Method and system for dynamic adjustment of third line of defense load shedding amount under new power system

Abstract

A method and system for dynamically adjusting the load shedding amount of the third line of defense in a new power system is proposed. This involves expanding, assigning values, and correcting the load shedding feeder data model to obtain a corrected model. When the "actual load shedding status" field in the corrected model is 1 and the model is in the resource pool, the model is compared with the precise load shedding sequence table based on the feeder circuit breaker ID. According to the comparison results, the "whether it is in the precise shedding scheme" field is assigned a correct value to obtain the final model. When multiple load shedding operations are performed based on the final model, the load shedding completion rate for each round is calculated. When the load shedding completion rate for a round is outside the expected range, a dynamic allocation strategy for subsequent rounds is triggered. An optimal load shedding adjustment scheme is automatically generated to ensure the load shedding completion rate remains stable within the set range.

Description

Technical Field

[0001] This invention belongs to the field of new power system technology, specifically, it relates to a method and system for dynamically adjusting the load reduction of the third line of defense in a new power system. Background Technology

[0002] In recent years, with the large-scale integration of distributed power sources and diverse load types, power grid load fluctuations have become significant, posing a considerable challenge to grid stability. During low-frequency load shedding adjustments, issues such as exceeding or falling short of grid demand during load shedding can affect the safe and stable operation of the power grid. To improve the level of lean equipment management, enhance the penetration of professional management, and ensure the safe and stable operation of the power system, it is necessary to build a dynamic intelligent control function for regional low-frequency load shedding based on the existing online monitoring and intelligent analysis system for low-frequency load shedding. This will support the intelligent management and digitalization of regional low-frequency load shedding operations, comprehensively improving the dispatching side's management level of regional low-frequency load shedding.

[0003] However, existing technologies have the following problems: 1) The list of loads that can be shelved is tied to the shelving cycle, lacking dynamic priority sorting; in traditional low-frequency load shelving devices, the list of loads to be shelved for each cycle is pre-set manually and remains unchanged over a long period. This static binding method cannot reflect the actual importance of the load, the real-time power level, and changes in the interruptible protocol on the user side in real time.

[0004] 2) Strategy generation relies on offline calculations and cannot be dynamically optimized online; the low-frequency load shedding of traditional devices is usually determined based on calculations or empirical settings under typical operating conditions. When the power grid is large-scale and operates in diverse modes, it lacks the ability to assess the current operating status online and dynamically calculate the optimal load shedding strategy, resulting in low strategy matching.

[0005] 3) There are problems with the modeling. The model is not perfect and lacks models of feeder load characteristics, feeder low-frequency load shedding function and remote switching capability. It cannot support the dynamic adjustment of low-frequency load shedding amount for auxiliary decision-making.

[0006] 4) The level of intelligence in load shedding adjustment is low. It is unable to monitor feeder power flow direction and feeder power supply in real time. When performing low-frequency load shedding impact analysis, it is unable to actively trigger low-frequency load shedding dynamic adjustment and track the execution of load adjustment. It lacks technical means to support load management.

[0007] 5) The load shedding scheme relies heavily on manual experience and has significant limitations. The scheme is mainly based on expert experience and does not fully consider the differences in power supply structure and load characteristics. It is based on a typical moment and has poor resistance to fluctuations. At certain times, there will be a large gap between the load that can be shelved and the load that should be shelved. If a load shedding action occurs, there will be situations where the load shedding is excessive or insufficient. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides a novel method and system for dynamically adjusting the load shedding of the third line of defense in a power system. It achieves a unified fusion framework for multi-source heterogeneous information, comprehensively analyzes information such as the priority level, load characteristics, and power flow direction of low-frequency feeder loads, accurately assesses the impact of distributed power generation output and the execution of low-frequency load shedding on customer electricity consumption, automatically generates the optimal load shedding adjustment scheme, and remotely activates and deactivates the low-frequency load shedding function pressure plate, ensuring that the load shedding completion rate of the low-frequency load shedding scheme remains stable within the set range.

[0009] The present invention adopts the following technical solution.

[0010] On the one hand, this invention proposes a novel method for dynamically adjusting the load reduction of the third line of defense in a power system, including: Obtain the electrical and physical attributes, secondary equipment control attributes, power grid operation management attributes, and process confirmation attributes of the feeders in the load reduction scheme, and expand and assign values ​​to the load reduction feeder data model; Power flow telemetry data is obtained from the Supervisory Control and Data Acquisition (SCADA) system and power supply protection tag records are obtained from the dispatch management system. The "distributed power source identifier" and "whether the line has a power supply protection tag" fields in the expanded load shedding feeder data model are assigned and corrected. Based on the assignment and correction results, the "actual pressure plate status" field in the load shedding feeder data model is assigned and corrected to obtain the corrected load shedding feeder data model. When the "Actual Pressure Plate Status" field in the modified load shedding feeder data model is 1 and the load shedding feeder data model is in the resource pool, the modified load shedding feeder data model is compared with the precise load shedding sequence point table based on the load shedding feeder circuit breaker identification identifier (ID); according to the comparison result, the "Whether it is in the precision shedding scheme" field in the load shedding feeder data model is assigned a value to correct, and the final load shedding feeder data model is obtained. When performing multiple load shedding operations based on the final load shedding feeder data model, the load shedding completion rate of each round is calculated; when the load shedding completion rate of a certain round is not within the expected range of the load shedding completion rate, the dynamic allocation strategy of subsequent rounds is triggered. In the dynamic allocation strategy, the optimal range of load shedding completion rate is determined based on the expected range of load shedding completion rate. The deviations of subsequent rounds from the optimal range of load shedding completion rate are calculated and sorted according to the real-time cross-sectional data of the power grid. Based on the scores of each feeder in the final load shedding feeder data model and the load shedding plan, the operation sequence of each load shedding feeder is determined. Remote commissioning and decommissioning operations are performed according to the operation sequence. After the operation is completed, the load shedding completion rate is recalculated and iterative adjustments are made if it does not fall within the optimal range of load shedding completion rate until all remaining rounds fall within the optimal range or there are no adjustable resources. The final load shedding feeder data model is saved after each iteration.

[0011] The electrical and physical attributes of the feeder, the secondary equipment control attributes, the power grid operation management attributes, and the process confirmation attributes are mapped to structured logical fields and added to the load shedding feeder data model. Among them, the electrical and physical attributes include: load type and distributed power source identification; the secondary equipment control attributes include: controllable status of the pressure plate and remote control execution result; the power grid operation management attributes include: power supply protection tag and fine-cutting scheme overlap identification; and the process confirmation attributes include: status update time and confirmer.

[0012] The extended operations of the unloaded feeder data model include: 1) Expanding within the existing domain: 1.1) Expand “Spare Field 3” to “Distributed Power Source Identifier”, where 0 indicates no distributed power source, 1 indicates distributed power source, and 2 indicates distributed voltage source. 1.2) Expand the "Spare Field 8" field to the "Load Type" field, where 1 represents high-risk users, 2 represents important users, 3 represents distributed power lines, 4 represents high proportion of residential loads, 5 represents medium proportion of residential loads, 6 represents low proportion of residential loads, 7 represents industrial loads, 8 represents commercial loads, 9 represents agricultural loads, and 10 represents generating units. 2) Expanding within a new domain: 2.1) Added a field "Whether the line has a power protection sign", where 0 indicates no sign and 1 indicates a sign; 2.2) Added a "Controllable pressure plate" field, where 1 indicates controllable and 0 indicates uncontrollable, with 0 as the default. 2.3) Add a "Remote Control Failure Flag" field, which defaults to 0. If the preset fails or the control fails during the remote control process, the field will be set to 1. After the remote control test is successful, manual reset will be performed. 2 indicates that no reset will be performed. 2.4) Add a new field "Whether the load is controllable", where 1 indicates controllable and 0 indicates uncontrollable; 2.5) Added "Whether it is in the fine cutting scheme", 1 indicates yes, 0 indicates no; 2.6) Added a "Whether it is in the resource pool" field, where 1 indicates it is in the resource pool and 0 indicates it is not. 2.7) Added a "Distributed Power Update Time" field, which directly uses the timestamp; 2.8) Added a "Power Supply Status Update Time" field, which directly uses the timestamp; 2.9) Added a "Distributed Power Source Confirmation Status" field, where 1 indicates confirmation and 0 indicates non-confirmation, which is updated by the human-machine interface; 2.10) Added a "Power Supply Confirmation Status" field, where 1 indicates confirmation and 0 indicates no confirmation; 2.11) Added the "Distributed Power Source Confirmer" field, which is updated via the human-machine interface; 2.12) Added a "Power Supply Confirmation Person" field, which is updated via the human-machine interface; 2.13) Added the "Actual Pressure Plate Status" field, where 0 indicates exit, 1 indicates engagement, 2 indicates no associated pressure plate signal, and 3 indicates multiple pressure plates; 2.14) Added a "Remote Control Count" field, which defaults to 0. Each remote control operation increments the count by 1, with a maximum of 10 remote control counts. The remote control count is cleared daily. 2.15) Added a "Importance Level" field; 2.16) Added the "Importance Index" field.

[0013] Power flow telemetry data is obtained from SCADA and power supply protection tag records are obtained from the dispatch management system. The "Distributed Power Source Identifier" and "Whether the Line Has a Power Supply Protection Tag" fields in the expanded load shedding feeder data model are automatically assigned values, including: Power flow telemetry data is obtained from SCADA to monitor the power flow direction of feeders in real time. For feeders with reversed power flow, the feeder is identified as a distributed power source feeder, and the "distributed power source identifier" field in the extended load shedding feeder data model is automatically assigned a value of 1. The system retrieves power supply guarantee tag records from the dispatch management system, queries the power supply guarantee feeder switch ID from the power supply guarantee tag records, and automatically assigns the value 1 to the "Whether the line has a power supply guarantee tag" field in the expanded load reduction feeder data model when the power supply guarantee feeder switch ID matches the load reduction feeder switch ID.

[0014] Based on the assignment results, the "Actual Pressure Plate State" field in the unloaded feeder data model is dynamically corrected, including: Based on the assigned load shedding feeder data model, dynamic correction of the load shedding feeder cut-off attributes is performed, including: obtaining the pressure plate status information from the protection device management unit; if the "distributed power source identifier" field or the "whether the line has a power protection sign" field in the extended load shedding feeder data model is 1, then the corresponding feeder performs the load shedding pressure plate exit operation, and the "actual pressure plate status" field is set to 0; if the "distributed power source identifier" field and the "whether the line has a power protection sign" field in the extended load shedding feeder data model are both 0, then the "actual pressure plate status" field is set to 1.

[0015] If the "Actual Pressure Plate Status" field in the load shedding feeder data model is 0, a load shedding undercut alarm event will be generated.

[0016] When the "Actual Platen Status" field in the corrected load shedding feeder data model is 1 and the "Whether in Resource Pool" field is 1, a comparison is performed between the corrected load shedding feeder data model and the accurate load shedding sequence point table based on the load shedding feeder circuit breaker ID, including: If the load shedding feeder circuit breaker ID is only in the revised load shedding feeder data model, then the "Whether it is in the fine-cutting scheme" field in the revised load shedding feeder data model is set to 0; if the load shedding feeder circuit breaker ID is only in the precise load shedding sequence point table, then the "Whether it is in the fine-cutting scheme" field in the revised load shedding feeder data model is set to 1; if the load shedding feeder circuit breaker ID exists in both the revised load shedding feeder data model and the precise load shedding sequence point table, then a fine-cutting overlap alarm event is generated.

[0017] Get the Planned load shedding during load shedding operation Compared with actual load , No. Actual load of wheel and the first The ratio of the planned load shedding in each round is used as the first Wheel load completion rate When the first Wheel load completion rate If the load shedding rate is not within the expected range, then subsequent actions will be triggered. Dynamic allocation strategy for wheel unloading plan, It is a positive integer greater than 2.

[0018] In the dynamic allocation strategy, the optimal range of load shedding completion rate for each round is determined based on the expected range of load shedding completion rate. Based on real-time grid cross-sectional data, the deviation between the load shedding completion rate and the optimal range for subsequent rounds is calculated online, and subsequent rounds are arranged in descending order of absolute deviation value. Based on the assigned values ​​of the "load type," "importance level," and "number of remote control operations" fields in the final load shedding feeder data model, the score of the load shedding feeder is calculated. Based on the scores of all feeders, the allocation score of the load shedding feeder is determined according to the load shedding plan, and the "actual" value in the load shedding feeder data model is adjusted according to the allocation score. The "Pressure Plate Status" field is updated; in each round after rolling arrangement, the operation sequence of each load shedding feeder is determined according to the allocation score and load of the load shedding feeder; according to the operation sequence of each load shedding feeder, the remote deployment and deactivation operation of the feeder low-frequency load shedding function pressure plate is executed; after the operation is completed, the load shedding completion rate of the current round is recalculated. If it does not fall within the optimal range of load shedding completion rate, iterative adjustment is performed until the load shedding completion rate of all remaining rounds falls within the optimal range or there are no adjustable resources; at the same time, after each iteration, a snapshot of all fields of the final load shedding feeder data model is saved to the historical adjustment record table.

[0019] Based on the The wheel load shedding completion rate and the expected range of the load shedding completion rate are used to determine whether subsequent wheel load shedding operations are feasible; when it is determined to be feasible, the optimal range of the load shedding completion rate is determined based on the expected range of the load shedding completion rate. Based on real-time grid cross-sectional data, the deviation between the load shedding completion rate and the optimal range of the load shedding completion rate for each subsequent round is calculated online, and the subsequent rounds are arranged in descending order of the absolute value of the deviation. Based on the values ​​assigned to the "Load Type", "Importance Level", and "Number of Remote Controls" fields in the final load shedding feeder data model, the score of the load shedding feeder is calculated. Based on the scores of all feeders, the allocation score of the load reduction feeders is determined according to the load reduction plan, and the "actual pressure plate status" field in the load reduction feeder data model is updated by assigning values ​​according to the allocation scores. In each round after the rolling arrangement, the operation sequence of each load shedding feeder is determined based on the allocation score of the load shedding feeder and the load of the load shedding feeder.

[0020] Based on the The wheel load shedding completion rate and the expected range of the load shedding completion rate are used to determine the first... The adjustment amount for the +1 round of load shedding operation is determined when the adjustment amount is not greater than the adjustable amount. +1 round load shedding operation is feasible; Determine the adjustment target range and the optimal load shedding completion rate based on the expected range of the load shedding completion rate; The optimal range of load shedding completion rate is determined based on the optimal load shedding completion rate.

[0021] The score for the unloaded feeder is shown in the following formula:

[0022] In the formula, For load reduction feeder The score, For load reduction feeder The value assigned to the "load type" field, For load reduction feeder The assignment of values ​​to the "importance level" field, For load reduction feeder The value assigned to the "Number of Remote Controls" field, , , This is a percentage parameter.

[0023] Feeders included in the load reduction plan will be designated as in-operation feeders, while feeders not included in the load reduction plan will be designated as backup feeders; for feeders designated as in-operation feeders... If the plan is to deploy a load-reducing feeder The pressure plate will reduce the load on the feeder. Score Subtract 100 points as the allocation score if the plan is to withdraw from the load reduction feeder. The pressure plate will reduce the load on the feeder. Score Add 100 points as the allocation score.

[0024] When load shedding feeders are put into operation: the operating sequence of each load shedding feeder is determined by combining the ascending order of the load shedding feeder allocation score and the descending order of the load shedding feeder load. When a load shedding feeder is decommissioned: the operation sequence of each load shedding feeder is determined by combining the descending order of the load shedding feeder allocation score and the descending order of the load shedding feeder load.

[0025] According to the operation sequence of each load shedding feeder, the remote activation and deactivation operation of the low-frequency load shedding function pressure plate of each feeder is executed one by one, and the operation results are written to the corresponding "actual pressure plate status" field in the final load shedding feeder data model in real time. At the same time, after each pressure plate operation is executed, the "remote control count" field of the corresponding feeder in the final load shedding feeder data model is incremented by 1, and the "remote control count" field of all feeders is cleared to zero at a fixed time every day.

[0026] After executing the first After the +1 round of load shedding, the actual load shedding completion rate for this round is recalculated using the current value of the "actual pressure plate status" field in the final load shedding feeder data model and the real-time load value of the corresponding feeder. If the load shedding completion rate for this round has fallen into the optimal range, the dynamic adjustment for this round is complete, and the original or adjusted plan for subsequent rounds continues to be executed. If the load shedding completion rate for this round has not yet fallen into the optimal range, the dynamic allocation strategy for subsequent rounds is executed, and the subsequent rounds are iteratively adjusted until the load shedding completion rates for all remaining rounds fall into the optimal range or there are no adjustable resources.

[0027] After each complete dynamic adjustment iteration, a snapshot of all fields of the final load shedding feeder data model is saved to the historical adjustment record table, including: "distributed power source identifier", "whether the line is equipped with a power protection sign", "actual pressure plate status", "whether it is in the fine-cutting scheme", "number of remote control operations", "load type", "importance level", "importance index", as well as the current round identifier and adjustment timestamp.

[0028] On the other hand, this invention also proposes a novel dynamic adjustment system for the load reduction of the third line of defense in a power system, comprising: The load shedding feeder data model extension and correction module is used to acquire the electrical and physical attributes, secondary equipment control attributes, power grid operation management attributes, and process confirmation attributes of the feeders in the load shedding scheme, and to extend and assign values ​​to the load shedding feeder data model. It obtains power flow telemetry data from SCADA and power supply protection tag records from the dispatch management system, and corrects the values ​​of the "distributed power source identifier" and "whether the line has a power supply protection tag" fields in the extended load shedding feeder data model. Based on the correction results, it corrects the value of the "actual pressure plate status" field in the load shedding feeder data model, resulting in the corrected load shedding feeder data model. When the "actual pressure plate status" field in the corrected load shedding feeder data model is 1 and the load shedding feeder data model is in the resource pool, it compares the corrected load shedding feeder data model with the precise load shedding sequence point table based on the load shedding feeder circuit breaker ID. Based on the comparison results, it corrects the value of the "whether it is in the precise shedding scheme" field in the load shedding feeder data model, resulting in the final load shedding feeder data model. The dynamic allocation strategy triggering module is used to calculate the load shedding completion rate of each round when performing multiple rounds of load shedding operations based on the final load shedding feeder data model; when the load shedding completion rate of a certain round is not within the expected range of the load shedding completion rate, the dynamic allocation strategy of subsequent rounds is triggered. The dynamic allocation strategy execution module is used in the dynamic allocation strategy to determine the optimal range of load shedding completion rate based on the expected range of load shedding completion rate, calculate and sort the deviations of each subsequent round from the optimal range of load shedding completion rate based on real-time grid cross-sectional data, determine the operation sequence of each load shedding feeder based on the score of each feeder in the final load shedding feeder data model and the load shedding plan, execute remote commissioning and decommissioning operations according to the operation sequence, recalculate the load shedding completion rate after the operation is completed, and perform iterative adjustments if it does not fall into the optimal range of load shedding completion rate until all remaining rounds fall into the optimal range or there are no adjustable resources. After each iteration, the final load shedding feeder data model is saved.

[0029] The present invention is also a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the method.

[0030] The present invention is also a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0031] The beneficial effects of this invention are that, compared with the prior art, it at least includes: 1) Establish a unified data fusion platform to achieve model-based aggregation and linkage correction of multi-source heterogeneous information: This invention maps the electrical and physical attributes of feeders, secondary equipment control attributes, power grid operation management attributes, and process confirmation attributes into structured logical fields, systematically expanding the feeder data model for load shedding (adding and expanding 16 fields such as "distributed power source identifier", "whether the line is under power protection sign", "actual pressure plate status", "whether it is in the precision shedding scheme", and "number of remote control operations"). Distributed power source access information, power protection sign constraint information, pressure plate controllable status information, and precision load shedding scheme overlap information are incorporated into the same structured data model, enabling the heterogeneous information originally scattered in SCADA, dispatch management system, and protection information management system to achieve unified management and collaborative access under the same framework, upgrading from a static model that "can only be viewed but not calculated" to a real-time decision engine that is "readable, calculable, and linkage-enabled". Based on this unified data model, the "distributed power source identifier" is automatically corrected from the power flow direction information obtained in real time from SCADA, and the "power supply tag status" is automatically corrected from the power supply tag information periodically polled from the scheduling management system. This, in turn, triggers the dynamic correction of the "actual pressure plate status". This realizes the automated integration of distributed power source identification, power supply tag recognition and pressure plate status management under the same technical framework, and upgrades the status judgment of feeder cut-off attributes from a manual cross-system query mode with a delay of several hours to a minute-level automatic perception and linkage decision-making.

[0032] 2) Establish a cross-system resource collaborative perception mechanism to solve the resource conflict early warning problem between low-frequency load shedding and precise load shedding systems: Based on a unified data model, this invention introduces an automatic cross-comparison mechanism between the low-frequency load shedding resource pool and the precise load shedding resource pool. Using the circuit breaker ID as the unique primary key, periodic inter-table association queries are performed to achieve near real-time automatic identification (minute-level), structured marking (written into the "whether it is in the precise shedding scheme" field), and automatic alarm (triggering a precise shedding overlap alarm event) of overlapping resources. For the first time, this invention solves the "resource hidden conflict" problem caused by two independent systems, low-frequency load shedding and precise load shedding, sharing the same physical resource pool in a new power system from the system architecture level, filling the long-standing technical gap of lacking automated resource collaborative perception and conflict early warning methods between the two systems.

[0033] 3) Establish a real-time dynamic scoring and ranking mechanism to accurately match load shedding strategies with the current power grid operation mode: Based on the assignment of values ​​to the "load type," "importance level," and "remote control frequency" fields in the final load shedding feeder data model, this invention constructs a three-layer composite scoring model. This model dynamically changes the cutoff priority of each feeder according to its load characteristics, importance, and recent operation frequency, ensuring that the load shedding strategy always matches the current power grid operation mode. Simultaneously, by differentiating the scoring strategy for operating / standby feeders, the current activated switch states are reused to the maximum extent, reducing unnecessary switch activation / deactivation operations and extending equipment lifespan. The matching degree between strategy and operation mode is increased from less than 40% in traditional fixed schemes to over 90%.

[0034] 4) Establish a rolling closed loop of "execution → detection → correction → re-execution" to ensure that the load shedding volume of the entire network continuously converges to the target range: This invention calculates the load shedding completion rate in real time after each round of load shedding operation. When the load shedding completion rate deviates from the expected range, it automatically triggers the dynamic allocation strategy for subsequent rounds. Through a complete closed loop of determining the optimal range → calculating the deviation → sorting by the absolute value of the deviation → calculating the feeder score → determining the allocation score → executing remote deployment and withdrawal → re-verifying the load shedding completion rate of this round, if it does not meet the target, it iterates back to the optimal range and recalculates. This ensures that the execution deviation of each round can be compensated in a timely manner in subsequent rounds, and the load shedding volume of the entire network always converges to the target range. The risks of under-shearing and over-shearing are effectively suppressed, and the error shedding rate of important loads is reduced by 80% or more. Each complete dynamic adjustment iteration saves a snapshot of all fields of the final load shedding feeder data model to the historical adjustment record table, realizing the traceability, reproducibility, and auditability of the entire process of dynamic adjustment of load shedding volume, and comprehensively improving the digitalization and intelligence level of the third line of defense load shedding scheme management. Attached Figure Description

[0035] Figure 1 This is a flowchart of a novel method for dynamically adjusting the load reduction of the third line of defense in a power system, as proposed in this invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0037] This invention proposes a novel method for dynamically adjusting the load reduction of the third line of defense in a power system, such as... Figure 1 As shown, the method includes: Step 1: Obtain the electrical and physical attributes, secondary equipment control attributes, power grid operation management attributes, and process confirmation attributes of the feeder in the load reduction scheme, and expand and assign values ​​to the load reduction feeder data model.

[0038] Specifically, the electrical and physical attributes of the feeder, the secondary equipment control attributes, the power grid operation management attributes, and the process confirmation attributes are mapped to structured logical fields and added to the load shedding feeder data model. Among them, the electrical and physical attributes include, but are not limited to: load type, distributed power source identifier; the secondary equipment control attributes include, but are not limited to: controllable status of the pressure plate, remote control execution result; the power grid operation management attributes include, but are not limited to: power supply protection tag, fine-cutting scheme overlap identifier; the process confirmation attributes include, but are not limited to: status update time, confirmer.

[0039] This invention is based on the model maintenance function of online monitoring of the third line of defense. According to the feeder-related information required for dynamic adjustment of the load reduction of the third line of defense under the new power system, the load reduction feeder data model is extended. The diverse and heterogeneous information affecting low-frequency load reduction decisions is integrated into a unified power grid resource description table. This ensures that the impact of distributed power generation output and execution of low-frequency load reduction on customer electricity consumption can be accurately judged through information such as feeder nature and priority level, power flow direction, etc. The optimal load reduction adjustment scheme is automatically generated, and the low-frequency load reduction function pressure plate is remotely activated or deactivated to ensure that the load reduction completion rate of the low-frequency load reduction scheme is stable within the set range.

[0040] In this embodiment, the expansion operation of the unloaded feeder data model includes: 1) Expanding within the existing domain: 1.1) Expand the "Spare Field 3" field to the "Distributed Power Source Identifier" field, where 0 indicates no distributed power source, 1 indicates distributed power source (program judgment), and 2 indicates distributed voltage (manual maintenance after user confirmation). 1.2) Expand the "Spare Field 8" field to the "Load Type" field, where 1 represents high-risk users, 2 represents important users, 3 represents distributed power lines, 4 represents high proportion of residential loads, 5 represents medium proportion of residential loads, 6 represents low proportion of residential loads, 7 represents industrial loads, 8 represents commercial loads, 9 represents agricultural loads, and 10 represents generating units.

[0041] 2) Expanding within a new domain: 2.1) Added a field "Whether the line has a power protection sign", where 0 indicates no sign and 1 indicates a sign; 2.2) Added a "Controllable pressure plate" field, where 1 indicates controllable and 0 indicates uncontrollable, with 0 as the default. 2.3) Add a "Remote Control Failure Flag" field, which defaults to 0. If the preset fails or the control fails during the remote control process, the field will be set to 1. After the remote control test is successful, manual reset will be performed. 2 indicates that no reset will be performed. 2.4) Add a new field "Whether the load is controllable", where 1 indicates controllable and 0 indicates uncontrollable; 2.5) Added "Whether it is in the fine cutting scheme", 1 indicates yes, 0 indicates no; 2.6) Added a "Whether it is in the resource pool" field, where 1 indicates it is in the resource pool and 0 indicates it is not. 2.7) Added a "Distributed Power Update Time" field, which directly uses the timestamp; 2.8) Added a "Power Supply Status Update Time" field, which directly uses the timestamp; 2.9) Added a "Distributed Power Source Confirmation Status" field, where 1 indicates confirmation and 0 indicates non-confirmation, which is updated by the human-machine interface; 2.10) Added a "Power Supply Confirmation Status" field, where 1 indicates confirmation and 0 indicates no confirmation; 2.11) Added the "Distributed Power Source Confirmer" field, which is updated via the human-machine interface; 2.12) Added a "Power Supply Confirmation Person" field, which is updated via the human-machine interface; 2.13) Added the "Actual Pressure Plate Status" field, where 0 indicates exit, 1 indicates engagement, 2 indicates no associated pressure plate signal, and 3 indicates multiple pressure plates; 2.14) Added a "Remote Control Count" field, which defaults to 0. Each remote control operation increments the count by 1, with a maximum of 10 remote control counts. The remote control count is cleared daily. 2.15) Added a "Importance Level" field; 2.16) Added the "Importance Index" field.

[0042] By expanding the data model as described above, the scoring algorithm and decision support in subsequent steps can directly call the structured field values ​​for quantitative calculation, thus solving the technical defect of the existing model that can only be viewed but not calculated.

[0043] The formulation of low-frequency load shedding strategies requires simultaneous consideration of the electrical and physical attributes of feeders (such as power direction and distributed power source access), the controllability attributes of secondary equipment (such as the controllability of load cells), the power grid operation and management attributes (such as power supply guarantee status), and the resource coordination relationships between multiple systems (such as overlapping precise load shedding resource pools). However, in existing technologies, the above information is stored separately in SCADA systems, dispatch management systems, and protection information management systems, which are isolated from each other and have different formats. They cannot be synchronously accessed and linked for calculation in the same data model, resulting in a serious lag in the assessment of load shedding status compared to changes in power grid operation. This invention, based on the model maintenance function of online monitoring of the third line of defense, expands the load shedding feeder data model according to the feeder-related information required for the dynamic adjustment of the load shedding amount of the third line of defense under the new power system. It integrates the diverse and heterogeneous information affecting low-frequency load shedding decisions—including power telemetry information from SCADA, power supply guarantee status information from the dispatch management system, load cell status information from the protection information management system, and resource pool information from the precise load shedding system—into a unified power grid resource description table. The aforementioned diverse and heterogeneous information is stored separately in different business systems in existing technologies. They are independent of each other, have different formats, and have never been managed and coordinated under the same data model framework. Through the above-mentioned extended operations, this invention, for the first time, incorporates distributed power supply access information, power supply guarantee constraint information, pressure plate controllable status information, and precise load shedding scheme overlap information into the same structured data model, laying a data foundation for subsequent multi-source information linkage correction and cross-system resource comparison.

[0044] Step 2: Obtain power flow telemetry data from SCADA and power supply protection tag records from the dispatch management system. Assign and correct the values ​​of the "Distributed Power Source Identifier" and "Whether the Line is Attached with a Power Supply Protection Tag" fields in the expanded load reduction feeder data model. Based on the assignment and correction results, assign and correct the values ​​of the "Actual Pressure Plate Status" field in the load reduction feeder data model to obtain the corrected load reduction feeder data model.

[0045] In existing technologies, SCADA telemetry data is used for real-time monitoring, power supply protection tag records are used for dispatch management, and pressure plate remote control is used for protection device operation. These three technologies serve different business scenarios and have never been used together in the real-time dynamic correction of feeder switchability attributes in low-frequency load shedding strategies. This invention integrates the power flow telemetry data, power supply protection tag records in the dispatch management system, and pressure plate status information in the protection device management unit—originally scattered across the D5000 platform SCADA database—into a single load shedding feeder data model. This expanded load shedding feeder data model provides a structured data storage framework for the dynamic correction of load shedding feeder switchability attributes. Through experiments using typical power grid simulation data, this invention… The proposed load reduction strategy has improved its matching accuracy with the current actual operating mode from less than 40% in the traditional fixed scheme to over 90%. By executing specific judgment logics such as distributed power flow reverse discrimination and power supply guarantee listing periodic polling and matching, the real-time changing power grid operating status and management information are continuously mapped and written into the corresponding fields of the data model. This allows the model to evolve from a static shell into a dynamically updated real-time state image, providing accurate and quantifiable input parameters for the auxiliary decision-making algorithm in subsequent steps. Moreover, the distributed power source discrimination logic and the power supply guarantee listing matching logic can be executed based on the same load reduction feeder data model, avoiding the information asymmetry and response lag problems caused by the need for manual cross-system consultation and comprehensive judgment in the traditional scheme.

[0046] Specifically, step 2 includes: Step 2.1: Obtain power flow telemetry data from SCADA, monitor the power flow direction of the feeder in real time, and determine that the feeder is a distributed power source feeder if the power flow reverses continuously. The "distributed power source identifier" field in the extended load shedding feeder data model is automatically assigned a value of 1. In this embodiment, if the load value of the load-reducing feeder is negative in real time, it is determined to be a distributed power supply feeder.

[0047] Step 2.2: Obtain the power supply guarantee tag record from the dispatch management system, query the power supply guarantee feeder switch ID from the power supply guarantee tag record, and when the power supply guarantee feeder switch ID matches the load reduction feeder switch ID, automatically assign the value 1 to the "Whether the line is tagged with a power supply guarantee tag" field in the expanded load reduction feeder data model; In this embodiment, the power supply protection tag records in the sign information table (table 616) are read every 5 minutes (the specific time can be configured). The switch ID is queried in the power supply protection tag record by using the "equipment keyword" field. The switch ID is compared with the switch ID in the load reduction information table (table 3382). When the switch ID matches, the "whether the line has a power supply protection tag" of the feeder is set to 1, indicating that the feeder is a power supply protection load.

[0048] Step 2.3: Based on the assigned load shedding feeder data model, perform dynamic correction of the load shedding feeder cut-off attributes, including: obtaining the pressure plate status information from the protection device management unit; if the "distributed power source identifier" field is 1 or the "line whether a power protection sign is attached" field is 1 in the extended load shedding feeder data model, then the corresponding feeder performs the load shedding pressure plate exit operation, and the "actual pressure plate status" field is set to 0; if the "distributed power source identifier" field is 0 and the "line whether a power protection sign is attached" field is 0 in the extended load shedding feeder data model, then the "actual pressure plate status" field is set to 1; thus obtaining the corrected load shedding feeder data model.

[0049] In addition, based on the operator information and time information during the execution of steps 2.1 to 2.3, values ​​are assigned to relevant fields of the extended load shedding feeder data model, such as the "distributed power supply update time" field and the "power supply status update time" field.

[0050] This invention dynamically corrects feeder attributes based on real-time status perception. Before the low-frequency load shedding strategy is executed, it dynamically identifies loads that cannot or should not be shedding by monitoring the feeder's operating status (power flow direction) and management status (power supply protection tag) in real time, and automatically triggers a linkage process for load shedding and under-shedding alarms. Specifically, it monitors the feeder power flow direction and feeder equipment tags involved in the load shedding plan in real time, enabling judgment of the feeder's low-frequency load shedding status and load shedding completion rate. When the system's load shedding amount does not meet the shedding requirements, it proactively triggers dynamic adjustment of low-frequency load shedding to assist in decision-making. When the system detects that the load shedding plan contains distributed power sources or power supply protection tag loads, it will display an indicator light on the human-machine interface, reminding the user to perform a low-frequency load shedding load shedding operation for such loads. The user can review whether such loads have been shedding loads through the interface.

[0051] Step 2.4: If the "Actual Pressure Plate Status" field in the load shedding feeder data model is 0, then a load shedding undercut alarm event is generated.

[0052] Insufficiency caused by the removal of distributed power sources or power protection tags from the pressure plate should be automatically generated immediately and sent to the third line of defense alarm module, expanding the alarm type to "low frequency load shedding alarm caused by change in load characteristics".

[0053] In this embodiment, the system periodically checks whether the line contains distributed power sources or whether power protection tags have been manually set. It monitors the status of line load cells and changes in load characteristics in real time. If the system determines that the line contains distributed power sources or that power protection tags have been manually set on the feeder, the load cell is deactivated after confirmation by the dispatcher, and the low-frequency load shedding function load cell is remotely controlled. After the remote control process is completed, a message is sent to the human-machine interface, and the load shedding completion rate at the current time point is calculated. If the set threshold is not met, an alarm is immediately issued.

[0054] The core innovation of Step 2 lies in establishing a linkage correction chain of "distributed power source / power guarantee sign identification result → actual power supply status → undercut alarm". Specifically, Steps 2.1 and 2.2 obtain information from different data sources (SCADA, dispatch management system) and automatically assign values, while Step 2.3 comprehensively judges and links the "actual power supply status" based on the assignment results of the above two fields—when any field indicates that the feeder should not be cut off, the system automatically executes the logic judgment of power supply exit. This processing mechanism of "multi-source input → single model convergence → linkage decision output" has not been seen in any public literature or actual engineering application before this invention. In the traditional approach, distributed power source access judgment, power guarantee sign query, and power supply status management are completed independently by different personnel in different systems. Information transmission relies on manual communication, which is inefficient and prone to errors. This invention, through a unified data model and linkage correction logic, realizes the automatic connection of the above three independent business links under the same technical framework for the first time.

[0055] Step 3: When the "Actual Pressure Plate Status" field in the corrected load shedding feeder data model is 1 and the load shedding feeder data model is in the resource pool, the corrected load shedding feeder data model is compared with the precise load shedding sequence point table based on the load shedding feeder circuit breaker ID; according to the comparison result, the "Whether it is in the precision shedding scheme" field in the load shedding feeder data model is assigned a value to correct it, and the final load shedding feeder data model is obtained.

[0056] Specifically, when the "Actual Pressure Plate Status" field in the corrected load shedding feeder data model is 1 and the "Whether it is in the resource pool" field is 1, a comparison is made between the corrected load shedding feeder data model and the precise load shedding sequence point table based on the load shedding feeder circuit breaker ID. If the load shedding feeder circuit breaker ID is only in the corrected load shedding feeder data model, the "Whether it is in the precise shedding scheme" field in the corrected load shedding feeder data model is set to 0. If the load shedding feeder circuit breaker ID is only in the precise load shedding sequence point table, the "Whether it is in the precise shedding scheme" field in the corrected load shedding feeder data model is set to 1. If the load shedding feeder circuit breaker ID exists in both the corrected load shedding feeder data model and the precise load shedding sequence point table, a precise shedding overlap alarm event is generated.

[0057] Existing low-frequency load shedding technologies focus on calculating the required load shedding and ensuring completion rates, but have never addressed the potential strategy conflicts that can arise when two independent systems—low-frequency load shedding and precise load shedding—share the same resource pool. With the widespread application of precise load shedding systems in new power systems, this conflict has become a real threat to the safe operation of the power grid. Therefore, this invention, based on an extended load shedding feeder data model, establishes an automatic cross-comparison mechanism between the low-frequency load shedding resource pool and the precise load shedding resource pool. Through periodic inter-table association queries using the circuit breaker ID as the unique primary key, it achieves structured marking and real-time alarms for overlapping resources.

[0058] In this embodiment, the program performs a comparison between the load shedding feeder data model and the precise load shedding sequence point table upon startup and daily at 10:00 AM (the specific startup cycle and time are configurable). All circuit breaker IDs recorded in the load shedding feeder data model are compared with the device identifiers in the precise load shedding sequence point table. If a circuit breaker ID recorded in the load shedding feeder data model appears in the device identifier column of the precise load shedding sequence point table, it indicates that the load corresponding to that record is in the precise load shedding scheme, and the "whether it is in the precise load shedding scheme" field in the load shedding feeder data model is set to 1. If a circuit breaker ID corresponding to a record cannot be found in the precise load shedding sequence point table, it indicates that the load on that line is not in the precise load shedding scheme, and the "whether it is in the precise load shedding scheme" field for that record is set to 0. If, after comparison, a load exists in both schemes simultaneously, an alarm is issued to the third-line alarm module, with the alarm type being "precise load shedding reclosing alarm".

[0059] In this embodiment, the method proposed in this invention can analyze the matching between the regional load shedding scheme model and the precise load shedding resources. The precise load shedding system loads the model information of low-frequency load shedding in the third line of defense from the model library, considers the calculation of the precise load shedding capacity of low-frequency load shedding, and for feeder resources with low-frequency load shedding function already in operation, its precise load shedding priority should be reduced, and the precise load shedding capacity should be calculated. This invention assists in realizing the function of analyzing and verifying the overlapping load shedding of low-frequency load shedding and precise load shedding functions. It mainly targets resources that participate in both precise load shedding and low-frequency load shedding rounds, analyzes the overlapping load shedding from the perspectives of model and real-time data, identifies overlapping feeder resources, and calculates overlapping load shedding. Moreover, the analysis of overlapping load shedding of precise load shedding and low-frequency resources based on the power grid model also enables the verification and analysis of the overlapping part of the precise load shedding resource pool and the low-frequency load shedding resource pool after the low-frequency load shedding scheme is maintained.

[0060] With the widespread application of precision load shedding systems in new power systems, it has become common for two systems to share the same physical resource pool (i.e., the load corresponding to the same circuit breaker may be included in both the low-frequency load shedding scheme and the precision load shedding scheme simultaneously). However, in existing technologies, the low-frequency load shedding scheme and the precision load shedding scheme are independently developed and operated, and there is no automated resource cross-comparison and overlap warning mechanism between the two systems. When a feeder appears in both schemes simultaneously, once the low-frequency load shedding action removes the load, the available resources on which the precision load shedding system depends will be passively reduced, and vice versa. This "hidden resource conflict" is not prominent in traditional power grids, but it is becoming increasingly serious in new power systems with the popularization of precision load shedding systems, yet there has always been a lack of effective technical means to identify and warn against it. Existing low-frequency load shedding technologies focus on how to calculate the required shedding volume and how to ensure the load shedding completion rate, but have never paid attention to the strategy conflict problem that may arise when two independent systems, low-frequency load shedding and precision load shedding, share the same resource pool. With the widespread application of precise load shedding systems in new power systems, this conflict has become a real hidden danger affecting the safe operation of the power grid: the two systems are operated and maintained independently by different professional departments, and each has its own load shedding plan. However, the actual resources available for shedding essentially come from the same set of physical circuit breakers. When the same feeder is included in both plans simultaneously, the action of either system will substantially affect the total available resources of the other system. Existing technologies lack both automatic identification capabilities and early warning mechanisms for such resource overlap. Therefore, this invention, based on an extended load shedding feeder data model, establishes for the first time an automated cross-comparison mechanism between the low-frequency load shedding resource pool and the precise load shedding resource pool. Through periodic inter-table association queries with the circuit breaker ID as the unique primary key, it achieves near real-time identification (minute-level), structured marking (writing the "whether it is in the precise shedding plan" field), and automatic alarm (precise shedding overlap alarm event triggering). Technically, this fills the technical gap of lacking resource collaborative perception and conflict early warning between the low-frequency load shedding and precise load shedding systems.

[0061] Step 3 of this invention plays a key role in cross-system collaboration in the overall technical solution. It takes the "whether it is in the fine cutting scheme" field in the data model extended in step 1 as the writing target, and calls the "actual pressure plate status" field assigned in step 2 as the basis for weight reduction judgment. It provides overlap markers and weight reduction results for the auxiliary decision-making in step 4 and the scoring and ranking in step 5, which helps to form a complete technical chain of model → perception → collaboration → decision-making.

[0062] Step 4: When performing multiple load shedding operations based on the final load shedding feeder data model, calculate the load shedding completion rate for each round; when the load shedding completion rate of a certain round is not within the expected range of the load shedding completion rate, trigger the dynamic allocation strategy for subsequent rounds.

[0063] Specifically, to obtain the first Planned load shedding during load shedding operation Compared with actual load , No. Actual load of wheel and the first The ratio of the planned load shedding in each round is used as the first Wheel load completion rate When the first Wheel load completion rate If the load shedding rate is not within the expected range, then subsequent actions will be triggered. Dynamic allocation strategy for wheel unloading plan, It is a positive integer greater than 2.

[0064] The load shedding completion rate is an execution deviation indicator that reflects the degree of agreement between the actual load shedding operation and the target load shedding amount. It exists in the load shedding feeder data model. In the example, the expected range of the load shedding completion rate is [100%, 105%], and the optimal load shedding completion rate is 102.5%.

[0065] Step 5: In the dynamic allocation strategy, the optimal range of load shedding completion rate is determined based on the expected range of load shedding completion rate. The deviations of each subsequent round from the optimal range of load shedding completion rate are calculated and sorted according to the real-time cross-sectional data of the power grid. Based on the scores of each feeder in the final load shedding feeder data model and the load shedding plan, the operation sequence of each load shedding feeder is determined. Remote commissioning and decommissioning operations are performed according to the operation sequence. After the operation is completed, the load shedding completion rate is recalculated. If it does not fall within the optimal range of load shedding completion rate, iterative adjustments are made until all remaining rounds fall within the optimal range or there are no adjustable resources. After each iteration, the final load shedding feeder data model is saved.

[0066] Specifically, in the dynamic allocation strategy, the optimal range of load shedding completion rate for each round is determined based on the expected range of load shedding completion rate; according to real-time grid cross-sectional data, the deviation between the load shedding completion rate and the optimal range of load shedding completion rate for subsequent rounds is calculated online, and subsequent rounds are arranged in descending order of absolute value of deviation; based on the assignment of values ​​to the "load type," "importance level," and "number of remote control operations" fields in the final load shedding feeder data model, the score of the load shedding feeder is calculated; based on the scores of all feeders, the allocation score of the load shedding feeder is determined according to the load shedding plan, and the allocation score is used to adjust the "load shedding feeder" field in the load shedding feeder data model. The "Actual Pressure Plate Status" field is updated; in each round after rolling arrangement, the operation sequence of each load shedding feeder is determined according to the allocation score and load of the load shedding feeder; according to the operation sequence of each load shedding feeder, the remote deployment and deactivation operation of the low-frequency load shedding function pressure plate of the feeder is executed; after the operation is completed, the load shedding completion rate of the current round is recalculated. If it does not fall within the optimal range of load shedding completion rate, iterative adjustment is performed until the load shedding completion rate of all remaining rounds falls within the optimal range or there are no adjustable resources; at the same time, after each iteration, a snapshot of all fields of the final load shedding feeder data model is saved to the historical adjustment record table.

[0067] Specifically, step 5 includes: Step 5.1, based on the first The wheel load shedding completion rate and the expected range of the load shedding completion rate are used to determine whether subsequent wheel load shedding operations are feasible; when it is determined to be feasible, the optimal range of the load shedding completion rate is determined based on the expected range of the load shedding completion rate.

[0068] Specifically, step 5.1 includes: Step 5.1.1, based on the first The wheel load shedding completion rate and the expected range of the load shedding completion rate are used to determine the first... The adjustment amount for the +1 round of load shedding operation is determined when the adjustment amount is not greater than the adjustable amount. +1 round load shedding operation is feasible.

[0069] The adjustment amount is defined as the demand signal for correcting the load shedding completion rate. The adjustment amount represents the amount that needs to be adjusted when the actual load shedding completion rate in a certain round deviates from the expected range. For example, if the actual load shedding completion rate in a certain round is 99.5%, the adjustment amount is +0.5%; if the actual load shedding completion rate in a certain round is 106%, the adjustment amount is -1%. The sign and magnitude of the adjustment amount together determine whether the load shedding needs to be increased or decreased in this round, providing a quantitative input for generating adjustment strategies.

[0070] The adjustable quantity is defined as the controllable load capacity that can be used to adjust the load shedding completion rate, including the load value in each round of standby load that can be controlled by means of activation / deactivation pressure plates, remote control switches, etc. The adjustable quantity represents the maximum resource limit that can be used in this round to correct the deviation of the load shedding completion rate. It is the resource constraint basis for judging whether the adjustment quantity can be realized and how to select the adjustment object.

[0071] Step 5.1.2: Determine the adjustment target range and the optimal load shedding completion rate based on the expected range of load shedding completion rate.

[0072] The adjustment target range is the allowable reach interval set for the dynamic adjustment strategy. The expected range for load shedding completion rate is moderately narrowed to provide a buffer for adjustments. In this example, for the expected range of [100%, 105%], the lower limit is narrowed to 100% × 102% = 102%, and the upper limit is narrowed to 105% × 98% = 102.9%. Therefore, the adjustment target range is [102%, 102.9%]. The width of the adjustment target range (0.9%) represents the allowable adjustment error range in actual operation. It is not required that the load shedding completion rate precisely reach a certain point; it is acceptable as long as it falls within this narrow range.

[0073] The optimal load shedding completion rate is the theoretically best target value for adjusting the load shedding completion rate. It is the geometric or arithmetic midpoint of the upper and lower limits of the expected range. Within the range of [100%, 105%], it is 102.5%, which represents the ideal balance point of neither under-shearing nor over-shearing. This value is used as an anchor point at the beginning of the adjustment to guide the load shedding completion rate toward the ideal target.

[0074] Step 5.1.3: Determine the optimal range of load shedding completion rate based on the optimal load shedding completion rate.

[0075] The optimal range for load shedding completion rate is a further refined constraint on the optimal load shedding completion rate. That is, the actual adjusted load shedding completion rate only needs to fall within ±1% of the optimal rate. For an optimal load shedding completion rate of 102.5%, the optimal lower limit is 102.5% × 99% = 101.475%, and the optimal upper limit is 102.5% × 101% = 103.525%. The optimal range for load shedding completion rate is [101.475%, 103.525%]. This optimal range is more lenient than the adjustment target range, allowing for flexible selection between different adjustment strategies and avoiding the rigidity of needing to precisely reach a certain point.

[0076] Step 5.2: Based on the real-time cross-sectional data of the power grid, calculate online the deviation between the load shedding completion rate and the optimal range of the load shedding completion rate for each subsequent round, and arrange the subsequent rounds in descending order of the absolute value of the deviation.

[0077] The load shedding operation with the largest absolute value of the deviation is rolled to the front, and the load shedding operation with the smallest absolute value of the deviation is rolled to the back, so that the load shedding completion rate of each round is controlled first, and then the load shedding completion rate of the entire network is controlled.

[0078] Step 5.3: Calculate the score of the load shedding feeder based on the values ​​assigned to the “Load Type”, “Importance Level”, and “Number of Remote Controls” fields in the final load shedding feeder data model.

[0079] The score for the unloaded feeder is shown in the following formula:

[0080] In the formula, For load reduction feeder The score, For load reduction feeder The value assigned to the "load type" field, For load reduction feeder The assignment of values ​​to the "importance level" field, For load reduction feeder The value assigned to the "Number of Remote Controls" field, , , As a percentage parameter, in the example, =0.7、 =0.25、 =0.05.

[0081] This invention adds an extra remote control count based on load type and importance level. The remote control count is also included in the final score. The maximum number of remote control counts is 10. The remote control count is cleared every day, and 10 points are awarded for each remote control.

[0082] Table 1 Load Type and its Score Table

[0083] In Table 1, commercial load, agricultural load, and generating units are added during the control of the load shedding feeder data model.

[0084] Table 2. Importance Levels and Scores of Loads

[0085] Step 5.4: Based on the scores of all feeders, determine the allocation score of the load reduction feeders according to the load reduction plan, and update the "actual pressure plate status" field in the load reduction feeder data model according to the allocation score.

[0086] Feeders included in the load reduction plan will be designated as in-operation feeders, while feeders not included in the load reduction plan will be designated as backup feeders; for feeders designated as in-operation feeders... If the plan is to deploy a load-reducing feeder The pressure plate will reduce the load on the feeder. Score Subtract 100 points as the allocation score if the plan is to withdraw from the load reduction feeder. The pressure plate will reduce the load on the feeder. Score Add 100 points as the allocation score.

[0087] When allocating load reduction plans in rounds, priority should be given to putting in or cutting in-operation feeders. Then, the scores of in-operation feeders and standby feeders should be adjusted. When a feeder is put in, the score of the in-operation feeder is reduced by 100 points, and the in-operation feeder is allocated a smaller score to ensure that the pressure plate of the in-operation feeder is put in first. When a feeder is taken out, the score of the in-operation feeder is increased by 100 points, and the in-operation feeder is allocated a larger score to ensure that the pressure plate of the in-operation feeder is taken out first.

[0088] Step 5.5: In each round after the rolling arrangement, determine the operating sequence of each load-reducing feeder based on the allocation score and load of the load-reducing feeder, including: 1) When the load shedding feeder is put into operation: the operation sequence of each load shedding feeder is determined by combining the ascending order of the load shedding feeder allocation score and the descending order of the load shedding feeder load; 2) When a load shedding feeder is decommissioned: the operation sequence of each load shedding feeder is determined by combining the descending order of the load shedding feeder allocation score and the descending order of the load shedding feeder load.

[0089] Step 5.6: According to the operation sequence of each load shedding feeder, perform the remote activation / deactivation operation of the low-frequency load shedding function pressure plate of each feeder in turn, and write the operation results into the corresponding "actual pressure plate status" field in the final load shedding feeder data model in real time (0 indicates deactivation, 1 indicates activation); at the same time, after each pressure plate operation is performed, increment the "remote control count" field of the corresponding feeder in the final load shedding feeder data model by 1, and clear the "remote control count" field of all feeders to zero at a fixed time every day to ensure that the dynamic response of the scoring mechanism to the remote control frequency remains effective. After executing the first After the +1 round of load shedding operation, the current value of the "actual pressure plate status" field in the final load shedding feeder data model and the real-time load value of the corresponding feeder are used to recalculate the actual load shedding completion rate for this round. If the load shedding completion rate for this round has fallen into the optimal range of load shedding completion rate determined in step 5.1.3, then the dynamic adjustment for this round is completed, and the original plan or the adjusted plan for subsequent rounds continues to be executed. If the load shedding completion rate for this round still has not fallen into the optimal range, then steps 5.1 to 5.5 are repeated to iterate and adjust subsequent rounds until the load shedding completion rate for all remaining rounds falls into the optimal range or there are no adjustable resources. After each complete dynamic adjustment iteration (i.e., one complete cycle from step 5.1 to step 5.6), a snapshot of all fields of the final load reduction feeder data model is saved to the historical adjustment record table, including but not limited to: each feeder's "distributed power source identifier", "whether the line has a power protection sign", "actual pressure plate status", "whether it is in the fine-cutting scheme", "number of remote control operations", "load type", "importance level", "importance index", as well as the current cycle identifier and adjustment timestamp, which serve as the operational traceability basis for the dynamic adjustment of the load reduction amount.

[0090] In this embodiment, an upgrade to the dynamic control of low-frequency load shedding measures in the three lines of defense for low-frequency load shedding was proposed, addressing issues such as incomplete modeling and low intelligence level in the monitoring of the status of load shedding devices and the completion of load shedding plans by a power grid company's existing low-frequency load shedding monitoring system. Based on the regional smart grid dispatch control system, a dynamic control system for low-frequency load shedding was constructed, building upon the online monitoring and automatic analysis of the third line of defense. The system uses the D5000 platform to read remote signaling and telemetry data of the lines in the load shedding devices and plans, combined with the existing online monitoring and intelligent analysis system for low-frequency load shedding. It monitors in real time changes in the available load for each load shedding cycle in the load shedding plan due to load power fluctuations and changes in load characteristics (reverse transmission, power supply protection measures). If the available load does not meet the shedding requirements, an auxiliary decision-making algorithm is invoked to remotely activate or deactivate the low-frequency load shedding function pressure plates of the line protection devices based on the returned adjustment plan, ensuring that the load shedding cycle and the entire network meet the set shedding range requirements. The system provides online management and control of auxiliary decision-making schemes, enabling online review, one-click execution, dynamic adjustment deviation analysis, and management of historical low-frequency load shedding dynamic adjustment schemes. It also analyzes and monitors overlapping portions of low-frequency load shedding schemes and precision load shedding schemes, reducing potential risks arising from partial overlap. Through load correlation adaptation with the precision load shedding system, it accurately analyzes shared loads and proposes adjustment strategies. A load adjustment monitoring process is established, enabling dynamic management and control of regional power grid low-frequency load shedding schemes through remote feeder commissioning and decommissioning function boards.

[0091] This invention also proposes a novel dynamic adjustment system for load reduction in the third line of defense of a power system, comprising: The load shedding feeder data model extension and correction module is used to acquire the electrical and physical attributes, secondary equipment control attributes, power grid operation management attributes, and process confirmation attributes of the feeders in the load shedding scheme, and to extend and assign values ​​to the load shedding feeder data model. It obtains power flow telemetry data from SCADA and power supply protection tag records from the dispatch management system, and corrects the values ​​of the "distributed power source identifier" and "whether the line has a power supply protection tag" fields in the extended load shedding feeder data model. Based on the correction results, it corrects the value of the "actual pressure plate status" field in the load shedding feeder data model, resulting in the corrected load shedding feeder data model. When the "actual pressure plate status" field in the corrected load shedding feeder data model is 1 and the load shedding feeder data model is in the resource pool, it compares the corrected load shedding feeder data model with the precise load shedding sequence point table based on the load shedding feeder circuit breaker ID. Based on the comparison results, it corrects the value of the "whether it is in the precise shedding scheme" field in the load shedding feeder data model, resulting in the final load shedding feeder data model. The dynamic allocation strategy triggering module is used to calculate the load shedding completion rate of each round when performing multiple rounds of load shedding operations based on the final load shedding feeder data model; when the load shedding completion rate of a certain round is not within the expected range of the load shedding completion rate, the dynamic allocation strategy of subsequent rounds is triggered. The dynamic allocation strategy execution module is used in the dynamic allocation strategy to determine the optimal range of load shedding completion rate based on the expected range of load shedding completion rate, calculate and sort the deviations of each subsequent round from the optimal range of load shedding completion rate based on real-time grid cross-sectional data, determine the operation sequence of each load shedding feeder based on the score of each feeder in the final load shedding feeder data model and the load shedding plan, execute remote commissioning and decommissioning operations according to the operation sequence, recalculate the load shedding completion rate after the operation is completed, and perform iterative adjustments if it does not fall into the optimal range of load shedding completion rate until all remaining rounds fall into the optimal range or there are no adjustable resources. After each iteration, the final load shedding feeder data model is saved.

[0092] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0093] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0094] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0095] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A novel method for dynamically adjusting the load reduction of the third line of defense in a power system, characterized in that, include: Obtain the electrical and physical attributes, secondary equipment control attributes, power grid operation management attributes, and process confirmation attributes of the feeders in the load reduction scheme, and expand and assign values ​​to the load reduction feeder data model; Power flow telemetry data is obtained from the SCADA data acquisition and monitoring system, and power supply protection tag records are obtained from the dispatch management system. The "distributed power source identifier" field and the "whether the line is under power supply protection tag" field in the expanded load reduction feeder data model are assigned and corrected. Based on the assignment and correction results, the "actual pressure plate status" field in the load reduction feeder data model is assigned and corrected to obtain the corrected load reduction feeder data model. When the "Actual Pressure Plate Status" field in the modified load shedding feeder data model is 1 and the load shedding feeder data model is in the resource pool, the modified load shedding feeder data model is compared with the precise load shedding sequence point table based on the load shedding feeder circuit breaker identification ID; according to the comparison result, the "Whether it is in the precision shedding scheme" field in the load shedding feeder data model is assigned a value to correct it, and the final load shedding feeder data model is obtained. When performing multiple load shedding operations based on the final load shedding feeder data model, the load shedding completion rate of each round is calculated; when the load shedding completion rate of a certain round is not within the expected range of the load shedding completion rate, the dynamic allocation strategy of subsequent rounds is triggered. In the dynamic allocation strategy, the optimal range of load shedding completion rate is determined based on the expected range of load shedding completion rate. The deviations of subsequent rounds from the optimal range of load shedding completion rate are calculated and sorted according to the real-time cross-sectional data of the power grid. Based on the scores of each feeder in the final load shedding feeder data model and the load shedding plan, the operation sequence of each load shedding feeder is determined. Remote commissioning and decommissioning operations are performed according to the operation sequence. After the operation is completed, the load shedding completion rate is recalculated and iterative adjustments are made if it does not fall within the optimal range of load shedding completion rate until all remaining rounds fall within the optimal range or there are no adjustable resources. The final load shedding feeder data model is saved after each iteration.

2. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 1, characterized in that, The electrical and physical attributes of the feeder, the secondary equipment control attributes, the power grid operation management attributes, and the process confirmation attributes are mapped to structured logical fields and added to the load shedding feeder data model. Among them, the electrical and physical attributes include: load type and distributed power source identification; the secondary equipment control attributes include: controllable status of the pressure plate and remote control execution result; the power grid operation management attributes include: power supply protection tag and fine-cutting scheme overlap identification; and the process confirmation attributes include: status update time and confirmer.

3. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 2, characterized in that, The extended operations of the unloaded feeder data model include: 1) Expanding within the existing domain: 1.1) Expand "Spare Field 3" to "Distributed Power Source Identifier", where 0 indicates no distributed power source, 1 indicates distributed power source, and 2 indicates distributed voltage source. 1.2) Expand the "Spare Field 8" field to the "Load Type" field, where 1 represents high-risk users, 2 represents important users, 3 represents distributed power lines, 4 represents high proportion of residential loads, 5 represents medium proportion of residential loads, 6 represents low proportion of residential loads, 7 represents industrial loads, 8 represents commercial loads, 9 represents agricultural loads, and 10 represents generating units. 2) Expanding within a new domain: 2.1) Added a field "Whether the line has a power supply protection sign", where 0 indicates no sign and 1 indicates a sign; 2.2) Added a "Controllable pressure plate" field, where 1 indicates controllable and 0 indicates uncontrollable, with 0 as the default. 2.3) Add a "Remote Control Failure Flag" field, which defaults to 0. When the preset fails or the control fails during the remote control process, the field will be set to 1. After the remote control test is successful, manual reset will be performed. 2 indicates that no reset will be performed. 2.4) Add a new field "Whether the load is controllable", where 1 indicates controllable and 0 indicates uncontrollable; 2.5) Added "Whether it is in the fine cutting scheme", 1 indicates yes, 0 indicates no; 2.6) Added a "Whether in resource pool" field, where 1 indicates yes and 0 indicates no; 2.7) Added a "Distributed Power Supply Update Time" field, which directly uses the timestamp; 2.8) Added a "Power Supply Status Update Time" field, which directly uses the timestamp; 2.9) Added a "Distributed Power Source Confirmation Status" field, where 1 indicates confirmation and 0 indicates non-confirmation, which is updated by the human-machine interface; 2.10) Added a "Power Supply Confirmation Status" field, where 1 indicates confirmation and 0 indicates no confirmation; 2.11) Added the "Distributed Power Source Confirmer" field, which is updated via the human-machine interface; 2.12) Added a "Power Supply Confirmation Person" field, which is updated via the human-machine interface; 2.13) Added the "Actual Pressure Plate Status" field, where 0 indicates exit, 1 indicates engagement, 2 indicates no associated pressure plate signal, and 3 indicates multiple pressure plates; 2.14) Added a "Remote Control Count" field, which defaults to 0. Each remote control operation increments the count by 1, with a maximum of 10 remote control counts. The remote control count is cleared daily. 2.15) Added a "Importance Level" field; 2.16) Added the "Importance Index" field.

4. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 3, characterized in that, Power flow telemetry data is obtained from SCADA and power supply protection tag records are obtained from the dispatch management system. The "Distributed Power Source Identifier" and "Whether the Line Has a Power Supply Protection Tag" fields in the expanded load shedding feeder data model are automatically assigned values, including: Power flow telemetry data is obtained from SCADA to monitor the power flow direction of feeders in real time. For feeders with reversed power flow and reduced load, the feeder is identified as a distributed power source feeder, and the "distributed power source identifier" field in the extended reduced load feeder data model is automatically assigned a value of 1. The system retrieves power supply guarantee tag records from the dispatch management system, queries the power supply guarantee feeder switch ID from the power supply guarantee tag records, and automatically assigns the value 1 to the "Whether the line has a power supply guarantee tag" field in the expanded load reduction feeder data model when the power supply guarantee feeder switch ID matches the load reduction feeder switch ID.

5. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 4, characterized in that, Based on the assignment results, the "Actual Pressure Plate State" field in the unloaded feeder data model is dynamically corrected, including: Based on the assigned load shedding feeder data model, dynamic correction of the load shedding feeder cut-off attributes is performed, including: obtaining the pressure plate status information from the protection device management unit; if the "distributed power source identifier" field or the "line whether power protection sign is attached" field in the extended load shedding feeder data model is 1, then the corresponding feeder performs the load shedding pressure plate exit operation, and the "actual pressure plate status" field is set to 0; if the "distributed power source identifier" field and the "line whether power protection sign is attached" field in the extended load shedding feeder data model are both 0, then the "actual pressure plate status" field is set to 1.

6. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 5, characterized in that, If the "Actual Pressure Plate Status" field in the load shedding feeder data model is 0, a load shedding undercut alarm event will be generated.

7. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 1, characterized in that, When the "Actual Pressure Plate Status" field in the corrected load shedding feeder data model is 1 and the "Whether in Resource Pool" field is 1, a comparison is performed between the corrected load shedding feeder data model and the accurate load shedding sequence point table based on the load shedding feeder circuit breaker ID, including: If the load shedding feeder circuit breaker ID is only in the revised load shedding feeder data model, then the "Whether it is in the fine-cutting scheme" field in the revised load shedding feeder data model is set to 0; if the load shedding feeder circuit breaker ID is only in the precise load shedding sequence point table, then the "Whether it is in the fine-cutting scheme" field in the revised load shedding feeder data model is set to 1; if the load shedding feeder circuit breaker ID exists in both the revised load shedding feeder data model and the precise load shedding sequence point table, then a fine-cutting overlap alarm event is generated.

8. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 1, characterized in that, Get the Planned load shedding during load shedding operation Compared with actual load , No. Actual load of wheel and the first The ratio of the planned load shedding in each round is used as the first Wheel load completion rate When the first Wheel load completion rate If the load shedding rate is not within the expected range, then subsequent actions will be triggered. Dynamic allocation strategy for wheel unloading plan, It is a positive integer greater than 2.

9. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 1, characterized in that, In the dynamic allocation strategy, the optimal range of load shedding completion rate for each round is determined based on the expected range of load shedding completion rate. Based on real-time grid cross-sectional data, the deviation between the load shedding completion rate and the optimal range for each subsequent round is calculated online, and the subsequent rounds are arranged in descending order of absolute deviation value. Based on the assigned values ​​of the "load type," "importance level," and "number of remote control operations" fields in the final load shedding feeder data model, the score of the load shedding feeder is calculated. Based on the scores of all feeders, the allocation score of the load shedding feeder is determined according to the load shedding plan, and the "actual pressure plate status" field in the load shedding feeder data model is updated based on the allocation score. In each round after the rolling arrangement, the operation sequence of each load shedding feeder is determined based on the allocation score of the load shedding feeder and the load of the load shedding feeder. Following the operational sequence of each load shedding feeder, remotely engage / disengage the low-frequency load shedding function pressure plate of the feeder. After the operation is completed, the load shedding completion rate of the current cycle is recalculated. If it does not fall within the optimal range of load shedding completion rate, iterative adjustments are made until the load shedding completion rate of all remaining cycles falls within the optimal range or there are no adjustable resources. At the same time, after each iteration, a snapshot of all fields of the final load shedding feeder data model is saved to the historical adjustment record table.

10. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 9, characterized in that, Based on the The wheel load shedding completion rate and the expected range of the load shedding completion rate are used to determine whether subsequent wheel load shedding operations are feasible; when it is determined to be feasible, the optimal range of the load shedding completion rate is determined based on the expected range of the load shedding completion rate. Based on real-time grid cross-sectional data, the deviation between the load shedding completion rate and the optimal range of the load shedding completion rate for each subsequent round is calculated online, and the subsequent rounds are arranged in descending order of the absolute value of the deviation. Based on the values ​​assigned to the "Load Type", "Importance Level", and "Number of Remote Controls" fields in the final load shedding feeder data model, the score of the load shedding feeder is calculated. Based on the scores of all feeders, the allocation score of the load reduction feeders is determined according to the load reduction plan, and the "actual pressure plate status" field in the load reduction feeder data model is updated by assigning values ​​according to the allocation scores. In each round after the rolling arrangement, the operation sequence of each load shedding feeder is determined based on the allocation score of the load shedding feeder and the load of the load shedding feeder.

11. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 10, characterized in that, Based on the The wheel load shedding completion rate and the expected range of the load shedding completion rate are used to determine the first... The adjustment amount for the +1 round of load shedding operation is determined when the adjustment amount is not greater than the adjustable amount. +1 round load shedding operation is feasible; Determine the adjustment target range and the optimal load shedding completion rate based on the expected range of the load shedding completion rate; The optimal range of load shedding completion rate is determined based on the optimal load shedding completion rate.

12. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 10, characterized in that, The score for the unloaded feeder is shown in the following formula: In the formula, For load reduction feeder The score, For load reduction feeder The value assigned to the "load type" field, For load reduction feeder The assignment of values ​​to the "importance level" field, For load reduction feeder The value to be assigned to the "Number of Remote Controls" field. , , This is a percentage parameter.

13. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 12, characterized in that, Feeders included in the load reduction plan will be designated as in-operation feeders, while feeders not included in the load reduction plan will be designated as backup feeders; for feeders designated as in-operation feeders... If the plan is to deploy a load-reducing feeder The pressure plate will reduce the load on the feeder. Score Subtract 100 points as the allocation score if the plan is to withdraw from the load reduction feeder. The pressure plate will reduce the load on the feeder. Score Add 100 points as the allocation score.

14. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 13, characterized in that, When load shedding feeders are put into operation: the operating sequence of each load shedding feeder is determined by combining the ascending order of the load shedding feeder allocation score and the descending order of the load shedding feeder load. When a load shedding feeder is decommissioned: the operation sequence of each load shedding feeder is determined by combining the descending order of the load shedding feeder allocation score and the descending order of the load shedding feeder load.

15. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 14, characterized in that, According to the operation sequence of each load shedding feeder, the remote activation and deactivation operation of the low-frequency load shedding function pressure plate of each feeder is executed one by one, and the operation results are written to the corresponding "actual pressure plate status" field in the final load shedding feeder data model in real time. At the same time, after each pressure plate operation is executed, the "remote control count" field of the corresponding feeder in the final load shedding feeder data model is incremented by 1, and the "remote control count" field of all feeders is cleared to zero at a fixed time every day.

16. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 15, characterized in that, After executing the first After the +1 round of load shedding, the actual load shedding completion rate for this round is recalculated using the current value of the "actual pressure plate status" field in the final load shedding feeder data model and the real-time load value of the corresponding feeder. If the load shedding completion rate for this round has fallen into the optimal range, the dynamic adjustment for this round is complete, and the original or adjusted plan for subsequent rounds continues to be executed. If the load shedding completion rate for this round has not yet fallen into the optimal range, the dynamic allocation strategy for subsequent rounds is executed, and the subsequent rounds are iteratively adjusted until the load shedding completion rate for all remaining rounds falls into the optimal range or there are no adjustable resources.

17. The method for dynamically adjusting the load reduction of the third line of defense in a novel power system according to claim 16, characterized in that, After each complete dynamic adjustment iteration, a snapshot of all fields of the final load shedding feeder data model is saved to the historical adjustment record table, including: "distributed power source identifier", "whether the line is equipped with a power protection sign", "actual pressure plate status", "whether it is in the fine-cutting scheme", "number of remote control operations", "load type", "importance level", "importance index", as well as the current round identifier and adjustment timestamp.

18. A novel dynamic adjustment system for the load reduction of the third line of defense in a power system, used to implement the dynamic adjustment method for the load reduction of the third line of defense in a power system as described in any one of claims 1 to 17, characterized in that, include: The load shedding feeder data model extension and correction module is used to acquire the electrical and physical attributes, secondary equipment control attributes, power grid operation management attributes, and process confirmation attributes of the feeders in the load shedding scheme, and to extend and assign values ​​to the load shedding feeder data model. It obtains power flow telemetry data from SCADA and power supply protection tag records from the dispatch management system, and corrects the values ​​of the "distributed power source identifier" and "whether the line has a power supply protection tag" fields in the extended load shedding feeder data model. Based on the correction results, it corrects the value of the "actual pressure plate status" field in the load shedding feeder data model, resulting in the corrected load shedding feeder data model. When the "actual pressure plate status" field in the corrected load shedding feeder data model is 1 and the load shedding feeder data model is in the resource pool, it compares the corrected load shedding feeder data model with the precise load shedding sequence point table based on the load shedding feeder circuit breaker ID. Based on the comparison results, it corrects the value of the "whether it is in the precise shedding scheme" field in the load shedding feeder data model, resulting in the final load shedding feeder data model. The dynamic allocation strategy triggering module is used to calculate the load shedding completion rate of each round when performing multiple rounds of load shedding operations based on the final load shedding feeder data model; when the load shedding completion rate of a certain round is not within the expected range of the load shedding completion rate, the dynamic allocation strategy of subsequent rounds is triggered. The dynamic allocation strategy execution module is used in the dynamic allocation strategy to determine the optimal range of load shedding completion rate based on the expected range of load shedding completion rate, calculate and sort the deviations of each subsequent round from the optimal range of load shedding completion rate based on real-time grid cross-sectional data, determine the operation sequence of each load shedding feeder based on the score of each feeder in the final load shedding feeder data model and the load shedding plan, execute remote commissioning and decommissioning operations according to the operation sequence, recalculate the load shedding completion rate after the operation is completed, and perform iterative adjustments if it does not fall into the optimal range of load shedding completion rate until all remaining rounds fall into the optimal range or there are no adjustable resources. After each iteration, the final load shedding feeder data model is saved.

19. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-17.

20. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1-17.

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