each synchronization window, placing corresponding requirements on the processing efficiency and seamlessness of each stage, ultimately achieving near real-time factor updates to meet the scheduling needs of dynamic power grid operation.

[0083] It should be noted that this solution organically integrates multiple technical aspects, including multi-source data synchronous preprocessing, multi-voltage cascaded topology modeling, cascaded loss allocation carbon flow calculation, full-process blockchain notarization, and periodic dynamic updates, forming a complete technical system from data input to scheduling applications. Each stage is interconnected and data is linked, with the output of one stage directly serving as the input of the next. Each stage is adapted for multi-regional and multi-voltage scenarios, collectively addressing the problems of existing accounting technologies such as limited dimensions, unreasonable loss allocation, insufficient dynamism, and poor traceability. This provides comprehensive data support for low-carbon scheduling of multi-regional interconnected power grids.

[0084] Specifically, this solution can be applied to electricity spot trading scenarios, providing a carbon price signal reference for electricity transactions. In electricity spot trading, in addition to electricity prices, carbon emission costs are also an important reference factor for trading decisions. The real-time carbon emission factors obtained by this solution, categorized by region and voltage level, can provide corresponding carbon emission cost references for electricity transactions at different nodes. Trading entities can make comprehensive decisions by combining electricity prices and carbon emission costs, prioritizing the trading of low-carbon electricity and promoting the development of electricity trading towards a low-carbon direction. At the same time, the carbon transfer volume in cross-regional transactions can be accurately calculated through this solution, clarifying the carbon emission responsibilities of both the sender and receiver, avoiding double counting or omission of carbon responsibilities in cross-regional transactions, and ensuring the fairness of electricity trading.

[0085] It should be noted that this solution can be applied to demand response scenarios to guide users' low-carbon electricity consumption behavior. By disseminating real-time carbon emission factor signals to users, they can understand the carbon emission levels of electricity consumption at different times, proactively adjust their electricity consumption plans, increase electricity consumption during periods of lower carbon emission factors, and decrease electricity consumption during periods of higher carbon emission factors. Through demand-side response, peak carbon emissions of the system are reduced, and the utilization rate of clean energy is improved. For load aggregators such as industrial users and commercial parks, differentiated demand response incentive strategies can be formulated based on real-time carbon emission factors to guide users to participate in low-carbon demand response and further tap the emission reduction potential on the demand side.

[0086] For example, this solution can be applied to carbon emission assessment scenarios, providing regulatory authorities with accurate assessment data support. Based on the carbon emission data calculated by this solution, categorized by region, industry, and voltage level, regulatory authorities can formulate differentiated emission reduction assessment targets, enabling precise assessment of carbon emissions in different regions and for different entities. The assessment data is supported by blockchain evidence storage, ensuring traceability and tamper-proofing, thereby enhancing the credibility of assessment results, reducing disputes during the assessment process, and promoting the implementation of emission reduction responsibilities. Simultaneously, the calculation results can be used to identify high-emission processes and regions, allowing for the development of targeted emission reduction policies and measures, thus improving overall emission reduction efficiency.

[0087] Specifically, for green electricity trading, the carbon flow tracking capabilities of this scheme can accurately calculate the emission reductions corresponding to green electricity, providing a basis for emission reduction certification and improving the transparency and credibility of green electricity trading. For carbon inclusion scenarios, the low-carbon electricity consumption behaviors of residential users and micro and small enterprises can be converted into corresponding carbon emission reductions, incentivized through carbon inclusion mechanisms to guide the whole society to participate in low-carbon electricity consumption. The refined calculation capabilities of this scheme can provide an accurate data foundation for various low-carbon products, promoting the diversified development of the low-carbon electricity market.

[0088] It should be noted that this solution has strong adaptability in practical applications and can be adjusted according to the scale and structure of different power grids. For smaller regional power grids, the voltage level division can be appropriately simplified to reduce the number of computing nodes and improve computational efficiency. For larger inter-provincial power grids, the granularity of computing nodes can be increased, and the voltage level and regional division can be refined to ensure calculation accuracy. The model's parameters, update cycle, and loss allocation rules can all be configured according to the local power grid operation characteristics and policy requirements, adapting to the actual needs of different regions.

[0089] For example, this solution can also play a role in power grid planning. Planners can use the calculation methods in this solution to simulate and calculate the carbon flow distribution and carbon emission levels of different planning schemes, evaluate the low-carbon benefits of different schemes, and select the scheme with the best carbon emission level. For instance, it can assess the impact of new power lines and substations on regional carbon emission factors, evaluate the optimization effect of new clean energy access on the overall grid carbon flow distribution, and evaluate the regulatory effect of energy storage power station layout on the spatiotemporal distribution of carbon flow. This allows for the optimization of power grid planning schemes from a low-carbon perspective, promoting the low-carbon construction of the power grid.

[0090] Specifically, in the scenario of unit emission reduction retrofitting, this solution can be used to calculate the corresponding carbon flow changes of the unit before and after the retrofit, and evaluate the actual effect of the emission reduction retrofitting. After thermal power units undergo energy-saving and low-carbon retrofitting, their carbon emission intensity will change. Through the cascaded carbon flow model of this solution, the changes in carbon flow distribution across the entire network after the retrofit can be simulated and calculated, the impact of the retrofitting on the carbon emission factors of downstream voltage levels and regions can be evaluated, and the emission reduction benefits of the retrofitting can be comprehensively measured, providing a basis for investment decisions on unit retrofitting.

[0091] It should be noted that the data security and privacy protection mechanisms in this solution are implemented throughout the entire process. Each stage of data collection, transmission, storage, and use employs corresponding encryption and access control measures. The commercial data of power generation companies and the electricity consumption data of users are subject to strict privacy protection and are used only for carbon emission accounting and related services, and will not be disclosed to unrelated third parties. Blockchain-based evidence storage only stores the hash value of the data and necessary evidence information, without storing the original sensitive data, thus ensuring traceability while also protecting data privacy and security.

[0092] For example, the system's operation and maintenance management is 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 a logging function, recording all operations, calculations, and accesses in detail, facilitating subsequent auditing and investigation. The system also has version management capabilities; updates to models and algorithms are recorded, allowing for the tracing of algorithm iterations and ensuring the consistency and comparability of accounting methods.

[0093] In this embodiment, the verification process of the cascaded carbon flow network model has a complete verification procedure. After the model is built or updated, it is verified from multiple dimensions, including topology connectivity, parameter rationality, power balance, and carbon flow balance. Topology connectivity verification checks whether all nodes in the network are connected and whether there are any isolated nodes; parameter rationality verification checks whether the device parameters are within a reasonable range and whether there are any obvious numerical errors; power balance verification checks whether the power of each node meets the conservation constraints; carbon flow balance verification checks whether the total amount of carbon flow in the entire network is balanced and whether the carbon flow injected by the power source is equal to the sum of the carbon flow corresponding to the load and losses. Through multi-dimensional verification, the accuracy and rationality of the model can be guaranteed, and the deviation of subsequent calculation results due to model errors can be avoided.

[0094] Specifically, the node carbon potential initialization process differentiates between different types of nodes. For power nodes, i.e., nodes directly connected to generator units, the carbon emission flows of all connected units are summed as the initial carbon injection for that node. The carbon emission flow equals the unit's active power multiplied by its carbon emission intensity. For nodes with distributed generation (DG) connections, if the DG injects power from the low-voltage side to the high-voltage side, the DG's carbon emission flow is included in the node's initial carbon injection to ensure accurate calculation of the DG's carbon contribution. For nodes without direct power connections, such as pure load nodes and tie-line receiving-end nodes, the initial carbon injection is set to zero and is subsequently updated through carbon flows transmitted from upstream branches.

[0095] It should be noted that the multi-regional collaborative power flow carbon flow calculation process can handle complex scenarios with bidirectional power flows. For inter-regional interconnections, power may switch between two directions depending on supply and demand. During the calculation, the sending and receiving ends are determined based on the real-time power direction, and the carbon flow transfer amount in the corresponding direction is calculated simultaneously. When the power direction changes, the carbon flow transfer direction also changes accordingly, ensuring that the carbon flow direction always remains consistent with the power direction, accurately reflecting the cross-regional carbon flow interaction. For inter-regional interconnection scenarios with multiple interconnections, the carbon flow transfer amount of each interconnection is calculated separately, and the total carbon flow transfer amount between regions is summed to ensure the integrity of cross-regional carbon flow accounting.

[0096] For example, the convergence accuracy and maximum number of iterations in the iterative solution process can be configured according to actual needs. For scenarios with high accuracy requirements, a smaller convergence accuracy threshold can be set, while the maximum number of iterations can be appropriately increased to ensure the accuracy of the calculation results. For scenarios with high computational speed requirements, the convergence accuracy threshold can be appropriately relaxed, and the maximum number of iterations can be reduced to improve computational efficiency. The parameters under the default configuration can balance accuracy and efficiency, meeting the usage needs of most power grid scenarios. During the iteration process, the error change of each iteration will be recorded to facilitate subsequent algorithm optimization and problem troubleshooting.

[0097] Specifically, carbon emission factors can be released through multiple push methods. For users who need real-time factor data, a proactive push method can be used, actively pushing the latest data to the user's system after each factor update. For users with low query frequency, a passive query method can be used, where users initiate query requests to obtain the corresponding data as needed. These multiple release methods can adapt to different user habits and system integration needs, improving service flexibility.

[0098] It should be noted that the electricity carbon emission accounting supports batch accounting. For large enterprises, industrial parks, and other users with multiple metering points, electricity consumption data from all metering points can be imported in batches. The system automatically matches the carbon emission factors of the corresponding nodes, completes the carbon emission accounting for all metering points in batches, and generates a summary accounting report, reducing the amount of work for users and improving accounting efficiency. Batch accounting also supports full-process evidence storage. The accounting result for each metering point corresponds to a unique evidence storage identifier, ensuring the traceability of batch accounting results.

[0099] For example, the traceability and evidence storage query function supports multi-dimensional queries. Besides precise queries based on evidence storage identifiers, queries can also be filtered by time range, user type, region, and other conditions, facilitating batch verification and statistical analysis by regulatory authorities. The retention period of the evidence storage data complies with relevant regulatory requirements, meeting the needs of long-term traceability. The evidence storage system has a disaster recovery backup mechanism; data is stored on multiple nodes, and the failure of a single node will not affect the integrity of the evidence storage data or the availability of the query service.

[0100] Specifically, the multi-source heterogeneous data acquisition layer is scalable, allowing for the addition of new data sources and acquisition points as needed. When new generating units, lines, or substations are added to the power grid, corresponding acquisition terminals and data interfaces can be added to the acquisition layer, quickly integrating them into the overall data acquisition system and adapting to the power grid's development and expansion. The preprocessing rules of the acquisition layer also support configuration updates, allowing for adjustments to anomaly identification rules and standardized formats based on changes in data types, ensuring the adaptability of preprocessing functions.

[0101] It should be noted that the regional voltage level cascaded topology modeling module supports manual adjustment. Maintenance personnel can manually adjust the topology and parameters according to actual conditions to address temporary special operating scenarios. Manual adjustments will leave operation records and be stored in the blockchain for evidence preservation, ensuring the traceability of topology adjustments. The manually adjusted model also needs to undergo a verification process to ensure it is error-free before being put into use, avoiding model errors caused by human intervention.

[0102] For example, the dynamic carbon flow tracing and factor calculation engine supports switching between multiple calculation modes. In addition to the default real-time calculation mode, it also supports historical backtracking and simulation modes. The historical backtracking mode can retrieve historical data to calculate the carbon emission factor at a specific time point in the past, used for historical data verification and retrospective analysis. The simulation mode allows input of hypothetical parameters such as power output, topology, and load levels to simulate and calculate the corresponding carbon flow distribution and carbon emission factor, used for scheme evaluation and predictive analysis. These multiple calculation modes expand the engine's application scenarios and can meet different types of computing needs.

[0103] Specifically, the collaborative accounting and application service layer supports customized report generation. Users can select the report's content, statistical dimensions, and display format according to their needs, and the system automatically generates customized accounting reports to meet the individual needs of different users. The service layer also has data visualization capabilities, displaying the spatial distribution and temporal trends of carbon emission factors through charts, maps, and other forms, intuitively presenting the dynamic characteristics of carbon flow and improving data readability.

[0104] It should be noted that the entire system complies with relevant power industry standards and carbon emission accounting standards. The accounting methods, data formats, and report content all meet general specifications, ensuring the standardization and comparability of the accounting results. The system can interface with existing power dispatching systems, marketing systems, carbon management systems, and other external systems to achieve data interconnection, avoid redundant construction, and improve the overall efficiency of information technology utilization.

[0105] For example, in actual deployment, the system can be deployed in either a centralized or distributed manner. For smaller regional power grids, a centralized deployment can be used, with all modules located at the central dispatch node for easier management and maintenance. For larger, multi-regional power grids, a distributed deployment can be used, with corresponding data acquisition and computing nodes deployed in each region, and the central node performing aggregated calculations to improve computational 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.

[0106] Specifically, the system's reliability design incorporates multiple redundancy mechanisms. Critical modules and data are backed up, ensuring that a single device failure will not paralyze the entire system. The system features automatic failover capability; when the primary device fails, the backup device automatically takes over services, ensuring uninterrupted operation. The system also has degraded operation capability; when some modules fail, the remaining modules continue to operate normally, ensuring the availability of core functions, and all functions are restored after the fault is repaired.

[0107] It should be noted that this solution fully considers the safety requirements of power grid operation during the design process. All data acquisition and calculation will not affect the normal operation of the power grid. The acquisition module adopts a bypass acquisition method and will not intervene in the power grid's control loop. The calculation process is carried out on an independent server and will not interfere with the dispatching system. The system has comprehensive network security protection measures, meets the network security level requirements of the power industry, and can resist common network attacks, ensuring the security of the system and data.

[0108] This invention also provides a multi-region, multi-voltage cascaded power carbon emission factor collaborative accounting system for implementing the multi-region, multi-voltage cascaded power carbon emission factor collaborative accounting method described above. The system includes: The multi-source heterogeneous data acquisition layer adopts a distributed acquisition architecture and is deployed at power grid nodes in various regions to synchronously acquire three types of core data and complete preprocessing and encrypted transmission. The regional voltage level cascaded topology modeling module is used to define carbon flow accounting nodes, construct a cascaded carbon flow network model with three-dimensional correlation between topological power and carbon flow, and support dynamic updates. The dynamic carbon flow tracking and factor calculation engine has a built-in collaborative accounting algorithm for performing carbon flow initialization, loss allocation and iterative solution, and outputting the instantaneous carbon emission factor of each node; The collaborative accounting and application service layer is used to release carbon emission factors to the public and provide carbon emission accounting and full-process traceability and evidence storage services for electricity consumption.

[0109] 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 collaborative accounting method for electricity carbon emission factors in a multi-regional, multi-voltage cascade manner, characterized in that, include: The system synchronously collects power generation data, network topology data, and switching power data. It performs preprocessing on the collected data, including time alignment, outlier cleaning, and format standardization, and outputs the preprocessed data through an encrypted transmission protocol. Define carbon flow accounting nodes, and use graph theory algorithms to construct the electrical topology of node branches in multiple regions and at multiple voltage levels, forming a cascaded carbon flow network model with three-dimensional correlation of topological power carbon flow. Based on the principle of proportional sharing and the cascade loss allocation operator, perform node carbon potential initialization, cascade loss carbon emission allocation, multi-regional collaborative power flow carbon flow calculation, and iterative solution of node carbon emission factors to obtain the instantaneous carbon emission factors of each carbon flow accounting node. Release carbon emission factors, respond to user requests to complete electricity carbon emission accounting, trace and record the entire accounting process, and perform collaborative accounting of electricity carbon emission factors across multiple regions and voltage levels.

2. The method for collaborative accounting of power carbon emission factors in multi-regional and multi-voltage cascaded systems according to claim 1, characterized in that, The synchronous acquisition of power generation side data, network topology data, and switching power data includes: Collect generation-side data covering various types of generator sets, including real-time active power, nameplate parameters, generation type, real-time fuel consumption data, and carbon emission intensity of the generator sets; Collect network topology data covering all voltage levels, including node connection relationships, line parameters, transformer parameters, and bus parameters; Collect the exchange power data corresponding to the inter-regional tie lines, including bidirectional active power values, power trading contract identifiers, tie line loss data, tie line operating status, and corresponding metering point information.

3. The method for collaborative accounting of power carbon emission factors in multi-regional and multi-voltage cascaded systems according to claim 2, characterized in that, The preprocessing of the collected data, including time alignment, outlier cleaning, and format standardization, includes: Based on the set synchronization window, time alignment is performed on multi-source data to unify the time dimension of the data; Outlier data is removed using statistical criteria, and missing data is supplemented using interpolation or the average of adjacent windows. Convert all data into a unified, standardized storage format; The statistical criteria are data screening criteria for identifying outliers based on the data mean and standard deviation.

4. The method for collaborative accounting of power carbon emission factors in multi-regional and multi-voltage cascaded systems according to claim 1, characterized in that, The defined carbon flow accounting nodes employ graph theory algorithms to construct multi-region, multi-voltage-level node branch electrical topology diagrams, forming a cascaded carbon flow network model with three-dimensional correlation of topological power and carbon flow. Based on the proportional sharing principle and cascade loss allocation operators, node carbon potential initialization, cascade loss carbon emission allocation, multi-regional collaborative power flow carbon flow calculation, and iterative solution of node carbon emission factors are performed to obtain the instantaneous carbon emission factors of each carbon flow accounting node, including: Define carbon flow accounting nodes and assign them unique identifiers to construct a cascaded carbon flow network model with multiple regions and voltage levels; Perform node carbon potential initialization to determine the initial carbon injection amount for each node; The cascade loss carbon emission allocation is performed, and the carbon emissions corresponding to the transmission loss are allocated to the corresponding nodes according to the set rules; an equation system is established based on the principle of carbon flow conservation, and the instantaneous carbon emission factor of each carbon flow accounting node is obtained by iterative solution.

5. The method for collaborative accounting of power carbon emission factors in multi-regional and multi-voltage cascaded systems according to claim 4, characterized in that, The process of defining carbon flow accounting nodes and assigning them unique identifiers, and constructing a cascaded carbon flow network model with multiple regions and voltage levels, includes: Define the busbars of a specific voltage level within a specific area as carbon flow accounting nodes, and assign a unique identifier code to each node; A graph theory algorithm is used to construct the electrical topology graph of nodes and branches, clarifying the cascade relationship of each node and the connection relationship of branches; By associating power generation data, exchange power data, and topology, a three-dimensional correlation model of topological power carbon flow is formed. The topology model is updated according to a set period, and model reconstruction is automatically triggered when a major topology adjustment is detected; the cascading relationship is a hierarchical connection relationship established by nodes of different voltage levels through voltage regulating transformers.

6. The method for collaborative accounting of power carbon emission factors in multi-regional and multi-voltage cascaded systems according to claim 4, characterized in that, The execution of cascaded loss carbon emission allocation, which distributes the carbon emissions corresponding to transmission losses to the corresponding nodes according to a set rule, includes: For transformer branches, the carbon flow rate of low-voltage side nodes is calculated using the rule that all carbon emissions from losses are distributed to the low-voltage side. For multi-level voltage cascaded scenarios, losses and carbon emissions are distributed step by step according to the voltage level from high to low. For inter-regional link branches, all carbon emissions corresponding to link losses are allocated to the corresponding nodes in the receiving region; the carbon flow rate is the amount of carbon emissions flowing through the nodes per unit time.

7. The method for collaborative accounting of power carbon emission factors in multi-regional and multi-voltage cascaded systems according to claim 4, characterized in that, The equation system established based on the principle of carbon flow conservation, and the instantaneous carbon emission factor of each carbon flow accounting node obtained by iterative solution, includes: Based on the principle of carbon flow conservation, a carbon flow conservation equation is established for each carbon flow accounting node, and a system of linear equations for the entire network is constructed. An iterative method was used to solve the linear equation system, and the carbon flux rate of each node was updated successively during the iteration process; After iterative convergence, the instantaneous carbon emission factor of each carbon flow accounting node is calculated; the carbon flow conservation principle is that the total carbon flow rate of the inflow node is equal to the total carbon flow rate of the outflow node.

8. The method for collaborative accounting of power carbon emission factors in multi-regional and multi-voltage cascaded systems according to claim 1, characterized in that, The process of publishing carbon emission factors, responding to user requests to complete electricity consumption carbon emission accounting, and tracing and storing evidence throughout the entire accounting process includes: The calculated carbon emission factors are organized and stored in a standardized format and then released to the public through the application programming interface. Receive regional voltage level information and electricity consumption information submitted by users, and match the corresponding carbon emission factors to calculate the total carbon emissions from electricity consumption; Based on the consortium blockchain architecture, information throughout the entire accounting process is stored and a unique storage identifier is generated for information retrieval.

9. The method for collaborative accounting of power carbon emission factors in multi-regional and multi-voltage cascaded systems according to claim 1, characterized in that, The method uses a set time period as a synchronization window to cyclically execute the entire process of data acquisition and preprocessing, cascaded carbon flow network model update, dynamic carbon flow calculation, factor release and accounting and storage, thereby realizing the dynamic updating of carbon emission factors.

10. A multi-regional, multi-voltage cascaded power carbon emission factor collaborative accounting system, characterized in that, The system is used to implement the collaborative accounting method for multi-regional, multi-voltage cascaded power carbon emission factors according to any one of claims 1 to 9, the system comprising: The multi-source heterogeneous data acquisition layer adopts a distributed acquisition architecture and is deployed at power grid nodes in various regions to synchronously acquire three types of core data and complete preprocessing and encrypted transmission. The regional voltage level cascaded topology modeling module is used to define carbon flow accounting nodes, construct a cascaded carbon flow network model with three-dimensional correlation between topological power and carbon flow, and support dynamic updates. The dynamic carbon flow tracking and factor calculation engine has a built-in collaborative accounting algorithm for performing carbon flow initialization, loss allocation and iterative solution, and outputting the instantaneous carbon emission factor of each node; The collaborative accounting and application service layer is used to release carbon emission factors to the public and provide carbon emission accounting and full-process traceability and evidence storage services for electricity consumption.

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