Blockchain-based distributed green power transaction and traceability method and system

Abstract

The application discloses a distributed green power transaction and traceability method and system based on a blockchain, relates to the field of power system information physical fusion and green power traceability, and can improve the consistency between the issued power and the real power delivery, and reduce the risk of mismatch, over-issuance and unqualified quality issuance.

Description

Technical Field

[0001] This invention relates to the field of cyber-physical fusion technology in power systems, specifically to a distributed green power trading and traceability method and system based on blockchain. Background Technology

[0002] When distributed renewable energy, energy storage, flexible loads, and user-side electrical equipment participate in green electricity trading, transaction contracts, green certificates, or blockchain-based evidence records can improve the immutability of transaction records, but they cannot directly prove that a target load actually consumes green electricity from the corresponding source node, corresponding physical path, corresponding phase, after deducting losses, and meeting power quality requirements within a certain verification window.

[0003] In AC distribution networks, the actual distribution of electrical energy is affected by topology switch status, node injection, branch impedance, transformer parameters, phase relationships, bidirectional power flow, three-phase imbalance, and cross-period charging and discharging of energy storage. If contracted transaction volume, curve-matched volume, or on-chain certificate volume are directly equated with receivable green electricity volume, problems such as time window mismatch, unreachable physical paths, undeducted line losses, phase mismatch, substandard power quality, repeated release of energy storage, and inconsistencies in the recorded electricity status after anomalies can easily occur.

[0004] Existing blockchain-based green electricity traceability solutions mostly process contracts, orders, scheduling curves, consumption tags, or certificate status, which can enhance record consistency and post-audit capabilities. However, they typically do not consider trusted measurement windows, distribution network physical path attribution, loss and phase correction, qualified power quality delivery, energy storage attribute inventory closure, and post-abnormal status rollback as necessary prerequisites for the same verifiable green electricity generation capacity. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a blockchain-based distributed green electricity trading and traceability method, comprising the following steps: Step 1: Obtain the metering, phasor, master and slave clock timestamps, sampling sequence number, event summary, topology, line and transformer parameters, phase labels, user common connection point (PCC) power quality, energy storage state of charge (SOC) and charge / discharge data, and transaction source-load mapping data of the verification node set within the verification window; wherein, the verification node set includes source nodes, load nodes, energy storage nodes, and grid-side nodes; Step two: Determine the trusted verification window based on the master-slave clock offset, sampling sequence continuity, phasor residual, and event digest consistency, and block untrusted windows from participating in the physical path coefficient matrix. generate; Step 3: Perform distribution network state estimation only on the data within the trusted verification window to obtain the node injection state and branch power flow state; if the state estimation does not meet the preset observability conditions, migrate the corresponding verification window to the Frozen state. Step four: Based on the transaction source-load mapping data, determine candidate source-load pairs, and generate a list indexed by source node, load node, phase, and trusted verification window based on node injection status, branch power flow status, topology, line and transformer parameters, and phase labels. and use Decompose the load power of the load node within the trusted verification window to obtain the physically attributable green electricity attribute power. Step 5: Determine the branch power loss and transformer power loss based on the branch power flow status, line parameters, and transformer parameters, respectively. Then, adjust the physically attributable green electricity power by combining the phase matching coefficient to obtain the net attributable green electricity power. ; Step 6: Generate a power quality qualified mask based on the user's common connection point (PCC) power quality data. and with Gating The power quality qualified attribute power can be obtained and can be included in the set to be issued; Step 7: Based on the energy storage SOC and charge / discharge data, charge / discharge efficiency, and the power quality qualification mask... The green attribute charging capacity written to the energy storage after gating and the energy used to retrieve the green attribute inventory from the energy storage The deducted green attribute discharge capacity is used to recursively calculate the physical energy state and the energy storage green attribute inventory. Before the energy storage discharge is issued, it is verified that the inventory reduction of the green attribute discharge capacity after discharge efficiency conversion is not greater than the energy storage green attribute inventory before discharge. ; Step 8, based on the power quality qualified mask. Gated and through the energy storage green attribute inventory The verified attribute power is used to generate a digest to be issued and written into the consortium blockchain smart contract. When the off-chain recalculation is consistent, the pending issuance state is transitioned to the final issuance state. If a time anomaly, phasor anomaly, physical path anomaly, power quality anomaly, energy storage inventory anomaly, or digest recalculation inconsistency occurs in the pending issuance state, it is transitioned to the frozen state. If the recalculation is inconsistent after the final issuance state, it is transitioned to the rollback state and the energy storage green attribute inventory is restored. It also adds a rollback reference summary.

[0006] Furthermore, the trusted verification window uses a trusted judgment quantity. Determined, the reliable determination quantity It is generated jointly by the master-slave clock deviation determination result, the sampling sequence continuity determination result, the phasor residual determination result, and the event digest consistency determination result; only when the master-slave clock deviation determination result, the sampling sequence continuity determination result, the phasor residual determination result, and the event digest consistency determination result all indicate that they have passed, is the corresponding verification window determined as the trusted verification window.

[0007] Furthermore, the physical path coefficient matrix include: The physical reachability coefficient from the source node to the load node under the current topology is determined based on the node injection state and the branch power flow state; the branch contribution coefficient of the source node to the load node is determined based on the branch power flow direction and the node power balance relationship; the phase matching relationship between the source node and the load node is determined based on the phase label, phase angle relationship, and voltage amplitude correlation; and the physical path coefficient matrix is ​​formed based on the physical reachability coefficient, the branch contribution coefficient, and the phase matching relationship. The source-load phase path coefficients in the model.

[0008] Furthermore, the branch power loss is determined based on the branch resistance, branch phase current, and verification window duration; the transformer power loss is determined based on the transformer no-load loss, transformer load loss, and transformer load rate; and the phase matching coefficient is determined based on the phase label, voltage amplitude correlation, and phase angle difference after transformer connection group compensation.

[0009] Furthermore, the power quality qualified mask This is generated based on the frequency determination result, voltage deviation determination result, harmonic determination result, three-phase imbalance determination result, and sag / boost event determination result; when the power quality qualified mask is obtained... This indicates the net attributable green electricity quantity when the power quality is qualified. Enter the set to be issued; when the power quality qualified mask This indicates the net attributable green electricity quantity when power quality is substandard. The issuance of t is blocked, or the issuance status of the corresponding certification window is changed to Frozen.

[0010] Furthermore, the physical energy state is recursively updated based on the energy storage charging capacity, energy storage discharging capacity, charging efficiency, discharging efficiency, and energy storage state of charge (SOC) data; the energy storage green attribute inventory... According to the power quality qualification mask After gating, the green attribute charging capacity of the energy storage is written, and the energy storage green attribute inventory is retrieved. The released green attribute discharge capacity, charging efficiency, and discharge efficiency are updated recursively; the inventory reduction of the green attribute discharge capacity after discounting by the discharge efficiency is no greater than the energy storage green attribute inventory before discharge. .

[0011] Furthermore, the green attribute charging capacity is determined according to the window ratio method; the window ratio method is: within the same trusted verification window, based on the physical path coefficient matrix... The branch power loss, the transformer power loss, the phase matching coefficient, and the power quality qualification mask. The proportion of the processed energy storage power quality qualified attribute electricity to the total energy storage charging electricity is used to determine the amount of energy storage green attribute inventory to be written. The share of green attributes.

[0012] Furthermore, when the summary to be issued is written into the consortium blockchain smart contract, the public ledger stores the window identifier, event identifier set, source node identifier set, load node identifier, phase set, topology version, physical path coefficient matrix summary, loss summary, phase matching summary, power quality summary, energy storage inventory change summary, clock quality code, phasor residual score, issuance status, reference transaction identifier, and rollback reference transaction identifier; the original metering sequence, phasor sequence, power quality details, energy storage state of charge (SOC) trajectory, and physical path coefficient matrix are stored in plaintext in the off-chain electrical verification engine or the consortium blockchain private data set.

[0013] Furthermore, when a switch state change, feeder transfer, fault event, generator tripping event, power flow reversal, master / slave clock anomaly, phasor residual anomaly, power quality anomaly, energy storage inventory anomaly, or inconsistency in off-chain recalculation summary is detected, the physical path coefficient matrix of the corresponding verification window is triggered. Net attributable green electricity Power quality qualified mask and energy storage with green attributes inventory The recalculation process will continue, and the corresponding issuance status will remain frozen until the recalculation result passes review. If an issuance record that is already in the final issuance status is determined to be inconsistent after recalculation, the corresponding issuance record will be migrated to the rollback status, and the corresponding energy storage green attribute inventory will be restored based on the rollback reference digest. .

[0014] A blockchain-based distributed green electricity trading and traceability system is used to execute the blockchain-based distributed green electricity trading and traceability method, including: a multi-node acquisition module, a dual-clock phasor reliability verification module, a distribution network physical path correction module, a loss and phase correction module, a power quality gating module, an energy storage attribute inventory module, an issuance state machine module, an on-chain digest anchoring module, and a data processing module. The multi-node acquisition module, dual-clock phasor reliability verification module, distribution network physical path correction module, loss and phase correction module, power quality gating module, energy storage attribute inventory module, issuance state machine module, and on-chain summary anchoring module are respectively connected to the data processing module. The multi-node acquisition module is used to acquire multi-point metering data of source, grid, load and storage, phasor data, master clock timestamp, auxiliary clock timestamp, sampling sequence number, event summary, topology switch status, line parameters, transformer parameters, phase labels, power quality data, energy storage state of charge (SOC) data, energy storage charge and discharge data and transaction source-load mapping data within the verification window; The dual-clock phasor reliability verification module is used to determine the reliability verification window based on the main and auxiliary clock deviation, sampling sequence continuity, phasor residual, and event digest consistency. The aforementioned distribution network physical path correction module is used to perform distribution network state estimation within the trusted verification window, obtain node injection state and branch power flow state, determine candidate source-load pairs by combining transaction source-load mapping data, and generate a physical path coefficient matrix. ; The aforementioned loss and phase correction module is used to generate net attributable green electricity attribute quantity based on branch loss quantity, transformer loss quantity, and phase matching coefficient. ; The power quality gating module is used to generate a power quality compliance mask based on the power quality data of the user's common connection point (PCC). and using the power quality qualified mask The net attributable green electricity attribute of the gating system ; The energy storage attribute inventory module is used to analyze energy storage charge and discharge data, charge and discharge efficiency, energy storage state of charge (SOC) data, and the power quality qualification mask. The green attribute charging capacity written to the energy storage after gating and the energy storage green attribute inventory The released green-attribute discharge electricity, in its physical energy state and stored in green-attribute inventory, Update the energy storage green attribute inventory in a parallel recursive manner Before issuing energy storage discharge permits, it is verified that the inventory reduction of the green attribute discharge capacity after discharge efficiency conversion is not greater than the energy storage green attribute inventory before discharge. ; The aforementioned nuclear power state machine module is used to determine the power quality qualification attribute and the energy storage green attribute inventory. The off-chain recalculation results generate a summary of the issuance to be issued, and the issuance status is migrated between the pending, final, frozen, and rolled-back states. The inventory recovery instruction and rollback reference summary are generated under the rolled-back state. The on-chain digest anchoring module is used to write the digest to be issued, the abnormal digest, and the rollback reference digest into the consortium blockchain smart contract.

[0015] The beneficial effects of this invention are: First, only those verification windows that pass the checks on master-slave clock skew, sampling sequence continuity, phasor residuals, and event digest consistency are allowed to enter the physical path coefficient matrix. The calculation reduces the risk of incorrect green electricity attribute issuance caused by sampling clock drift, buffer replay, sampling out-of-order, and event mismatch.

[0016] Second, the physical path coefficient matrix It generates data based on topology switch status, node injection status, branch power flow status, phasor measurement, line parameters, transformer parameters, and phase labels, rather than directly determining it based on contract paths. This allows for further modification of contract trustworthiness into distribution network physical reachability trustworthiness.

[0017] Third, the net attributable green electricity quantity is obtained by correcting for branch losses, transformer losses, and phase matching. This reduces the risk of excessive attribute issuance due to undeducted line losses, unattributed transformer losses, and phase mismatch.

[0018] Fourth, power quality qualified mask Directly affects net attributable green electricity. This links green energy sources with qualified delivery, preventing electricity generated during periods of substandard power quality from being unconditionally issued as green energy.

[0019] Fifth, energy storage with green attributes inventory By recursively extrapolating in parallel with the physical energy state, the risk of duplicate issuance and over-issuance of green electricity attributes of energy storage can be reduced in scenarios of mixed charging and discharging and cross-window release.

[0020] Sixth, the pending, final, frozen, and rolled-back states constitute an append-based issuance state machine. During rollback, the on-chain record is not deleted, but a rollback reference digest is added and the corresponding inventory is restored, improving the consistency of regulatory audit recalculation. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a blockchain-based distributed green electricity trading and traceability method. Detailed Implementation

[0022] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the following description.

[0023] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0024] Example 1

[0025] like Figure 1 As shown, the blockchain-based distributed green electricity trading and traceability method includes the following steps: Step 1: Obtain the metering, phasor, master and slave clock timestamps, sampling sequence number, event summary, topology, line and transformer parameters, phase labels, user common connection point (PCC) power quality, energy storage state of charge (SOC) and charge / discharge data, and transaction source-load mapping data of the verification node set within the verification window; wherein, the verification node set includes source nodes, load nodes, energy storage nodes, and grid-side nodes; Step two: Determine the trusted verification window based on the master-slave clock offset, sampling sequence continuity, phasor residual, and event digest consistency, and block untrusted windows from participating in the physical path coefficient matrix. generate; Step 3: Perform distribution network state estimation only on the data within the trusted verification window to obtain the node injection state and branch power flow state; if the state estimation does not meet the preset observability conditions, migrate the corresponding verification window to the Frozen state. Step four: Based on the transaction source-load mapping data, determine candidate source-load pairs, and generate a list indexed by source node, load node, phase, and trusted verification window based on node injection status, branch power flow status, topology, line and transformer parameters, and phase labels. and use Decompose the load power of the load node within the trusted verification window to obtain the physically attributable green electricity attribute power. Step 5: Determine the branch power loss and transformer power loss based on the branch power flow status, line parameters, and transformer parameters, respectively. Then, adjust the physically attributable green electricity power by combining the phase matching coefficient to obtain the net attributable green electricity power. ; Step 6: Generate a power quality qualified mask based on the user's common connection point (PCC) power quality data. and with Gating The power quality qualified attribute power can be obtained and can be included in the set to be issued; Step 7: Based on the energy storage SOC and charge / discharge data, charge / discharge efficiency, and the power quality qualification mask... The green attribute charging capacity written to the energy storage after gating and the energy used to retrieve the green attribute inventory from the energy storage The deducted green attribute discharge capacity is used to recursively calculate the physical energy state and the energy storage green attribute inventory. Before the energy storage discharge is issued, it is verified that the inventory reduction of the green attribute discharge capacity after discharge efficiency conversion is not greater than the energy storage green attribute inventory before discharge. ; Step 8, based on the power quality qualified mask. Gated and through the energy storage green attribute inventory The verified attribute power is used to generate a digest to be issued and written into the consortium blockchain smart contract. When the off-chain recalculation is consistent, the pending issuance state is transitioned to the final issuance state. If a time anomaly, phasor anomaly, physical path anomaly, power quality anomaly, energy storage inventory anomaly, or digest recalculation inconsistency occurs in the pending issuance state, it is transitioned to the frozen state. If the recalculation is inconsistent after the final issuance state, it is transitioned to the rollback state and the energy storage green attribute inventory is restored. It also adds a rollback reference summary.

[0026] Specifically, this embodiment applies to the green electricity attribute verification and traceability scenario involving distributed photovoltaic, energy storage, flexible loads, and enterprise electricity loads within 10kV park feeders and their low-voltage distribution areas. The system includes at least new energy grid-connected nodes, energy storage converter PCS interface nodes, feeder nodes, distribution area main meter nodes, key branch nodes, user common connection point (PCC) nodes, and target load nodes. Among them, the new energy grid-connected nodes act as source nodes to inject green electricity into the distribution network, the target load nodes act as load nodes to represent the location of electricity consumption by the target user or target load side, the energy storage converter PCS interface nodes act as energy storage nodes to participate in cross-window charging and discharging, and the feeder nodes, distribution area main meter nodes, key branch nodes, and user common connection point (PCC) nodes, together with the source nodes, load nodes, and energy storage nodes, constitute the verification node set.

[0027] Within the verification window used to perform green electricity attribute certification calculations, the multi-node acquisition module acquires active power, reactive power, voltage phasors, current phasors, frequency, phase angle, power direction, and event summaries from the new energy grid-connected nodes; it acquires distribution network power flow status, branch current, branch voltage, topology switch status, and event summaries from feeder nodes, transformer area meter nodes, and key branch nodes; it acquires frequency, voltage deviation, harmonics, imbalance, and sag / boost event data from the user's point of common coupling (PCC) node; it acquires load power and phase labels from the target load node; and it acquires data from energy storage. The converter PCS interface node and battery management system (BMS) acquire charging and discharging direction, charging and discharging capacity, energy storage state of charge (SOC) data, and energy storage operation events; they also acquire transaction source-load mapping data from the transaction or verification service interface. This transaction source-load mapping data is used to characterize the transaction or verification qualification correspondence between candidate source nodes and candidate load nodes, and to determine the candidate source-load pairs participating in the physical attribution calculation. However, it does not replace the physical path coefficient matrix generated by topology switch status, node injection status, branch power flow status, line parameters, transformer parameters, and phase labels. In one implementation, the verification window uses a 15-minute window, an hourly window for aggregated auditing, and an event-level window for freezing and rollback. The time granularity can be configured according to the site metering granularity and verification rules.

[0028] The aforementioned metering data, phasor data, and power quality data all carry a master clock timestamp, a secondary clock timestamp, and a sampling sequence number. The event summary is used to identify events within the corresponding verification window, such as switch status changes, faults, generator trips, power flow reversals, power quality anomalies, or energy storage operation events. The master clock can use GNSS timing, and the secondary clock can use PTP timing. If other equivalent dual-clock structures are used in actual engineering, as long as master and secondary timestamps can be provided and master-secondary clock deviation determination is supported, it also belongs to the equivalent implementation of this embodiment.

[0029] After receiving the data output by the multi-node acquisition module, the off-chain electrical verification engine first calculates the master-slave clock deviation. If the master-slave clock deviation exceeds a preset freezing threshold, the corresponding verification window is written into the abnormal window set. If the master-slave clock deviation does not exceed the preset freezing threshold, the sampling sequence continuity determination, phasor residual determination, and event digest consistency determination are then performed. The preset freezing threshold, preset residual threshold, preset observability condition, preset correlation threshold, preset angle difference threshold, and preset power quality condition can be determined based on equipment synchronization accuracy, measurement accuracy, site engineering configuration, grid connection specifications, user power requirements, or off-chain electrical verification rules. If no specific values ​​are given, their specific values ​​are not considered independent protection boundaries.

[0030] Phasor residuals can be calculated jointly from node voltage phasors, node current phasors, phase angle continuity, power direction, and topology consistency. In one implementation, the normalized difference between the predicted phasors estimated based on the current topology state and the measured phasors is used as the phasor residual. If the phasor residual exceeds a preset residual threshold, the corresponding verification window is written into the anomalous window set. If the event occurrence order corresponding to the event digest is inconsistent with the sampling sequence number, or if the event hash is inconsistent with the off-chain event cache, the corresponding verification window is written into the anomalous window set.

[0031] A verification window is determined to be a reliable verification window only when the master-slave clock offset, sampling sequence continuity, phasor residual, and event digest consistency all meet the criteria. Not identified as a trusted verification window. The data must not be used in the physical path coefficient matrix Calculation. In one implementation, the confidence determination quantity. Used to indicate whether the verification window is trustworthy, and satisfies:

[0032] in, This indicates the result of the master-slave clock deviation determination. This indicates the result of determining the continuity of the sampling sequence. This indicates the phasor residual determination result. This indicates the result of the event summary consistency determination; , , and All are binary determination results, only when At that time, the corresponding verification window is determined as a trusted verification window. .

[0033] In the trusted verification window Internally, the off-chain electrical verification engine estimates the distribution network state based on topology switch states, node injected power, branch voltage, current phasor, line impedance, transformer parameters, and phase labels, obtaining node injected state and branch power flow state.

[0034] The off-chain electricity verification engine determines candidate source-load pairs based on transaction source-load mapping data; these candidate source-load pairs are used to limit the combination of source nodes and load nodes that need to be calculated for green electricity attribute certification. The transaction source-load mapping data is not directly used as the physical attributable contribution coefficient, but rather in the physical path coefficient matrix. Once generated, it is used in conjunction with the physical reachability results to determine the source payload paths that can participate in kernel issuance.

[0035] The off-chain electrical verification engine establishes a physical path coefficient matrix based on the source node, load node, phase, and trusted verification window. In one implementation, the physical path coefficient matrix Represented in the following form:

[0036] in, Indicates the source node, Indicates the load node. Indicates separation, Indicates the trusted verification window number. Indicates in the trusted verification window Intrinsic nodes At parting Up to load nodes The physical attributable contribution coefficients. Physical path coefficient matrix. It is generated jointly by trusted phasors, topology switch states, node injection states, branch power flow states, branch parameters, transformer parameters, and phase labels, and is not directly replaced by the contract path table. Based on... When decomposing load electricity to obtain physically attributable green electricity, the following conditions must be met:

[0037] in, Indicates load node At parting and trusted verification window The load power within, This represents the physically attributable green electricity attribute quantity under the phase dimension. Indicates the source node In the trusted verification window Internally belonging to load nodes The sum of the physical attributes of each phase that can be attributed to green electricity. Generate the physical path coefficient matrix. At that time, the off-chain electrical verification engine performs at least the following processes: Identify whether the source node and the target load node are physically reachable under the current topology; The contribution ratio of the source node to the target load node is determined based on the node injection status and branch power flow status. The phase matching relationship is determined based on the phase label, phase angle relationship, and voltage amplitude correlation. The attribution paths for branch losses and transformer losses are determined based on line impedance and transformer parameters.

[0038] When the state estimation fails to converge, key nodes are missing, topology versions are inconsistent, or observability does not meet the preset observability conditions, the off-chain electrical verification engine does not use the contract power extrapolation physical path coefficient matrix. Instead, the corresponding verification window is moved to a frozen state.

[0039] The off-chain electrical verification engine calculates branch power loss based on branch resistance, branch phase current, and verification window duration. In one implementation, the branch... At the verification window Internal branch circuit power loss satisfy:

[0040] in, Indicates the duration of the verification window. Indicates a branch At parting The equivalent resistance on, Indicates a branch At parting and verification window The phase current within.

[0041] The off-chain electrical verification engine calculates transformer power loss based on transformer no-load loss, transformer load loss, and transformer load rate. In one implementation, the transformer... At the verification window Internal transformer power loss satisfy:

[0042] in, Indicates transformer The no-load loss, Indicates transformer Rated load loss, Indicates transformer At the verification window Load rate within.

[0043] The off-chain electrical verification engine distributes branch power losses and transformer power losses to the corresponding source-load paths based on branch contribution coefficients and transformer contribution coefficients. The off-chain electrical verification engine also uses phase matching coefficients... Phase consistency correction is applied to physically attributable green electricity quantities. Phase matching coefficient. Either a hard-determination method or a soft-determination method can be used. In the hard-determination method, when the voltage amplitude correlation is not lower than a preset correlation threshold and the phase angle difference after transformer connection group compensation is not higher than a preset angle difference threshold, the phase matching coefficient is... Select 1 if the value is 1, otherwise select 0.

[0044] The off-chain electrical verification engine combines physically attributable green electricity, branch loss electricity, transformer loss electricity, and phase matching coefficients to obtain net attributable green electricity. In one implementation, net attributable green electricity is... satisfy:

[0045] in, Represents the phase matching coefficient. Indicates belonging to the source node With load nodes The power loss of branches in the path between them. Indicates belonging to the source node With load nodes The transformer power loss along the path between them This indicates that a value less than zero is taken as zero. Net attributable green electricity quantity. It is the only electricity subject for subsequent power quality gating and energy storage attribute inventory deduction. Contracted electricity volume does not directly enter into power quality gating and energy storage attribute inventory deduction.

[0046] The power quality gating module uses the trusted verification window based on the user's common connection point (PCC) node. Data on frequency, voltage deviation, harmonics, imbalance, and sag / boost events are used to generate a power quality compliance mask. Power quality qualified mask It can be a binary mask or a multi-state mask that includes qualified, verified, and blocked states.

[0047] In the binary mask implementation, if the frequency, voltage deviation, harmonics, imbalance, and sag / boost events all meet the preset power quality conditions, then the power quality is qualified mask. Set to 1; if any blocking power quality condition is not met, then the power quality qualified mask is used. Set to 0. Power quality qualified mask. Effect on net attributable green electricity The power quality attribute of the obtained power is qualified. :

[0048] in, Indicates load node At the verification window Internal power quality qualified mask, Indicates the source node Belonging to load nodes Furthermore, the power attribute is gated through power quality.

[0049] The preset power quality conditions can be given by grid connection specifications, user power receiving requirements, or engineering configuration. Specific numerical thresholds are not considered independent protection boundaries; this embodiment discloses power quality data types, determination sources, and gating targets to ensure that those skilled in the art can implement power quality gating according to specific site rules.

[0050] The energy storage attribute inventory module establishes the physical energy status of energy storage devices. and energy storage with green attributes inventory Physical energy state is used to reflect the physical electrical energy state of energy storage devices, and is a green attribute inventory of energy storage. Used to reflect the inventory of releasable green attributes within energy storage devices.

[0051] In one implementation, the physical energy state of the energy storage satisfies:

[0052] in, Indicates charging efficiency. Indicates discharge efficiency. Indicates the verification window The charging capacity inside, Indicates the verification window The discharge capacity inside, This refers to the physical-side correction item. The physical-side correction item is determined based on at least one of the following: energy storage self-discharge capacity, the metering calibration difference of the energy storage converter PCS interface node or the battery management system (BMS), and the energy storage auxiliary energy consumption confirmed within the verification window; in the absence of a physical-side correction event... Take 0.

[0053] Energy storage green attribute inventory satisfy:

[0054] in, Indicates the verification window The internal energy storage stores the green attribute of the charging capacity. Indicates the verification window The green discharge power released from energy storage. This represents the attribute-side correction item. The attribute-side correction item is determined based on the green attribute inventory correction amount triggered by the frozen state, the rolled-back state, or inconsistencies in off-chain recalculation; when using the above recursive formula... A positive value indicates a deduction from the green attribute inventory. A negative value indicates the restoration of green attribute inventory, when there is no attribute-side correction event. Set to 0. Green attribute discharge capacity. Discharge efficiency The converted inventory reduction shall not exceed the energy storage green attribute inventory before discharge. .

[0055] In the peer ratio method implementation, the off-chain electrical verification engine calculates the trusted verification window. Internal physical path coefficient matrix Loss correction, phase correction, and power quality compliance mask The proportion of the power quality qualified electricity recorded after processing to the total charging electricity of energy storage is recorded as the green attribute share of the energy storage. When energy storage discharges, inventory is determined based on the green attributes of energy storage. The amount of green attribute discharge capacity that can be released is determined by the discharge capacity and discharge efficiency. If the amount of green attribute discharge capacity to be issued, after deducting inventory based on discharge efficiency, exceeds the green attribute inventory of energy storage... If the discharge amount is insufficient, the corresponding discharge quantity must not enter the final issuance state (Final).

[0056] The issuance state machine module sets an issuance state for each digest to be issued. These states include Pending, Final, Frozen, and Rolled-back. Pending indicates that the digest has been generated and written to the consortium blockchain smart contract but final recalculation has not yet been completed. Final indicates that issuance is confirmed after the off-chain recalculation result, digest to be issued, power quality gating result, energy storage green attribute inventory change result, and audit conditions are all consistent. Frozen indicates that final issuance is suspended due to time anomalies, phasor anomalies, physical path anomalies, power quality anomalies, energy storage inventory anomalies, or digest recalculation inconsistencies. Rolled-back indicates that issuance records already in Final are appended with a rollback reference digest and the corresponding energy storage green attribute inventory is restored after being determined to be inconsistent in subsequent audits or late data recalculations. .

[0057] When the confidence quantity Equal to 1, physical path coefficient matrix Successfully generated net attributable green electricity. A mask indicating power quality is greater than zero. Allow issuance of green energy storage inventory If the deduction is not negative and the off-chain recalculation result is consistent with the digest to be issued, the issuance state machine module will transition the corresponding digest to be issued from the pending state to the final issuance state.

[0058] When the following occurs: master / slave clock anomaly, sampling sequence anomaly, phasor residual anomaly, event digest anomaly, topology version anomaly, physical path matrix cannot be generated, power quality blockage, insufficient inventory of energy storage green attributes, or inconsistent off-chain recalculation digest, the issuance state machine module will migrate the corresponding digest to be issued to the Frozen state.

[0059] When an issuance record in the Final issuance state is found to be inconsistent during subsequent regulatory review, late data recalculation, or abnormal event supplementation, the issuance state machine module will migrate the corresponding issuance record to the Rolled-back state. The Rolled-back state does not delete existing on-chain records; instead, it appends a rollback reference digest and restores the corresponding energy storage green attribute inventory based on the rollback reference digest. .

[0060] The on-chain summary anchoring module writes the summary to be issued into the consortium blockchain smart contract. The public ledger stores the window identifier, event identifier set, source node identifier set, load node identifier, phase set, topology version, physical path coefficient matrix summary, loss summary, phase matching summary, power quality summary, energy storage inventory change summary, clock quality code, phasor residual score, issuance status, reference transaction identifier, and rollback reference transaction identifier. The original metering sequence, phasor sequence, power quality details, energy storage state of charge (SOC) trajectory, physical path coefficient matrix plaintext, and off-chain recalculation intermediate results are stored in the off-chain electrical verification engine or the consortium blockchain private data set.

[0061] Example 2: Low Observability Scenarios deal with

[0062] In some transformer substations or feeders, the phasor acquisition coverage of the target node is insufficient. In this case, the off-chain electrical verification engine can combine smart meter data, substation master meter data, feeder measurement data, and phasor acquisition unit data, using confidence weights to participate in distribution network state estimation. If the preset observability conditions can still be met under low observability conditions, a physical path coefficient matrix with confidence labels is generated. If the low observability state cannot meet the preset observability conditions, the corresponding verification window will be moved to the Frozen state.

[0063] Example 3: Power Quality Compliance Mask Review status

[0064] In some grid-connected disturbance scenarios, short-term power quality breaches may occur simultaneously with grid support events. In this case, the power quality compliance mask... It can be expanded into three states: qualified, under review, and blocked. The qualified state allows for net attributable green electricity. Entering the pending issuance set; the blocking state prohibits net attributable green electricity. Enter the pending issuance set; the review status allows the corresponding electricity to enter the pending issuance status, but it can only be migrated to the final issuance status or the frozen status after the event-level review.

[0065] Example 4: Energy Storage with Green Attributes Inventory Batch cancellation

[0066] In addition to the window ratio method, the energy storage attribute inventory module can also use a batch write-off method to store green attribute batches entering energy storage. Each green attribute batch includes a window identifier, source node identifier, charging attribute capacity, charging efficiency correction value, and batch summary. When energy storage discharges, the green attribute inventory is written off according to the batch entry order. The batch write-off method is suitable for scenarios that require more granular auditing of cross-window attribute releases of energy storage.

[0067] Example 5: Inventory Recovery After Abnormal Rollback

[0068] When the issued energy storage discharge capacity is subsequently determined by audit to require rollback, the issuance state machine module locates the corresponding energy storage inventory deduction record based on the rollback reference transaction identifier, calculates the inventory recovery amount, writes the inventory recovery amount back to the energy storage inventory register, and appends a rollback reference digest to the consortium blockchain smart contract. The original final issuance digest and the newly added rollback reference digest are retained on-chain; the final valid state is determined by the rollback reference digest during audit recalculation.

[0069] Example 6

[0070] This embodiment provides a blockchain-based distributed green electricity trading and traceability system. The system includes a multi-node acquisition module, a dual-clock phasor reliability verification module, a distribution network physical path correction module, a loss and phase correction module, a power quality gating module, an energy storage attribute inventory module, a power issuance state machine module, and an on-chain digest anchoring module.

[0071] The multi-node acquisition module collects multi-point metering data, phasor data, master and slave clock timestamps, sampling sequence numbers, event summaries, topology switch status, power quality data, energy storage operation data, and transaction source-load mapping data from the verification node set, and sends the acquisition results to the dual-clock phasor trusted verification module and the off-chain electrical verification engine.

[0072] The dual-clock phasor reliability verification module determines the reliability verification window based on the master-slave clock offset, sampling sequence continuity, phasor residual, and event digest consistency. and the trusted verification window Send to the distribution network physical path correction module.

[0073] The distribution network physical path correction module is only available in the trusted verification window. The distribution network state is estimated internally to obtain the node injection state and branch power flow state. Candidate source-load pairs are determined by combining the transaction source-load mapping data, and a physical path coefficient matrix is ​​generated. The candidate source load pairs are then sent to the loss and phase correction module, along with the corresponding physically attributable green electricity attribute.

[0074] The loss and phase correction module generates net attributable green electricity based on branch losses, transformer losses, and phase matching coefficients. And the net attributable green electricity Send to the power quality gating module.

[0075] The power quality gating module generates a power quality compliance mask based on the power quality data from the user's common connection point (PCC) node. And will pass through a power quality qualified mask. The power quality qualified attribute power after gating is sent to the energy storage attribute inventory module.

[0076] The energy storage attribute inventory module uses the charge and discharge data, charge and discharge efficiency, and state of charge (SOC) data of the energy storage converter PCS interface node, along with the power quality qualification mask, to determine the energy storage attributes. The green attribute charging capacity written to the energy storage after gating and the energy storage green attribute inventory The released green-attribute discharge electricity, in its physical energy state and stored in green-attribute inventory, Update the energy storage green attribute inventory in a parallel recursive manner The inventory verification result is then sent to the issuance state machine module.

[0077] The issuance state machine module generates a summary to be issued based on the trusted window result, physical path result, power quality gating result, energy storage inventory verification result, and off-chain recalculation result. It then transitions the issuance state between the pending, final, frozen, and rolled-back states. Under the rolled-back state, it generates an inventory recovery instruction and a rollback reference summary.

[0078] The on-chain summary anchoring module writes the summary to be issued, the abnormal summary, and the rollback reference summary into the consortium blockchain smart contract, and retains the audit index for regulatory audit recalculation.

[0079] The following state transition table is used to define the state boundaries, triggering conditions, processing actions, and on-chain write-back results of the certification state machine under different certification results and abnormal events. Its function is to define the trusted certification window. Physical path coefficient matrix Net attributable green electricity Power quality qualified mask Energy storage with green attributes inventory In addition, the off-chain recalculation results are used to establish a correspondence between the pending issuance state (Pending), the final issuance state (Final), the frozen state (Frozen), and the rollback state (Rolled-back), so that each pending issuance digest has a recalcible state basis during normal issuance, frozen review, and rollback recovery.

[0080] State transition table

[0081] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A blockchain-based distributed green electricity trading and traceability method, characterized in that, Includes the following steps: Step 1: Obtain the metering, phasor, master and slave clock timestamps, sampling sequence number, event summary, topology, line and transformer parameters, phase labels, user common connection point (PCC) power quality, energy storage state of charge (SOC) and charge / discharge data, and transaction source-load mapping data of the verification node set within the verification window; wherein, the verification node set includes source nodes, load nodes, energy storage nodes, and grid-side nodes; Step two: Determine the trusted verification window based on the master-slave clock offset, sampling sequence continuity, phasor residual, and event digest consistency, and block untrusted windows from participating in the physical path coefficient matrix. generate; Step 3: Perform distribution network state estimation only on the data within the trusted verification window to obtain the node injection state and branch power flow state; if the state estimation does not meet the preset observability conditions, migrate the corresponding verification window to the Frozen state. Step four: Based on the transaction source-load mapping data, determine candidate source-load pairs, and generate a list indexed by source node, load node, phase, and trusted verification window based on node injection status, branch power flow status, topology, line and transformer parameters, and phase labels. and use Decompose the load power of the load node within the trusted verification window to obtain the physically attributable green electricity attribute power. Step 5: Determine the branch power loss and transformer power loss based on the branch power flow status, line parameters, and transformer parameters, respectively. Then, adjust the physically attributable green electricity power by combining the phase matching coefficient to obtain the net attributable green electricity power. ; Step 6: Generate a power quality qualified mask based on the user's common connection point (PCC) power quality data. and with Gating The power quality qualified attribute electricity can be obtained and can be included in the set to be issued; Step 7: Based on the energy storage SOC and charge / discharge data, charge / discharge efficiency, and the power quality qualification mask... The green attribute charging capacity written to the energy storage after gating and the energy used to retrieve the green attribute inventory from the energy storage The deducted green attribute discharge capacity is used to recursively calculate the physical energy state and the energy storage green attribute inventory. Before the energy storage discharge is issued, it is verified that the inventory reduction of the green attribute discharge capacity after discharge efficiency conversion is not greater than the energy storage green attribute inventory before discharge. ; Step 8, based on the power quality qualified mask. Gated and through the energy storage green attribute inventory The verified attribute power is used to generate a digest to be issued and written into the consortium blockchain smart contract. When the off-chain recalculation is consistent, the pending issuance state is transitioned to the final issuance state. If a time anomaly, phasor anomaly, physical path anomaly, power quality anomaly, energy storage inventory anomaly, or digest recalculation inconsistency occurs in the pending issuance state, it is transitioned to the frozen state. If the recalculation is inconsistent after the final issuance state, it is transitioned to the rollback state and the energy storage green attribute inventory is restored. It also adds a rollback reference summary.

2. The blockchain-based distributed green electricity trading and traceability method according to claim 1, characterized in that, The trusted verification window uses a trusted judgment quantity. Determined, the reliable determination quantity It is generated jointly by the master-slave clock deviation determination result, the sampling sequence continuity determination result, the phasor residual determination result, and the event digest consistency determination result; only when the master-slave clock deviation determination result, the sampling sequence continuity determination result, the phasor residual determination result, and the event digest consistency determination result all indicate that they have passed, is the corresponding verification window determined as the trusted verification window.

3. The blockchain-based distributed green electricity trading and traceability method according to claim 1, characterized in that, The physical path coefficient matrix include: The physical reachability coefficient from the source node to the load node under the current topology is determined based on the node injection state and the branch power flow state; the branch contribution coefficient of the source node to the load node is determined based on the branch power flow direction and the node power balance relationship; the phase matching relationship between the source node and the load node is determined based on the phase label, phase angle relationship, and voltage amplitude correlation; and the physical path coefficient matrix is ​​formed based on the physical reachability coefficient, the branch contribution coefficient, and the phase matching relationship. The source-load phase path coefficients in the model.

4. The blockchain-based distributed green electricity trading and traceability method according to claim 1, characterized in that, The branch power loss is determined based on the branch resistance, branch phase current, and verification window duration; the transformer power loss is determined based on the transformer no-load loss, transformer load loss, and transformer load rate; the phase matching coefficient is determined based on the phase label, voltage amplitude correlation, and phase angle difference after transformer connection group compensation.

5. The blockchain-based distributed green electricity trading and traceability method according to claim 1, characterized in that, The power quality qualified mask This is generated based on the frequency determination result, voltage deviation determination result, harmonic determination result, three-phase imbalance determination result, and sag / boost event determination result; when the power quality qualified mask is obtained... This indicates the net attributable green electricity quantity when the power quality is qualified. Enter the set to be issued; when the power quality qualified mask This indicates the net attributable green electricity quantity when power quality is substandard. Issuance is blocked, or the issuance status of the corresponding certification window is changed to Frozen.

6. The blockchain-based distributed green electricity trading and traceability method according to claim 1, characterized in that, The physical energy state is updated recursively based on energy storage charging capacity, energy storage discharging capacity, charging efficiency, discharging efficiency, and energy storage state of charge (SOC) data; the energy storage green attribute inventory... According to the power quality qualification mask After gating, the green attribute charging capacity of the energy storage is written, and the energy storage green attribute inventory is retrieved. The released green attribute discharge capacity, charging efficiency, and discharge efficiency are updated recursively; the inventory reduction of the green attribute discharge capacity after discounting by the discharge efficiency is no greater than the energy storage green attribute inventory before discharge. .

7. The blockchain-based distributed green electricity trading and traceability method according to claim 6, characterized in that, The green attribute charging capacity is determined according to the same window ratio method; the same window ratio method is: within the same trusted verification window, based on the physical path coefficient matrix. The branch power loss, the transformer power loss, the phase matching coefficient, and the power quality qualification mask. The proportion of the processed energy storage power quality qualified attribute electricity to the total energy storage charging electricity is used to determine the amount of energy storage green attribute inventory to be written. The share of green attributes.

8. The blockchain-based distributed green electricity trading and traceability method according to claim 1, characterized in that, When the summary to be issued is written into the consortium blockchain smart contract, the public ledger stores the window identifier, event identifier set, source node identifier set, load node identifier, phase set, topology version, physical path coefficient matrix summary, loss summary, phase matching summary, power quality summary, energy storage inventory change summary, clock quality code, phasor residual score, issuance status, reference transaction identifier, and rollback reference transaction identifier; the original metering sequence, phasor sequence, power quality details, energy storage state of charge (SOC) trajectory, and physical path coefficient matrix are stored in plaintext in the off-chain electrical verification engine or the consortium blockchain private data set.

9. The blockchain-based distributed green electricity trading and traceability method according to claim 1, characterized in that, When a change in switch status, feeder switching, fault event, generator tripping event, power flow reversal, master / slave clock anomaly, phasor residual anomaly, power quality anomaly, energy storage inventory anomaly, or inconsistency in off-chain recalculation summary is detected, the physical path coefficient matrix of the corresponding verification window is triggered. Net attributable green electricity Power quality qualified mask and energy storage with green attributes inventory The recalculation process will continue, and the corresponding issuance status will remain frozen until the recalculation result passes review. If an issuance record that is already in the final issuance status is determined to be inconsistent after recalculation, the corresponding issuance record will be migrated to the rollback status, and the corresponding energy storage green attribute inventory will be restored based on the rollback reference digest. .

10. A blockchain-based distributed green electricity trading and traceability system, characterized in that, The method for executing the blockchain-based distributed green electricity trading and traceability method according to any one of claims 1 to 9 includes: a multi-node acquisition module, a dual-clock phasor trust verification module, a distribution network physical path correction module, a loss and phase correction module, a power quality gating module, an energy storage attribute inventory module, a certificate issuance state machine module, an on-chain digest anchoring module, and a data processing module. The multi-node acquisition module, dual-clock phasor reliability verification module, distribution network physical path correction module, loss and phase correction module, power quality gating module, energy storage attribute inventory module, issuance state machine module, and on-chain summary anchoring module are respectively connected to the data processing module. The multi-node acquisition module is used to acquire multi-point metering data of source, grid, load and storage, phasor data, master clock timestamp, auxiliary clock timestamp, sampling sequence number, event summary, topology switch status, line parameters, transformer parameters, phase labels, power quality data, energy storage state of charge (SOC) data, energy storage charge and discharge data and transaction source-load mapping data within the verification window; The dual-clock phasor reliability verification module is used to determine the reliability verification window based on the main and auxiliary clock deviation, sampling sequence continuity, phasor residual, and event digest consistency. The aforementioned distribution network physical path correction module is used to perform distribution network state estimation within the trusted verification window, obtain node injection state and branch power flow state, determine candidate source-load pairs by combining transaction source-load mapping data, and generate a physical path coefficient matrix. ; The aforementioned loss and phase correction module is used to generate net attributable green electricity attribute quantity based on branch loss quantity, transformer loss quantity, and phase matching coefficient. ; The power quality gating module is used to generate a power quality compliance mask based on the power quality data of the user's common connection point (PCC). and using the power quality qualified mask The net attributable green electricity attribute of the gating system ; The energy storage attribute inventory module is used to analyze energy storage charge and discharge data, charge and discharge efficiency, energy storage state of charge (SOC) data, and the power quality qualification mask. The green attribute charging capacity of the energy storage is written after gating and the energy storage green attribute inventory is obtained. The released green-attribute discharge electricity, in its physical energy state and stored in green-attribute inventory, Update the energy storage green attribute inventory in a parallel recursive manner Before issuing energy storage discharge permits, it is verified that the inventory reduction of the green attribute discharge capacity after discharge efficiency conversion is not greater than the energy storage green attribute inventory before discharge. ; The aforementioned nuclear power state machine module is used to determine the power quality qualification attribute and the energy storage green attribute inventory. The off-chain recalculation results generate a summary of the issuance to be issued, and the issuance status is migrated between the pending, final, frozen, and rolled-back states. The inventory recovery instruction and rollback reference summary are generated under the rolled-back state. The on-chain digest anchoring module is used to write the digest to be issued, the abnormal digest, and the rollback reference digest into the consortium blockchain smart contract.

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