A carbon accounting data quality gating method, system, device

Abstract

The application discloses a carbon accounting data quality gating method, system and device, and relates to the technical field of micro-grid energy metering and carbon emission accounting data processing; the method configures energy metering mode and direction semantic coefficient for the metering point in the closed boundary of the vehicle depot in a time window, collects data and performs direction semantic correction, time alignment and offset determination; calculates the collection weight based on the duration of the vehicle in the closed boundary to obtain the regenerative collection energy of the vehicle; aggregates the energy flow into the total energy on the input side and the total energy on the output side containing the regenerative collection energy, establishes an energy closure equation to calculate the closure relative error; generates a gating mark and a reason code according to the determination result, the data missing state and the closure relative error; if the gating is qualified, the data is allowed to enter the carbon accounting account, and if the gating is unqualified, the data is isolated and frozen for backfilling and recalculation. The application realizes multi-source energy closure consistency verification, and blocks unverifiable data from entering the carbon account book from the source.

Description

Technical Field

[0001] This invention relates to the field of microgrid energy metering and carbon emission accounting data processing technology, specifically to a carbon accounting data quality gating method, system, and device. Background Technology

[0002] The statements in this section are provided only as background information in connection with this disclosure and may not constitute prior art.

[0003] Intelligent Rail Transit (ART) depots typically form user-side photovoltaic-storage-charging-feeder or main meter microgrids, with frequent distribution and conversion of power flow among multiple devices. With the advancement of dual carbon targets, carbon accounting for such complex microgrids has become particularly important. Existing depot carbon accounting practices mostly rely on main meters or single metering sources to calculate electricity consumption, multiplying it by the grid emission factor to obtain carbon emissions.

[0004] However, existing carbon accounting methods have the following significant drawbacks in the context of intelligent rail transit depots:

[0005] Inconsistent statistical standards and unverifiable issues arise from multiple data sources. Intelligent rail depots not only contain on-site equipment such as photovoltaic systems, energy storage, charging piles, and auxiliary equipment loads, but also dynamically operating vehicle-side regenerative braking energy. Due to the presence of multiple metering sources and diverse data calibers, relying solely on single-table statistics easily leads to inconsistencies in statistical standards, data reconciliation difficulties, and challenges in auditing and recalculation.

[0006] The "spatiotemporal reconciliation black hole" caused by vehicle regenerative energy. Regenerative braking energy is typical in rail transit scenarios and is usually obtained by statistics or measurement from the vehicle operation side. However, this regenerative energy and the metering from the depot power supply and distribution side are often not included in the closed reconciliation within the same time window, which can easily lead to an unverifiable state where "there is regenerative energy output on the vehicle side, but not reflected on the depot side" or "the depot side reflects energy input, but the source cannot be explained".

[0007] The high costs and compliance audit risks associated with cloud-based verification. Existing solutions often place anomaly identification and data verification logic on cloud-based carbon ledger platforms or rely on manual verification. This not only leads to data delays and increased labor costs, but also poses a compliance audit risk of "entering the ledger first and correcting errors later" when forming the carbon ledger and reporting it externally.

[0008] Therefore, there is an urgent need for a multi-source metering energy closure consistency verification method for intelligent rail transit depots, which can prevent unverifiable data from entering the carbon accounting and reporting chain from the source. Summary of the Invention

[0009] The purpose of this invention is:

[0010] In view of the above-mentioned deficiencies in the existing technology, the purpose of this invention is to provide a carbon accounting data quality gating method and system for a photovoltaic-storage-charging-discharging microgrid in an intelligent rail transit vehicle depot, aiming to solve the following technical problems:

[0011] 1. How to perform unified multi-source metering of photovoltaic, energy storage, charging piles, feeders or main meters, and dynamic vehicle regenerative braking energy in the intelligent rail vehicle depot within the same time window, and form a reconcilable energy closure verification.

[0012] 2. How to scientifically generate closure errors and form gating tags that can be used for carbon accounting entries and reporting, so as to avoid inconsistencies and unverifiable risks caused by relying on single tables or single-source data;

[0013] 3. How to perform time alignment, closure error calculation and gating decision-making at the edge node side in advance, and output qualified data and data to be corrected, thereby reducing cloud dependence and manual review costs, and blocking the compliance risks of "entering accounts first and correcting errors later".

[0014] The technical solution of the present invention is as follows:

[0015] A carbon accounting data quality gating method includes:

[0016] Within a predetermined time window, a set of metering points belonging to the closed boundary of the intelligent rail vehicle depot is determined, and each metering point in the set of metering points is configured with a quantization method and a directional semantic coefficient.

[0017] Data from each measurement point in the measurement point set is collected within the time window. The energy within the window is calculated according to the energy conversion method. Directional semantic correction is performed in combination with the directional semantic coefficient. Time alignment and offset determination are performed and the determination results are recorded. At the same time, the data missing status is recorded.

[0018] The regenerative braking energy of each vehicle in the vehicle set associated with the intelligent rail vehicle depot within the time window is obtained. The vehicle aggregation weight is calculated based on the duration of each vehicle in the vehicle set within the closed boundary of the intelligent rail vehicle depot, so as to obtain the vehicle regenerative aggregation energy aggregated to the closed boundary of the intelligent rail vehicle depot.

[0019] The energy flow within the closed boundary of the intelligent rail vehicle depot is aggregated into total input energy and total output energy, wherein the total input energy includes the energy collected by vehicle regeneration; based on the total input energy, the total output energy, and the calculated loss energy, an energy closure equation is established and the energy closure residual and closure relative error are calculated;

[0020] Based on the determination results of the time alignment and offset, the data missing status, and the relative closure error, a gating tag and a reason code are generated.

[0021] Based on the gating flag, the output is split: when the gating flag indicates that the data packet is qualified, a qualified data packet is output and allowed to enter the carbon accounting and reporting link; when the gating flag indicates that the data packet is unqualified, a data packet to be corrected is output and the data packet to be corrected is frozen and isolated. The data packet to be corrected carries the reason code, which is used to indicate the missing reason or failure reason for remediation and recalculation.

[0022] Furthermore, the energy conversion method includes differential energy conversion and integral energy conversion;

[0023] When the energy conversion method is differential energy conversion, the metering terminal provides the cumulative energy reading, and the energy within the window is obtained by the difference between the cumulative energy readings at the boundary of the time window;

[0024] When the energy conversion method is integral energy conversion, the metering terminal provides instantaneous power sampling, and the energy within the window is obtained by discretely integrating the power within the time window;

[0025] The step of performing directional semantic correction in conjunction with the directional semantic coefficient includes: fixing the directional semantic coefficient for each metering point in the metering point set, wherein the directional semantic coefficient is used to unify the positive and negative directions of different metering devices to a convention that entering a closed boundary is positive and leaving a closed boundary is negative, and defining the electrical energy within the window after unifying the semantics as the product of the energy within the window and the corresponding directional semantic coefficient.

[0026] Furthermore, the step of performing time alignment and offset determination and recording the determination result includes:

[0027] For each meter in the set of metering points, the acquisition time offset is calculated, whereby the acquisition time offset represents the estimated offset of the metering point data timestamp relative to the boundary of the time window.

[0028] When the energy conversion method is the differential energy conversion method, the acquisition time offset is the median of the difference between the reading timestamp near the start of the time window and the start time of the time window, and the difference between the reading timestamp near the end of the time window and the end time of the time window.

[0029] When the energy conversion method is the integral energy conversion method, the acquisition time offset is the median of the difference between the power sampling timestamp and the sampling time of the grid within the window;

[0030] The absolute value of the acquisition time offset of each measurement point is compared with a preset time offset threshold. If there is a measurement point whose absolute value is greater than the time offset threshold, it is determined that the corresponding time window has failed to align, and the determination result is recorded as a hard failure state.

[0031] Further, the step of calculating the vehicle aggregation weight based on the duration of each vehicle in the vehicle set within the closed boundary of the intelligent rail transit depot, to obtain the vehicle regeneration aggregation energy aggregated to the closed boundary of the intelligent rail transit depot, includes:

[0032] The vehicle aggregation weight is calculated as the ratio of the duration during which a target vehicle in the vehicle set is identified as being within the closed boundary of the intelligent rail vehicle segment within the time window to the length of the time window.

[0033] The product of the regenerative braking energy of each vehicle and its corresponding vehicle aggregation weight is summed to obtain the vehicle regenerative aggregation energy that is aggregated to the closed boundary of the intelligent rail vehicle section within the time window.

[0034] When the regenerative braking energy of each vehicle is missing, making it impossible to calculate the regenerative energy collected by the vehicle, the data missing state is recorded as a hard missing state.

[0035] Further, the step of establishing an energy closure equation and calculating the energy closure residual and closure relative error based on the total energy on the input side, the total energy on the output side, and the calculated energy loss includes:

[0036] The total energy on the input side is defined as the sum of the electrical energy within the window after unifying the semantics of each metering point in the subset of input-side metering points belonging to the closed boundary in the metering point set, and the energy collected by the vehicle regeneration.

[0037] The total output energy is defined as the sum of the window energy of each metering point in the subset of output-side metering points that are outside the closed boundary, after unifying the semantics.

[0038] The energy loss is defined as the product of the total energy on the input side and a preset energy loss ratio coefficient.

[0039] The difference between the total energy on the input side and the total energy on the output side plus the energy loss is calculated and used as the energy closure residual.

[0040] The ratio of the absolute value of the energy closure residual and the sum of the total energy on the input side and the zero-prevention quantity is calculated as the dimensionless closure relative error, wherein the zero-prevention quantity is used to prevent the denominator of the ratio from being zero.

[0041] Further, the step of generating a gating marker based on the determination result of the time alignment and offset, the data missing state, and the relative closure error includes:

[0042] The data missing state includes a hard missing state that makes it impossible to obtain closed input items including the vehicle regeneration and collection energy; the determination result includes a hard failure state that causes the time alignment and offset determination to fail.

[0043] When the hard missing state or the hard failure state occurs, a gating flag indicating non-compliance is generated;

[0044] When there are no hard missing states or hard failure states, and the relative closure error is less than or equal to a preset closure error threshold, a gating flag indicating qualification is generated.

[0045] When neither the hard missing state nor the hard failure state exists, and the relative closure error is greater than the closure error threshold, a gate flag indicating non-compliance is generated.

[0046] Furthermore, the logic for generating the reason code includes:

[0047] When the gate control indicator is qualified, a reason code indicating successful closure is generated;

[0048] When the hard failure state occurs, a reason code indicating that the time offset has exceeded the limit is generated;

[0049] When data for a necessary measurement point is missing, a reason code indicating the measurement loss is generated;

[0050] When the vehicle's regenerative energy is insufficient, a reason code indicating the lack of regenerative data is generated;

[0051] When the relative closure error is greater than the closure error threshold, a reason code indicating closure failure is generated;

[0052] The qualified data packet and the data packet to be corrected both carry a time window identifier, as well as the total energy on the input side, the total energy on the output side, the energy loss, the energy collected by the vehicle regeneration, the energy closure residual, the closure relative error, the gating mark, and the cause code within the corresponding time window.

[0053] Furthermore, the step of allowing the qualified data packet to enter the carbon accounting and reporting link when the gating flag indicates that it is qualified includes:

[0054] Carbon accounting entries and reporting are performed only when the qualified data packet is received;

[0055] Obtain a pre-configured subset of power grid purchase metering points belonging to the set of metering points, and calculate the power grid purchase energy based on the sum of the in-window electrical energy after unifying the semantics of each metering point in the subset of power grid purchase metering points;

[0056] Obtain the grid purchase carbon factor carrying a version number or effective range identifier from the carbon factor library;

[0057] The product of the electricity purchased from the power grid and the carbon factor of the electricity purchased from the power grid is calculated to obtain the emissions within the window for accounting and reporting.

[0058] This invention also proposes a carbon accounting data quality gating system, including a metering terminal layer, a vehicle renewable energy data interface, an edge verification node, and a cloud carbon ledger platform that are interconnected.

[0059] The metering terminal layer is used to collect and provide the cumulative energy readings or instantaneous power samples and their timestamps for each metering point within the closed boundary of the intelligent rail vehicle depot within a time window.

[0060] The vehicle regenerative energy data interface is used to obtain the regenerative braking energy of each vehicle in the set of vehicles associated with the intelligent rail vehicle depot within the time window and the depot-related events.

[0061] The edge verification node is used to configure the energy conversion method and directional semantic coefficient for each metering point within the time window, calculate the energy within the window, perform directional semantic correction, time alignment and offset determination, and record the determination results, while also recording the data missing status; calculate the vehicle aggregation weight based on the duration of each vehicle within the closed boundary, and obtain the vehicle regeneration aggregation energy aggregated to the closed boundary of the intelligent rail vehicle section; aggregate the energy flow within the closed boundary of the intelligent rail vehicle section into the total energy on the input side and the total energy on the output side, establish an energy closure equation based on the total energy on the input side, the total energy on the output side, and the calculated loss energy, and calculate the energy closure residual and closure relative error; and generate a gating mark and reason code according to the determination results, the data missing status, and the closure relative error.

[0062] The edge verification node is also used to output qualified data packets or data packets to be corrected based on the gating mark, and to freeze and isolate the data packets to be corrected.

[0063] The cloud-based carbon ledger platform is used to receive the qualified data packets and execute carbon accounting and reporting logic, as well as to isolate and store the data packets to be corrected to support recalculation based on the supplementary data.

[0064] The present invention also proposes an electronic device, comprising:

[0065] At least one processor; and a memory communicatively connected to said at least one processor;

[0066] The memory stores instructions that can be executed by the at least one processor, and the at least one processor executes the instructions stored in the memory to perform the method described above.

[0067] Compared with existing technologies, the advantages of this invention are:

[0068] 1. An innovative dynamic spatiotemporal aggregation model eliminates the unreconcilable blind spots caused by "vehicle regenerative energy." This invention breaks through the limitations of traditional local microgrids that only account for fixed meters. It creatively collects the duration of vehicles within the closed boundary of the intelligent rail depot to calculate the "vehicle aggregation weight," accurately extracting dynamic vehicle regenerative braking energy and incorporating it as an aggregation item into the closed input. This mechanism enables precise spatiotemporal reconciliation between "vehicle operation-side regenerative energy" and "depot power supply and distribution-side metering" within the same time window, greatly improving the verifiability and audit transparency of intelligent rail depot carbon accounting data.

[0069] 2. An energy closure consistency verification system with zero-prevention logic is constructed to prevent carbon asset compliance risks at the source. This invention constructs a rigorous energy closure equation by calculating the total input energy, total output energy, and energy loss after unifying semantics. Simultaneously, a dimensionless relative error for zero-prevention small-scale calculations is introduced to prevent algorithmic overflow risks during nighttime or outages when there is no input. By generating gating markers through the relative error and hard missing / failure states, unverifiable "dirty data" is prevented from entering the carbon ledger and external reporting links from the technical source, completely eliminating the audit and compliance risks caused by "entering the ledger first and correcting errors later."

[0070] 3. A pioneering edge-side pre-positioned quality gating and cause code tracking mechanism significantly reduces cloud and manual costs. This invention decentralizes time alignment determination, closure calculation, and gating decisions to the edge verification node side, and automatically splits qualified data packets and data packets to be corrected based on gating tags. Unqualified data is frozen and isolated, and the reasons for failure of the data to be corrected are clarified by generating multi-dimensional cause codes (such as time offset exceeding limits, missing measurement, closure failure, etc.). This mechanism allows system or maintenance personnel to quickly locate anomalies and perform recalculation, significantly reducing reliance on cloud computing power and the cost of subsequent manual verification and investigation. Attached Figure Description

[0071] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in the embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0072] Figure 1A flowchart of a carbon accounting data quality gating method;

[0073] Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0074] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0075] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0076] Example 1

[0077] To address the compliance issues arising from the current ART (Intelligent Rail Transit) depots' reliance on master meters or single metering sources for electricity consumption statistics, which leads to inconsistencies in statistical standards for data from multiple sources such as photovoltaic, energy storage, charging, and discharging, and difficulties in reconciling regenerative braking energy on the vehicle side, this embodiment provides a carbon accounting data quality gating method. The implementing entity can be an edge verification node (such as an edge gateway or local control server) deployed at the edge of the depot. This method includes the following steps:

[0078] This embodiment provides a carbon accounting data quality gating method for a photovoltaic-storage-charging-discharging microgrid in an intelligent rail transit depot. The executing entity can be an edge verification node (such as an edge gateway or a local control server) deployed at the edge of the depot. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps:

[0079] Step S1: Calibration Configuration; Within a predetermined time window, determine the set of metering points belonging to the closed boundary of the intelligent rail vehicle depot, and configure the quantization method and directional semantic coefficient for each metering point in the set of metering points.

[0080] Specifically, the time window is defined as .

[0081] in, Indicates the first The start time of each time window, in seconds; where This indicates the length of the time window, measured in seconds (s).

[0082] All metering devices (such as electricity meters, inverters, or PCS) belonging to the closed boundary of the depot are pre-configured at the edge node side as a set of metering points. .in, This represents the set of metering points within the closed boundary of this depot, derived from equipment ledgers and edge configurations. For each metering point... Solidified energy conversion method ,in This indicates the differential quantization method. This indicates the integration energy conversion method. In order to ensure that multi-source heterogeneous devices can be reconciled horizontally within the same time scale, the energy conversion method and physical flow of their data acquisition must be fixed in advance.

[0083] It should be noted that the above configuration remains unchanged within the effective period of a configuration version. If the configuration changes, the configuration version will be updated and the closure will be recalculated from the time window after the change, so as to avoid cross-version calculation and ensure audit traceability.

[0084] Step S2: Data Acquisition and Energy Conversion; Data of each measurement point in the measurement point set is acquired within the time window, the energy within the window is calculated according to the energy conversion method, and directional semantic correction is performed in combination with the directional semantic coefficient. Time alignment and offset determination are also performed and the determination results are recorded. At the same time, the data missing status is recorded.

[0085] In this embodiment, the energy transformation method includes differential energy transformation and integral energy transformation:

[0086] (1) When the energy conversion method is differential energy conversion method ( When the cumulative energy is stored, the metering terminal (such as an energy meter, an inverter that provides a cumulative energy storage value, or a PCS) provides the cumulative energy reading. The energy within the window is obtained by the difference between the cumulative energy readings at the boundaries of the time window. Its mathematical model is as follows:

[0087]

[0088] in, Indicates measurement point In the time window The electrical energy within, measured in kWh; of which and This represents the cumulative energy reading at the boundary of the time window, expressed in kWh.

[0089] (2) When the energy conversion method is integral energy conversion method ( When the power is measured, an instantaneous power sample is provided by a metering terminal (such as an auxiliary device that only provides a power curve). The energy within the window is obtained by discretely integrating the power within the time window. Its mathematical model is as follows:

[0090]

[0091] in, This indicates the sampling time of the grid within the window, in seconds; where This represents the sampling step size, in seconds (s); where The number of sampling points within the window and ;in This indicates the instantaneous power sampling provided by the metering terminal, in kW.

[0092] Furthermore, the step of performing directional semantic correction in conjunction with the directional semantic coefficients includes: solidifying the directional semantic coefficients for each measurement point in the set of measurement points. The directional semantic coefficient is used to unify the positive and negative directions of different metering devices to a convention where entering a closed boundary is positive and leaving a closed boundary is negative. The electrical energy within the window after unifying the semantics is defined as the product of the energy within the window and the corresponding directional semantic coefficient, that is:

[0093]

[0094] in, This represents the electrical energy within the window after unifying semantics, expressed in kWh.

[0095] In heterogeneous microgrids with multiple sources, the clocks of different devices often exhibit slight deviations. Therefore, the process of performing time alignment and offset determination and recording the determination results specifically includes: for each metering point in the metering point set, calculating the acquisition time offset. .in, This represents the estimated offset of the timestamp of the measurement point data relative to the window boundary, in seconds.

[0096] When using differential quantization, define When using integral quantization, define... .

[0097] in, This represents taking the median of a given finite set of values; Indicates the timestamp of the reading near the start of the window, in seconds; Indicates the timestamp of the reading near the end of the window, in seconds; This represents the power sampling timestamp, in seconds.

[0098] The absolute value of the acquisition time offset of each measurement point With respect to the preset time offset threshold (This represents the maximum allowed time offset, in seconds) A comparison is made. If there is a measurement point whose absolute value is greater than the time offset threshold, the corresponding time window is determined to have experienced time alignment failure, and the determination result is recorded as a hard failure state. Simultaneously, if any necessary measurement point is missing within the window, resulting in... If it cannot be calculated, its data missing state is recorded as a hard missing state.

[0099] Step S3: Regeneration and aggregation; Obtain the regenerative braking energy of each vehicle in the vehicle set associated with the intelligent rail vehicle depot within the time window, and calculate the vehicle aggregation weight based on the duration of each vehicle in the vehicle set within the closed boundary of the intelligent rail vehicle depot, so as to obtain the vehicle regenerative aggregation energy aggregated to the closed boundary of the intelligent rail vehicle depot.

[0100] In this embodiment, it should be noted that intelligent rail vehicles differ from conventional stationary equipment in that they possess dynamic spatiotemporal attributes for entering and exiting the depot. Traditional carbon accounting schemes often only focus on fixed meters, resulting in "regenerative braking energy output on the vehicle side, but not reflected on the depot side," thus creating an unverifiable carbon ledger black hole. This invention creatively introduces a dynamic aggregation model based on spatiotemporal residence characteristics:

[0101] Specifically, vehicle sets are captured through entry / exit events or charging authentication events. ,in Indicates time window The set of vehicles associated with this depot. Calculate the weight of the vehicle aggregation:

[0102]

[0103] in, Indicates the weight of vehicle aggregation; Indicates vehicle In the time window The duration identified as being within the closed boundary of the depot is measured in seconds.

[0104] The onboard statistical regenerative braking energy of each vehicle. The corresponding weighted products are summed to accurately extract the vehicle regeneration and aggregation energy belonging to the spatiotemporal boundary of this vehicle depot:

[0105]

[0106] in, Indicates time window The vehicle regenerative braking energy collected within the closed boundary of the depot, in kWh; Indicates vehicle In the time window The regenerative braking energy generated internally is measured in kWh. When this portion of regenerative energy is missing and cannot be calculated, the data loss state is also recorded as a hard loss state.

[0107] Step S4: Closed-loop calculation; aggregate the energy flow within the closed boundary of the intelligent rail vehicle depot into total input energy and total output energy, wherein the total input energy includes the energy collected by the vehicle regeneration; based on the total input energy, the total output energy, and the calculated loss energy, establish an energy closure equation and calculate the energy closure residual and closure relative error.

[0108] Specifically, an energy closure verification model incorporating vehicle regeneration terms is established:

[0109] The total energy on the input side is defined as: ;

[0110] The total energy on the output side is defined as: ;

[0111] The energy loss is defined as the ratio of the total input energy to a preset energy loss ratio coefficient. The product of: .

[0112] in, The unit is kWh; The unit is kWh; This represents the loss ratio coefficient, and its value range is... ; The unit is kWh.

[0113] Based on Kirchhoff's law of conservation of energy, calculate the energy closure residual:

[0114]

[0115] in, Indicates time window The energy closure residual is expressed in kWh.

[0116] Then, calculate the relative error of closure:

[0117]

[0118] in, It is dimensionless and is used to measure the relative deviation of the closure residual relative to the energy scale of the input side; This represents the zero-prevention term for the energy ratio (zero-prevention small quantity), with the unit being kWh. It originates from edge configuration and its physical significance lies in preventing overflow of division calculations or excessive false relative errors when the microgrid input energy is extremely small (or even 0) at night or during outages, thereby improving the robustness of the system.

[0119] Step S5: Gating determination; Based on the determination results of the time alignment and offset determination, the data missing status, and the relative closure error, generate a gating mark and a reason code.

[0120] Gating decisions are executed directly at the edge (instead of reporting all data to the cloud for review, which greatly reduces compliance risks and labor costs):

[0121] Define gated flags ,in This indicates that the application is qualified and allowed to proceed with carbon accounting and reporting. Indicates non-compliance and freezes / isolates the device. Defines the closure error threshold. ,in This indicates the upper limit of the allowable relative error of closure, and its range. .

[0122] When any of the aforementioned hard missing states that prevent input items from being retrieved, or hard failure states that fail to time alignment, occurs, a gate flag indicating non-compliance is directly generated (set). When there is no hard state and the relative error of closure. At that time, a gating flag indicating that the gate is qualified is generated (set). );like The same indication will be that it is unqualified (set). ).

[0123] At the same time, define the reason code. The data packets contain identifiers indicating the reasons for gating conclusions: OK is generated if gating is successful (indicating successful closure); TIME_OFFSET is generated if time alignment fails (indicating time offset exceeds limits); DATA_MISSING is generated if measurement is missing (indicating missing measurement); REG_MISSING is generated if regeneration is missing (indicating missing regeneration data); and CLOSE_FAIL is generated if error exceeds limits (indicating closure failure). Both successful and pending correction data packets encapsulate the time window identifier (wid), total energy for each item, residual, and reason code, ensuring 100% traceability and recalculation of the master ledger.

[0124] Step S6: Perform traffic splitting based on the gating flag; when the gating flag indicates that the data packet is qualified, output a qualified data packet and allow the qualified data packet to enter the carbon accounting and reporting link; when the gating flag indicates that the data packet is unqualified, output a data packet to be corrected and freeze and isolate the data packet to be corrected.

[0125] For qualified data packets, perform carbon accounting: obtain a pre-configured subset of grid electricity purchase metering points and calculate the grid electricity purchase energy. Obtain the grid purchase carbon factors from the carbon factor library, which carry version numbers or effective period identifiers. The product of the two is used to calculate the emissions inside the window. Incorporate it into the accounts and report it.

[0126] in, This represents the amount of electricity purchased from the power grid, expressed in kWh. The carbon factor for electricity purchased from the power grid is expressed in units of [unit missing]. ; Indicates the amount of emissions inside the window, in units of .

[0127] For data packets that need to be corrected, they are frozen in the local isolation area, and the aforementioned reason codes are used to accurately guide the operation and maintenance personnel to intervene and correct them, thus preventing the compliance and audit risks of "entering accounts first and then correcting errors".

[0128] To further verify the logical feasibility of this embodiment, let's take specific operating data as an example: Set a time window. Error threshold Loss coefficient Preventing small quantities kWh.

[0129] After edge node acquisition and correction, the following data was obtained: 380 kWh of electricity purchased from the grid inside the window, 120 kWh from photovoltaic power, and 60 kWh from energy storage discharge (attributed to the input side); 520 kWh of charging pile output, 40 kWh of energy storage charging, and 25 kWh of auxiliary equipment load (attributed to the output side). Meanwhile, both intelligent rail vehicles remained inside the window for 450 seconds each (weighted). The vehicles generate 40 kWh and 20 kWh of regenerative energy respectively. The calculated regenerative energy collected by the vehicles is... kWh.

[0130] Based on this calculation, the total energy on the input side is... kWh; Total energy on the output side kWh; energy loss kWh. Closure residual kWh.

[0131] Then, the relative error of closure can be obtained. .because If there are no hard defects, the system will automatically generate a gated flag of 1, a reason code of OK, and calculate the carbon emissions for the current window. Reporting of entries is permitted.

[0132] Example 2

[0133] To implement the method described in Embodiment 1, this embodiment provides a carbon accounting data quality gating system. This system, through an "edge-cloud" collaborative architecture, prevents unverifiable data from entering the carbon accounting and reporting chain at the source, thereby reducing compliance risks.

[0134] The system includes interconnected metering terminal layers, vehicle renewable energy data interfaces, edge verification nodes, and a cloud-based carbon ledger platform.

[0135] 1. Metering terminal layer

[0136] The metering terminal layer is deployed on the power supply and distribution side of the intelligent rail vehicle depot. It is used to collect and provide the cumulative energy readings (for differential energy measurement devices, such as energy meters and inverters) or instantaneous power sampling (for integral energy measurement devices, such as auxiliary loads) of each metering point within the closed boundary of the intelligent rail vehicle depot within a time window, and their corresponding timestamps.

[0137] 2. Vehicle Regenerative Energy Data Interface

[0138] The vehicle regenerative energy data interface is connected to the vehicle operation side system or the vehicle-to-ground wireless communication network. It is used to obtain the onboard statistical regenerative braking energy of each vehicle in the vehicle set associated with the intelligent rail vehicle depot within the time window, and to capture depot entry and exit events or charging authentication and other depot-related events, so as to provide spatiotemporal data support for calculating vehicle aggregation weights.

[0139] 3. Edge verification node

[0140] The edge verification node is deployed at the edge of the vehicle depot (such as a local intelligent gateway or station server) to perform data quality gating decisions before accounting, reducing reliance on the cloud. The edge verification node includes at least a time alignment unit, a closed-loop calculation unit, and a gating unit.

[0141] Time alignment unit: Used to configure the energy conversion method and direction semantic coefficient for each measurement point within the time window, calculate the energy within the window and perform direction semantic correction, as well as perform time alignment and offset determination and record the determination results, and record the data missing status.

[0142] Closed-loop calculation unit: used to calculate the vehicle aggregation weight based on the duration of each vehicle within the closed boundary, to obtain the vehicle regeneration aggregation energy aggregated to the closed boundary of the intelligent rail vehicle depot; to aggregate the energy flow within the closed boundary of the intelligent rail vehicle depot into the total input energy and the total output energy; to establish an energy closure equation based on the total input energy, the total output energy, and the calculated loss energy, and to calculate the energy closure residual and the closure relative error.

[0143] Gating unit: used to generate gating flags and cause codes based on the judgment result, the data missing state and the relative error of closure; and to output qualified data packets or data packets to be corrected based on the gating flags, and freeze and isolate the data packets to be corrected.

[0144] 4. Cloud-based carbon ledger platform

[0145] The cloud-based carbon ledger platform is deployed on a cloud server and is used to receive the qualified data packets and execute the carbon accounting and reporting logic (i.e., multiplying the electricity purchased from the grid by the carbon factor of the electricity purchased from the grid to form the emissions). Simultaneously, the cloud-based carbon ledger platform is also used to isolate and store the data packets to be corrected. By parsing the reason codes carried in the data packets, it supports maintenance personnel or automated scripts to recalculate based on the supplemented data (i.e., after missing data such as vehicle renewable energy is supplemented, the same time window is recalculated to form new records that can be entered).

[0146] Example 3

[0147] Based on the same technical concept, embodiments of the present invention also provide an electronic device that can implement the carbon accounting data quality gating method flow provided in the above embodiments of the present invention. In one embodiment, the electronic device can be a server, a terminal device, or other electronic devices. Figure 2 As shown, the electronic device may include:

[0148] At least one processor and a memory connected to the at least one processor. In this embodiment of the invention, the specific connection medium between the processor and the memory is not limited. Figure 2 The example used is the connection between the processor and memory via a bus. The bus... Figure 2 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. Buses can be divided into address buses, data buses, control buses, etc., but for ease of representation, [the specific bus type is not shown here]. Figure 2 The processor is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, a processor can also be called a controller; there are no restrictions on the name.

[0149] In this embodiment of the invention, the memory stores instructions executable by at least one processor. By executing the instructions stored in the memory, the at least one processor can perform a carbon accounting data quality gating method as described above. The processor can implement... Figure 2 The functions of each module in the device shown.

[0150] The processor is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory and calling data stored in memory, it can monitor the device's various functions and process data, thereby enabling overall monitoring of the device.

[0151] In an alternative design, the processor may include one or more processing units. The processor may integrate an application processor and a modem processor, wherein the application processor primarily handles the operating system, user interface, and applications, while the modem processor primarily handles wireless communication. It is understood that the modem processor may also not be integrated into the processor. In some embodiments, the processor and memory may be implemented on the same chip; in some embodiments, they may also be implemented separately on separate chips.

[0152] The processor can be a general-purpose processor, such as a CPU, digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the carbon accounting data quality gating method disclosed in the embodiments of this invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0153] Memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory can include at least one type of storage medium, such as flash memory, hard disk, multimedia cards, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), and electrically erasable programmable read-only memory (EPROM). Only memory (EEPROM), magnetic storage, magnetic disks, optical disks, etc. A memory is any other medium capable of carrying or storing desired program code in the form of instructions or data structures, and accessible by a computer, but is not limited thereto. The memory in embodiments of this invention can also be a circuit or any other device capable of performing storage functions for storing program instructions and / or data.

[0154] By designing and programming the processor, the code corresponding to the carbon accounting data quality gating method described in the foregoing embodiments can be embedded into the chip, enabling the chip to execute the steps of the method described in the foregoing embodiments during runtime. How to design and program the processor is a technique well-known to those skilled in the art and will not be elaborated upon here.

[0155] The embodiments described above merely illustrate specific implementation methods of this application, and while the descriptions are detailed and specific, they should not be construed as limiting the scope of protection of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the technical solution of this application, and these modifications and improvements all fall within the scope of protection of this application.

[0156] This background section is provided to generally present the context of the invention. The work of the currently named inventors, the work to the extent described in this background section, and aspects of this section that did not constitute prior art at the time of application are neither expressly nor impliedly acknowledged as prior art to the invention.

Claims

1. A method for gating the quality of carbon accounting data, characterized in that, include: Within a predetermined time window, a set of metering points belonging to the closed boundary of the intelligent rail vehicle depot is determined, and each metering point in the set of metering points is configured with a quantization method and a directional semantic coefficient. Data from each measurement point in the measurement point set is collected within the time window. The energy within the window is calculated according to the energy conversion method. Directional semantic correction is performed in combination with the directional semantic coefficient. Time alignment and offset determination are performed and the determination results are recorded. At the same time, the data missing status is recorded. The regenerative braking energy of each vehicle in the vehicle set associated with the intelligent rail vehicle depot within the time window is obtained. The vehicle aggregation weight is calculated based on the duration of each vehicle in the vehicle set within the closed boundary of the intelligent rail vehicle depot, so as to obtain the vehicle regenerative aggregation energy aggregated to the closed boundary of the intelligent rail vehicle depot. The energy flow within the closed boundary of the intelligent rail vehicle depot is aggregated into total input energy and total output energy, wherein the total input energy includes the energy collected by vehicle regeneration; based on the total input energy, the total output energy, and the calculated loss energy, an energy closure equation is established and the energy closure residual and closure relative error are calculated; Based on the determination results of the time alignment and offset, the data missing status, and the relative closure error, a gating tag and a reason code are generated. Based on the gating mark, the output is split: when the gating mark indicates that it is qualified, a qualified data packet is output and the qualified data packet is allowed to enter the carbon accounting and reporting link; When the gating flag indicates that the condition is not met, a data packet to be corrected is output and the data packet to be corrected is frozen and isolated. The data packet to be corrected carries the reason code, which is used to indicate the missing reason or the reason for failure so that it can be replenished and recalculated.

2. The carbon accounting data quality gating method according to claim 1, characterized in that, The energy conversion methods include differential energy conversion and integral energy conversion. When the energy conversion method is differential energy conversion, the metering terminal provides the cumulative energy reading, and the energy within the window is obtained by the difference between the cumulative energy readings at the boundary of the time window; When the energy conversion method is integral energy conversion, the metering terminal provides instantaneous power sampling, and the energy within the window is obtained by discretely integrating the power within the time window; The step of performing directional semantic correction in conjunction with the directional semantic coefficient includes: fixing the directional semantic coefficient for each metering point in the metering point set, wherein the directional semantic coefficient is used to unify the positive and negative directions of different metering devices to a convention that entering a closed boundary is positive and leaving a closed boundary is negative, and defining the electrical energy within the window after unifying the semantics as the product of the energy within the window and the corresponding directional semantic coefficient.

3. The carbon accounting data quality gating method according to claim 2, characterized in that, The process of performing time alignment and offset determination and recording the determination results includes: For each meter in the set of metering points, the acquisition time offset is calculated, whereby the acquisition time offset represents the estimated offset of the metering point data timestamp relative to the boundary of the time window. When the energy conversion method is the differential energy conversion method, the acquisition time offset is the median of the difference between the reading timestamp near the start of the time window and the start time of the time window, and the difference between the reading timestamp near the end of the time window and the end time of the time window. When the energy conversion method is the integral energy conversion method, the acquisition time offset is the median of the difference between the power sampling timestamp and the sampling time of the grid within the window; The absolute value of the acquisition time offset of each measurement point is compared with a preset time offset threshold. If there is a measurement point whose absolute value is greater than the time offset threshold, it is determined that the corresponding time window has failed to align, and the determination result is recorded as a hard failure state.

4. The carbon accounting data quality gating method according to claim 1, characterized in that, The calculation of vehicle aggregation weights based on the duration of each vehicle in the vehicle set within the closed boundary of the intelligent rail transit depot, to obtain the vehicle regeneration aggregation energy aggregated to the closed boundary of the intelligent rail transit depot, includes: The vehicle aggregation weight is calculated as the ratio of the duration during which a target vehicle in the vehicle set is identified as being within the closed boundary of the intelligent rail vehicle segment within the time window to the length of the time window. The product of the regenerative braking energy of each vehicle and its corresponding vehicle aggregation weight is summed to obtain the vehicle regenerative aggregation energy that is aggregated to the closed boundary of the intelligent rail vehicle section within the time window. When the regenerative braking energy of each vehicle is missing, making it impossible to calculate the regenerative energy collected by the vehicle, the data missing state is recorded as a hard missing state.

5. The carbon accounting data quality gating method according to claim 2, characterized in that, The process of establishing an energy closure equation and calculating the energy closure residual and closure relative error based on the total energy on the input side, the total energy on the output side, and the calculated energy loss includes: The total energy on the input side is defined as the sum of the electrical energy within the window after unifying the semantics of each metering point in the subset of input-side metering points belonging to the closed boundary in the metering point set, and the energy collected by the vehicle regeneration. The total output energy is defined as the sum of the window energy of each metering point in the subset of output-side metering points that are outside the closed boundary, after unifying the semantics. The energy loss is defined as the product of the total energy on the input side and a preset energy loss ratio coefficient. The difference between the total energy on the input side and the total energy on the output side plus the energy loss is calculated and used as the energy closure residual. The ratio of the absolute value of the energy closure residual and the sum of the total energy on the input side and the zero-prevention quantity is calculated as the dimensionless closure relative error, wherein the zero-prevention quantity is used to prevent the denominator of the ratio from being zero.

6. The carbon accounting data quality gating method according to claim 1, characterized in that, The step of generating a gating marker based on the determination result of the time alignment and offset, the data missing state, and the relative closure error includes: The data missing state includes a hard missing state that makes it impossible to obtain closed input items including the vehicle regeneration and collection energy; the determination result includes a hard failure state that causes the time alignment and offset determination to fail. When the hard missing state or the hard failure state occurs, a gating flag indicating non-compliance is generated; When there are no hard missing states or hard failure states, and the relative closure error is less than or equal to a preset closure error threshold, a gating flag indicating qualification is generated. When neither the hard missing state nor the hard failure state exists, and the relative closure error is greater than the closure error threshold, a gate flag indicating non-compliance is generated.

7. A carbon accounting data quality gating method according to claim 6, characterized in that, The reason code generation logic includes: When the gate control indicator is qualified, a reason code indicating successful closure is generated; When the hard failure state occurs, a reason code indicating that the time offset has exceeded the limit is generated; When data for a necessary measurement point is missing, a reason code indicating the measurement loss is generated; When the vehicle's regenerative energy is insufficient, a reason code indicating the lack of regenerative data is generated; When the relative closure error is greater than the closure error threshold, a reason code indicating closure failure is generated; The qualified data packet and the data packet to be corrected both carry a time window identifier, as well as the total energy on the input side, the total energy on the output side, the energy loss, the energy collected by the vehicle regeneration, the energy closure residual, the closure relative error, the gating mark, and the cause code within the corresponding time window.

8. A carbon accounting data quality gating method according to claim 2, characterized in that, When the gating flag indicates that the data packet is qualified, allowing the qualified data packet to enter the carbon accounting and reporting link includes: Carbon accounting entries and reporting are performed only when the qualified data packet is received; Obtain a pre-configured subset of power grid purchase metering points belonging to the set of metering points, and calculate the power grid purchase energy based on the sum of the in-window electrical energy after unifying the semantics of each metering point in the subset of power grid purchase metering points; Obtain the grid purchase carbon factor carrying a version number or effective range identifier from the carbon factor library; The product of the electricity purchased from the power grid and the carbon factor of the electricity purchased from the power grid is calculated to obtain the emissions within the window for accounting and reporting.

9. A carbon accounting data quality gating system, characterized in that, This includes interconnected metering terminal layers, vehicle renewable energy data interfaces, edge verification nodes, and cloud-based carbon ledger platforms; The metering terminal layer is used to collect and provide the cumulative energy readings or instantaneous power samples and their timestamps for each metering point within the closed boundary of the intelligent rail vehicle depot within a time window. The vehicle regenerative energy data interface is used to obtain the regenerative braking energy of each vehicle in the set of vehicles associated with the intelligent rail vehicle depot within the time window and the depot-related events. The edge verification node is used to configure the energy conversion method and directional semantic coefficient for each metering point within the time window, calculate the energy within the window, perform directional semantic correction, time alignment and offset determination, and record the determination results, while also recording the data missing status; calculate the vehicle aggregation weight based on the duration of each vehicle within the closed boundary, and obtain the vehicle regeneration aggregation energy aggregated to the closed boundary of the intelligent rail vehicle section; aggregate the energy flow within the closed boundary of the intelligent rail vehicle section into the total energy on the input side and the total energy on the output side, establish an energy closure equation based on the total energy on the input side, the total energy on the output side, and the calculated loss energy, and calculate the energy closure residual and closure relative error; And based on the judgment result, the data missing status, and the relative closure error, a gating tag and a reason code are generated; The edge verification node is also used to output qualified data packets or data packets to be corrected based on the gating mark, and to freeze and isolate the data packets to be corrected. The cloud-based carbon ledger platform is used to receive the qualified data packets and execute carbon accounting and reporting logic, as well as to isolate and store the data packets to be corrected to support recalculation based on the supplementary data.

10. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, which executes the instructions stored in the memory to perform the method as described in any one of claims 1-8.

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