Constant value remote dynamic operation and maintenance system and method

Abstract

The invention discloses a constant value remote dynamic operation and maintenance system and method, and belongs to the technical field of intelligent substation operation and maintenance, and the system comprises a cloud cooperative control unit, an edge agent unit and a terminal constant value processing unit which construct a cooperative operation and maintenance architecture through a communication network. Wherein the cloud cooperative control unit is deployed in a regional regulation and control center, the edge agent unit is deployed in a field station, and the terminal constant value processing unit is integrated in a relay protection device. Constant value remote management is realized through a cloud side-end collaborative architecture, operation and maintenance personnel do not need to be on-site on duty, the problem of time consumption of going back and forth on site in a traditional mode is solved, and manpower and traffic costs are reduced; the whole course of constant value modification, checking and tracing is automatic, manual intervention is reduced, the single constant value adjustment period is shortened from several hours to the minute level, and the operation and maintenance response speed is improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent substation operation and maintenance technology, and in particular to a remote dynamic operation and maintenance system and method for fixed values. Background Technology

[0002] With the large-scale construction of substations, the workload of modifying relay protection device settings has increased dramatically, mainly in three aspects: traveling to and from the site, organizing the implementation of measures, and verifying settings. Relying on traditional manual on-site setting changes not only exacerbates operation and maintenance costs but also inevitably leads to setting errors. Simultaneously, the integration of new energy sources has resulted in significant changes in power flow and load in the grid, rendering the existing manual offline setting method inadequate for the dynamic needs of grid operation. Therefore, grid operation and maintenance urgently require a remote operation and maintenance system for relay protection settings with functions such as remote online modification, remote online verification, dynamic early warning, setting, and verification. Currently, some master stations have achieved remote setting modification through MMS communication, but most lack double confirmation of setting modifications, online monitoring of setting rationality, and digital twin virtual verification. Furthermore, they cannot achieve dynamic setting and download verification, and their efficiency and accuracy in setting operation and maintenance need improvement. Summary of the Invention

[0003] To address the problems of low efficiency, poor accuracy, insufficient security, and weak dynamic adaptability in traditional methods of modifying settings, this invention provides a remote dynamic operation and maintenance system and method for substation settings. This system solves the problem of remote operation and maintenance of substation settings, significantly improves the correctness and efficiency of setting modification and verification, and enables online monitoring and digital twin virtual verification of setting rationality. It also achieves dynamic setting and download verification.

[0004] The technical solution adopted by the fixed-value remote dynamic operation and maintenance system and method of the present invention is as follows: A remote dynamic operation and maintenance system for setting values ​​includes a cloud-based collaborative control unit, an edge agent unit, and a terminal setting value processing unit. The three units are connected through a communication network to form a collaborative operation and maintenance architecture. The cloud-based collaborative control unit is deployed in a regional control center, the edge agent unit is deployed in a field station, and the terminal setting value processing unit is integrated into a relay protection device.

[0005] A further improvement to the technical solution of the present invention is that the cloud-based collaborative control unit includes: The data acquisition module is used to collect electrical quantity data, equipment status information, fault log files, and environmental perception data at the field site. The data storage module is used to store collected data, digital twin model data, and fixed-value full lifecycle data; The security verification module uses hardware encryption technology to achieve identity authentication, role-based authorization, and operation permission control. The digital twin module is used to construct a primary model of the power grid topology and a secondary protection logic model, forming a virtual mirror synchronized with the physical power grid. The virtual verification module is used to simulate various fault scenarios and operating conditions to perform simulation verification of the setpoint scheme; The dynamic early warning module is used to monitor the power grid's operating status and the matching degree of the setpoints, predict operating trends, and generate setpoint optimization strategies. The fixed value management module is used for fixed value recall, modification, version comparison, and historical tracing; The setpoint maintenance module is used for safe setting of settings, monitoring of device actions, and optimization of closed-loop control.

[0006] A further improvement of the technical solution of the present invention is that the virtual verification module includes a pre-set fault scenario library and a parallel simulation mechanism; wherein, the fault scenario library includes in-zone / out-zone faults, complex evolving faults and special operating conditions; the simulation process includes real-time operating condition initialization, setting scheme injection, multi-scenario parallel electromagnetic transient simulation, action behavior monitoring and quantitative evaluation report generation, and the evaluation report includes action accuracy, risk index and protection coordination relationship analysis.

[0007] A further improvement to the technical solution of the present invention lies in the fact that the working mechanism of the dynamic early warning module includes: Real-time monitoring: Analyze the matching degree between power grid operating conditions and setpoints, and generate setpoint approach warnings or critical state warnings through load current comparison and impedance trajectory monitoring; Trend forecasting: Based on historical data, meteorological information, and new energy power data, predict the load change curve and the evolution trend of power grid operation mode in the next 24 hours; Setpoint optimization: Under the premise of satisfying reliability and selectivity, generate initial optimized setpoints, and generate 1-3 sets of optimal setpoint adjustment strategies through multi-scheme simulation evaluation; Strategy Recommendation: Outputs an adjustment strategy report that includes profit analysis and risk quantification, showing the trade-offs between the optimization objectives of different options.

[0008] A further improvement of the technical solution of the present invention is that the security verification module supports three-level role classification, including operator, auditor and administrator. Operator only has the authority to view and issue fixed values, auditor has the authority to review fixed value schemes, and administrator has the authority to configure the system and allocate permissions. Identity authentication adopts a combination of hardware encryption lock and password verification method, and operation records are left trace throughout the process.

[0009] A further improvement of the technical solution of the present invention is that the edge agent unit has local decision-making and collaborative relay functions. After receiving the instructions of the cloud collaborative control unit, it completes the local verification of the set value based on the real-time data on site. When the cloud-edge communication is interrupted, it autonomously performs emergency set value adjustment or lockout operation to ensure the safe operation of the on-site equipment.

[0010] A further improvement of the technical solution of the present invention is that: the terminal setting processing unit includes a setting delay execution module and a dual confirmation feedback module, and the dual setting area includes a running setting area and a standby setting area; the setting modification instruction issued remotely is only written to the standby setting area, and a configurable security delay timer is started, during which the setting in the running setting area is used; before the timer ends, a confirmation switching instruction or a cancellation instruction can be received, and after switching, dual confirmation feedback is achieved through hash value verification and standardized file transmission.

[0011] A method for fixed-value remote dynamic operation and maintenance includes the following steps: S1, the cloud-based collaborative control unit constructs primary and secondary power grid models through a digital twin module, completing the virtual image initialization; S2. The data acquisition module collects real-time data from the site, stores it in the data storage module, and updates the digital twin model synchronously. S3, the dynamic early warning module monitors the power grid operation status, combines historical data to make trend predictions, and calls the virtual verification module to verify the rationality of the current set value; S4. If there is a risk of mismatch in the set value, the dynamic early warning module generates the optimal set value adjustment strategy, which is then approved by the security verification module and distributed to the edge agent unit by the set value operation and maintenance module. S5. After receiving the setting information, the edge agent unit performs on-site verification based on real-time data. If there is no abnormality, it forwards the information to the terminal setting processing unit. S6. The terminal setting processing unit writes the new setting into the standby setting area, starts the security delay timer, and provides real-time feedback on the setting area status and countdown information through the "heartbeat" protocol. S7. After confirmation during the timing period, the terminal setting processing unit switches to the new setting operation and sends back the verification information through the double confirmation feedback module; if a cancellation command is received, the standby setting area is cleared and the original setting operation is maintained. The S8 cloud-based collaborative control unit receives feedback information and completes version updates and historical tracing through the fixed value management module, forming a closed-loop operation and maintenance system.

[0012] A further improvement of the above technical solution of the present invention is that the modeling process of the digital twin module in step S1 includes: S1.1. Perform object-oriented modeling of primary equipment, assign unique identifiers to equipment such as generators, transformers, and transmission lines, and configure electrical parameters consistent with those of the physical equipment; S1.2. Based on the real-time status of switches / disconnectors, construct dynamically updated power grid topology connections; S1.3 Utilize real-time power flow and load data to construct a dynamic power flow profile of the entire network and form the initial operating conditions of the model; S1.4 Construct a secondary protection logic model, simulate the measurement elements and logic judgment process of the protection device, and inject the current running set value or the set value scheme to be modified; S1.5. Implement interactive simulation between the primary and secondary models. Inject the electrical quantity data of the primary model into the secondary model, and use the action signals of the secondary model to drive the topology adjustment of the primary model in reverse.

[0013] The workflow of the dynamic early warning module in step S3 includes: The further improvement of the above technical solution of the present invention is as follows: S3.1, monitoring and early warning: by collecting data in real time, continuously analyze the matching degree between the current power grid operating condition and the operating setting; monitor the load current of the protected element in real time and compare it with the overcurrent setting, differential start setting, etc. in the setting sheet; when the load current continues to approach these setting values, generate a setting value approach warning to indicate that the setting margin is insufficient; for distance protection, continuously calculate and measure the impedance and draw its trajectory on the impedance complex plane; observe the relative position of the impedance trajectory and the protection characteristics. If the trajectory lingers near the operating boundary for a long time, the warning setting is in a critical state. S3.2 Trend Forecasting: Based on historical load data, date type, meteorological information, and renewable energy power, predict the load change curve for the next few hours to 24 hours; S3.3, Operation Mode Evolution Prediction: Based on the predicted load and new energy distribution, drive the digital twin module to perform power flow calculations to predict the power flow distribution, voltage level and potential overloaded / overloaded equipment of the power grid at a specific point in the future. S3.4 Virtual Verification: The monitored state and the predicted state are analyzed for the rationality of the current set value using the virtual verification module. If an anomaly occurs, the set value is optimized. S3.5, Setpoint Generation: Prioritize selectivity while ensuring reliability, and then maximize sensitivity to generate initial optimized setpoints; S3.6, Setpoint Optimization: Within the limits permitted by the procedures and the safety of the equipment, a search is conducted, and multiple candidate setpoint schemes are generated based on the initial optimized setpoints. Each scheme is rapidly simulated in the digital twin module and the virtual verification module for the predicted operating mode and the preset fault set, and its score on each optimization objective is evaluated. S3.7 Strategy Recommendation and Risk Quantification: After optimization, the system will generate a dynamic fixed value adjustment strategy recommendation report. Its core contents include: providing 1-3 optimal fixed value adjustment schemes, clearly showing the trade-offs of different schemes on multiple optimization objectives in the form of charts, clearly informing about the benefits after adjustment, and clearly pointing out any side effects that may be brought about by the adjustment.

[0014] The technological advancements achieved by this invention due to the adoption of the above technical solutions are as follows: This invention enables remote management of setpoints through a cloud-edge-device collaborative architecture, eliminating the need for on-site maintenance personnel and solving the time-consuming problem of traveling to and from the site in the traditional model, thus reducing manpower and transportation costs. The entire process of settingpoint modification, verification, and traceability is automated, reducing manual intervention and shortening the cycle of a single settingpoint adjustment from several hours to minutes, thereby improving the speed of operation and maintenance response.

[0015] This invention integrates digital twin technology to construct a virtual verification environment, which can simulate various fault scenarios and operating conditions such as short circuits, oscillations, and CT saturation, and identify the risk of unreasonable settings in advance to avoid protection failure or false operation; the dynamic early warning module realizes adaptive optimization of settings based on real-time data and trend prediction, ensuring that the settings always match the power grid operating status and solving the problem of power flow fluctuation adaptation caused by the access of new energy sources.

[0016] This invention adopts a dual-value zone architecture and a delayed execution mechanism. New values ​​will not take effect immediately after being issued, and a security confirmation window is reserved. Operation and maintenance personnel can perform secondary confirmation based on the virtual verification results, which can avoid accidental operation. The dual confirmation feedback mechanism ensures the consistency between value issuance and execution through hash value verification and standardized file transmission. The local decision-making capability of the edge agent unit can autonomously perform emergency operations when cloud-edge communication is interrupted, ensuring the continuous and safe operation of the power grid. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of a fixed-value remote dynamic operation and maintenance system according to the present invention; Figure 2 This is a schematic diagram of the cloud-based collaborative control unit modules of a fixed-value remote dynamic operation and maintenance system according to the present invention; Figure 3 This is a flowchart of a fixed-value remote dynamic operation and maintenance method according to the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings. In the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily obscuring the concept of this invention.

[0019] Example 1 like Figure 1 As shown, this embodiment provides a fixed-value remote dynamic operation and maintenance system, including: Cloud-based collaborative control unit: Deployed in the provincial or network dispatch center, it provides unified management of setpoints across the entire region, digital twin simulation, virtual testing, dynamic early warning, modification strategy formulation, and historical data analysis functions.

[0020] Edge agent unit: Deployed in various substations or new energy power plants, it serves as a bridge between the cloud and protection devices, enabling local verification of regional settings and emergency interlocking.

[0021] Terminal setting processing unit: Add functions such as delayed execution of setting modification and double confirmation information return to the existing relay protection device.

[0022] like Figure 2 As shown, the cloud-based collaborative control unit includes the following modules; Data acquisition module: Collects power flow, load, switch and disconnector positions, protection SOE information, protection setting information, fault recording files, meteorological information, etc. of each substation; Data storage module: Stores information collected by the data acquisition module, the model built by the digital twin module, and historical value management module information, etc. Security verification module: Implements identity authentication and access control based on hardware encryption, and supports role-based hierarchical management (such as operator, administrator, auditor, etc.); Digital twin module: Constructs a primary model of the power grid topology and a secondary protection logic model, and builds a virtual mirror that pulses synchronously with the physical power grid based on real-time collected data; Virtual verification module: Before the settings are officially issued, the system can simulate various fault scenarios (such as short circuit, oscillation, and open circuit) in the twin, comprehensively evaluate the behavior of the new setting scheme under various extreme conditions, and discover and avoid the risk of protection failure or false operation caused by unreasonable settings in advance. Dynamic early warning module: Based on real-time collected data, it senses changes in the power grid operation mode and performs trend prediction based on stored historical data. The digital twin will dynamically calculate and recommend the optimal setpoint adjustment strategy based on preset optimization goals. The setting management module provides functions for setting recall, modification, version comparison, and history tracing; it is used to compare the modified and protected settings returned with the setting file to ensure information consistency. Fixed value operation and maintenance module: Securely distributes fixed values ​​through edge agent, continuously monitors the action behavior of protection devices, and feeds the results back to the digital twin to form a learning loop for continuous optimization.

[0023] The edge agent unit has on-site decision-making capabilities. After receiving instructions from the cloud, it can quickly verify based on real-time data from its local station, and autonomously perform emergency setting modifications or locking operations when communication with the cloud is interrupted.

[0024] In this embodiment, the terminal setting processing unit improves upon the existing relay protection device by adding a setting delay execution module and a dual confirmation feedback module.

[0025] The setpoint delay execution module adopts a dual setpoint area architecture. In addition to the traditional running setpoint area, a dedicated standby setpoint area is added inside the device. All remotely issued setpoint modifications are first written to, and only to, the standby setpoint area. Once a new setpoint is written to the standby setpoint area, the device automatically starts a configurable safety delay timer. The new setpoint will not take effect until this timer reaches zero, and the device continues to operate normally using the original setpoint in the running setpoint area. The device continuously reports its setpoint area status and remaining safety countdown time to the edge agent unit and the cloud-based collaborative control unit via a "heartbeat" protocol. During the countdown, maintenance personnel can view the status on the remote maintenance interface. The system can check the new settings at any time and reconfirm them by combining the pre-drill report from the digital twin module and the information from the dynamic early warning module. If the new settings are deemed correct, a confirmation switching command can be issued through the platform. After the terminal setting processing unit switches the settings, it calculates the hash value of the new settings in each area of ​​the device through the dual confirmation feedback module and sends it back via the MMS protocol. The new setting information is then returned to the edge agent unit and the cloud collaborative control unit in the form of an XML file. If the maintenance personnel or the system AI finds that the new settings pose a risk within the countdown, a cancellation command can be issued at any time. After receiving the command, the device will automatically clear the standby setting area and stop the timer. The entire process has no impact on operation.

[0026] In this embodiment, the digital twin module of the cloud-based collaborative control unit includes: Step 1: Object-oriented modeling of primary equipment, defining generators, transformers, transmission lines, circuit breakers, disconnect switches, busbars, loads, etc., as software objects with unique IDs and rich attributes in virtual space, and configuring each component with electrical parameters consistent with reality; Step 2: Construct a topology connection relationship consistent with the real power grid, and dynamically change the power grid connection relationship according to the real-time collected switch / disconnector status; Step 3: Construct a dynamic power flow profile of the entire network based on the collected power flow and load data to form the initial operating conditions of the model; Step 4: Construct a secondary protection logic model. For each specific protection device (such as line differential protection, distance protection, transformer differential protection), simulate its measuring elements and complete logic judgment process, and seamlessly inject the current setting sheet or the new setting scheme to be modified in the physical device into the corresponding virtual protection model to ensure that the basis of the logic operation is completely consistent with the real world. Step 5: Inject the current and voltage simulated by the primary model into the secondary model; the secondary model performs calculations based on its internal logic and setpoints to determine whether the action conditions are met; if action is taken, the secondary model sends a virtual trip signal to the primary model; upon receiving the signal, the primary model immediately changes the topology, thereby changing the power flow distribution and realizing the simulation of the chain reaction of the protection action on the power grid.

[0027] In this embodiment, the virtual verification module of the cloud-based collaborative control unit includes: Step 1: The pre-set fault scenario library includes: in-zone / out-zone faults (metallic, through transition resistance), complex faults (transitional, evolving faults), special operating conditions (system oscillation, non-full-phase operation, CT saturation), etc. Step 2: Real-time operating condition initialization: Use the current real-time power flow section of the power grid as the initial state for all simulation cases; Step 3: Parallel simulation calculation: Inject the set values ​​into the quadratic model and perform parallel electromagnetic transient simulation on all selected fault scenarios; Step 4: Monitor the virtual action behavior of each protection device, the virtual breaking sequence of the circuit breaker, and the stability of the system after the fault is cleared (such as voltage and frequency recovery).

[0028] Step 5: Generate a quantitative evaluation report: After the simulation is completed, a detailed report will be automatically generated, including the accuracy of actions, risk index, and analysis of the coordination relationship between upstream and downstream protection systems.

[0029] In this embodiment, the dynamic early warning module of the cloud-based collaborative control unit includes: Step 1: Monitoring and Early Warning: Continuously analyze the matching degree between the current power grid operating conditions and the operating settings through real-time data collection; monitor the load current of the protected components in real time and compare it with the overcurrent settings, differential start settings, etc. in the setting sheet; when the load current continues to approach these settings, a setting approach warning is generated, indicating insufficient setting margin; for distance protection, continuously calculate and measure the impedance, and plot its trajectory on the impedance complex plane; observe the relative position of the impedance trajectory and the protection characteristics. If the trajectory lingers near the operating boundary for a long time, the warning setting is in a critical state. Step 2: Trend Forecasting: Based on historical load data, date type, meteorological information, and renewable energy power, predict the load change curve for the next few hours to 24 hours; Step 3: Operation mode evolution prediction: Based on the predicted load and renewable energy distribution, drive the digital twin module to perform power flow calculations to predict the power flow distribution, voltage level and potential overloaded / overloaded equipment of the power grid at a specific point in the future; Step 4: Virtual Verification: The monitored status and the predicted status are analyzed for the rationality of the current set value using the virtual verification module. If an anomaly occurs, the set value is optimized. Step 5: Value generation: Prioritize selectivity while ensuring reliability, and then maximize sensitivity to generate initial optimized values; Step 6: Setpoint Optimization: Within the limits permitted by the procedures and the safety of the equipment, a search is conducted to generate multiple candidate setpoint schemes based on the initial optimized setpoints. Each scheme is rapidly simulated in the digital twin module and the virtual verification module for the predicted operating mode and the preset fault set, and its score on each optimization objective is evaluated. Step 7: Strategy Recommendation and Risk Quantification: After optimization, the system will generate a dynamic fixed-value adjustment strategy recommendation report. Its core contents include: providing 1-3 optimal fixed-value adjustment schemes, clearly showing the trade-offs of different schemes on multiple optimization objectives in the form of charts, clearly informing about the benefits after adjustment, and clearly pointing out any side effects that may be brought about by the adjustment.

[0030] Example 2 like Figure 3 As shown, this embodiment provides a fixed-value remote dynamic operation and maintenance system, including the following steps: S1, the cloud-based collaborative control unit constructs primary and secondary power grid models through a digital twin module, completing the virtual image initialization; S2. The data acquisition module collects real-time data from the site, stores it in the data storage module, and updates the digital twin model synchronously. S3, the dynamic early warning module monitors the power grid operation status, combines historical data to make trend predictions, and calls the virtual verification module to verify the rationality of the current set value; S4. If there is a risk of mismatch in the set value, the dynamic early warning module generates the optimal set value adjustment strategy, which is then approved by the security verification module and distributed to the edge agent unit by the set value operation and maintenance module. S5. After receiving the setting information, the edge agent unit performs on-site verification based on real-time data. If there is no abnormality, it forwards the information to the terminal setting processing unit. S6. The terminal setting processing unit writes the new setting into the standby setting area, starts the security delay timer, and provides real-time feedback on the setting area status and countdown information through the "heartbeat" protocol. S7. After confirmation during the timing period, the terminal setting processing unit switches to the new setting operation and sends back the verification information through the double confirmation feedback module; if a cancellation command is received, the standby setting area is cleared and the original setting operation is maintained. S8, the cloud-based collaborative control unit receives feedback information and completes version updates and historical traceability through the set value management module, forming a closed loop of operation and maintenance; S9, the terminal setting processing unit performs setting call, modification confirmation, version comparison and historical tracing.

[0031] In the above embodiments, a remote dynamic operation and maintenance system and method for setting values ​​are provided. This invention achieves remote management of setting values ​​through a cloud-edge-device collaborative architecture, eliminating the need for on-site maintenance personnel and solving the time-consuming problem of traveling to and from the site in traditional models, thus reducing labor and transportation costs. Setting value modification, verification, and traceability are fully automated, reducing manual intervention and shortening the cycle of a single setting value adjustment from several hours to minutes, improving operation and maintenance response speed. This invention integrates digital twin technology to construct a virtual verification environment, which can simulate various fault scenarios and operating conditions such as short circuits, oscillations, and CT saturation, proactively identifying risks of unreasonable setting values ​​and avoiding protection failures or malfunctions. Dynamic prediction... The alarm module, based on real-time data and trend prediction, achieves adaptive optimization of setpoints, ensuring that setpoints always match the power grid's operating status and resolving the power flow fluctuation adaptation problem caused by new energy access. This invention employs a dual setpoint area architecture and a delayed execution mechanism; new setpoints do not take effect immediately after issuance, reserving a security confirmation window. Maintenance personnel can perform secondary confirmation based on virtual verification results, avoiding misoperation. The dual confirmation feedback mechanism ensures consistency between setpoint issuance and execution through hash value verification and standardized file transmission. The edge agent unit's local decision-making capability allows it to autonomously execute emergency operations when cloud-edge communication is interrupted, ensuring continuous and safe power grid operation.

[0032] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the concept and scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the design concept of the present invention should fall within the protection scope of the present invention. The technical content for which protection is sought in this invention has been fully described in the claims.

Claims

1. A fixed-value remote dynamic operation and maintenance system, characterized in that: It includes a cloud-based collaborative control unit, an edge agent unit, and a terminal setting processing unit, which are connected through a communication network to form a collaborative operation and maintenance architecture. The cloud-based collaborative control unit is deployed in the regional control center, the edge agent unit is deployed in the field station, and the terminal setting processing unit is integrated into the relay protection device.

2. The fixed-value remote dynamic operation and maintenance system according to claim 1, characterized in that, The cloud-based collaborative control unit includes: The data acquisition module is used to collect electrical quantity data, equipment status information, fault log files, and environmental perception data at the field site. The data storage module is used to store collected data, digital twin model data, and fixed-value full lifecycle data; The security verification module uses hardware encryption technology to achieve identity authentication, role-based authorization, and operation permission control. The digital twin module is used to construct a primary model of the power grid topology and a secondary protection logic model, forming a virtual mirror synchronized with the physical power grid. The virtual verification module is used to simulate various fault scenarios and operating conditions to perform simulation verification of the setpoint scheme; The dynamic early warning module is used to monitor the power grid's operating status and the matching degree of the setpoints, predict operating trends, and generate setpoint optimization strategies. The fixed value management module is used for fixed value recall, modification, version comparison, and historical tracing; The setpoint maintenance module is used for safe setting of settings, monitoring of device actions, and optimization of closed-loop control.

3. The fixed-value remote dynamic operation and maintenance system according to claim 2, characterized in that: The virtual verification module includes a pre-set fault scenario library and a parallel simulation mechanism. The fault scenario library includes in-zone / out-zone faults, complex evolving faults, and special operating conditions. The simulation process includes real-time operating condition initialization, setting scheme injection, multi-scenario parallel electromagnetic transient simulation, action behavior monitoring, and quantitative evaluation report generation. The evaluation report includes action accuracy, risk index, and protection coordination relationship analysis.

4. A fixed-value remote dynamic operation and maintenance system according to claim 2, characterized in that, The working mechanism of the dynamic early warning module includes: Real-time monitoring: Analyze the matching degree between power grid operating conditions and setpoints, and generate setpoint approach warnings or critical state warnings through load current comparison and impedance trajectory monitoring; Trend forecasting: Based on historical data, meteorological information, and new energy power data, predict the load change curve and the evolution trend of power grid operation mode in the next 24 hours; Setpoint optimization: Under the premise of satisfying reliability and selectivity, generate initial optimized setpoints, and generate 1-3 sets of optimal setpoint adjustment strategies through multi-scheme simulation evaluation; Strategy Recommendation: Outputs an adjustment strategy report that includes profit analysis and risk quantification, showing the trade-offs between the optimization objectives of different options.

5. A fixed-value remote dynamic operation and maintenance system according to claim 2, characterized in that, The security verification module supports three levels of roles, including operator, auditor, and administrator. Operators only have the authority to view and issue fixed values, auditors have the authority to review fixed value schemes, and administrators have the authority to configure the system and assign permissions. Identity authentication uses a combination of hardware encryption lock and password verification, and operation records are kept in the entire process.

6. A fixed-value remote dynamic operation and maintenance system according to claim 1, characterized in that: The edge agent unit has local decision-making and collaborative relay functions. After receiving instructions from the cloud collaborative control unit, it completes local verification of setpoints based on real-time field data. When cloud-edge communication is interrupted, it autonomously performs emergency setpoint adjustments or lockout operations to ensure the safe operation of field equipment.

7. A fixed-value remote dynamic operation and maintenance system according to claim 1, characterized in that: The terminal setting processing unit includes a setting delay execution module and a dual confirmation feedback module. The dual setting area includes a running setting area and a standby setting area. The setting modification command issued remotely is only written to the standby setting area. A configurable security delay timer is started, and the setting in the running setting area is used during the timer. Before the timer ends, a confirmation switching command or a cancellation command can be received. After switching, dual confirmation feedback is achieved through hash value verification and standardized file transmission.

8. A method for fixed-value remote dynamic operation and maintenance, characterized in that, Using the operation and maintenance system according to any one of claims 1-7 includes the following steps: S1, the cloud-based collaborative control unit constructs primary and secondary power grid models through a digital twin module, completing the virtual image initialization; S2. The data acquisition module collects real-time data from the site, stores it in the data storage module, and updates the digital twin model synchronously. S3, the dynamic early warning module monitors the power grid operation status, combines historical data to make trend predictions, and calls the virtual verification module to verify the rationality of the current set value; S4. If there is a risk of mismatch in the set value, the dynamic early warning module generates the optimal set value adjustment strategy, which is then approved by the security verification module and distributed to the edge agent unit by the set value operation and maintenance module. S5. After receiving the setting information, the edge agent unit performs on-site verification based on real-time data. If there is no abnormality, it forwards the information to the terminal setting processing unit. S6. The terminal setting processing unit writes the new setting into the standby setting area, starts the security delay timer, and provides real-time feedback on the setting area status and countdown information through the "heartbeat" protocol. S7. After confirmation during the timing period, the terminal setting processing unit switches to the new setting operation and sends back the verification information through the double confirmation feedback module; if a cancellation command is received, the standby setting area is cleared and the original setting operation is maintained. The S8 cloud-based collaborative control unit receives feedback information and completes version updates and historical tracing through the fixed value management module, forming a closed-loop operation and maintenance system.

9. A method for fixed-value remote dynamic operation and maintenance according to claim 8, characterized in that, The modeling process of the digital twin module in step S1 includes: S1.

1. Perform object-oriented modeling of primary equipment, assign unique identifiers to equipment such as generators, transformers, and transmission lines, and configure electrical parameters consistent with those of the physical equipment; S1.2 Based on the real-time status of switches / disconnectors, construct dynamically updated power grid topology connections; S1.3 Utilize real-time power flow and load data to construct a dynamic power flow profile of the entire network and form the initial operating conditions of the model; S1.4 Construct a secondary protection logic model, simulate the measurement elements and logic judgment process of the protection device, and inject the current running set value or the set value scheme to be modified. S1.

5. Implement interactive simulation between the primary and secondary models. Inject the electrical quantity data of the primary model into the secondary model, and use the action signals of the secondary model to drive the topology adjustment of the primary model in reverse.

10. A method for fixed-value remote dynamic operation and maintenance according to claim 8, characterized in that, The workflow of the dynamic early warning module in step S3 includes: S3.1 Monitoring and Early Warning: Through real-time data collection, continuously analyze the matching degree between the current power grid operating conditions and the operating settings; monitor the load current of the protected components in real time and compare it with the overcurrent settings, differential start settings, etc. in the setting sheet; when the load current continues to approach these settings, generate a setting approach warning, indicating insufficient setting margin; for distance protection, continuously calculate and measure the impedance and plot its trajectory on the impedance complex plane; observe the relative position of the impedance trajectory and the protection characteristics; if the trajectory lingers near the operating boundary for a long time, the warning setting is in a critical state. S3.2 Trend Forecasting: Based on historical load data, date type, meteorological information, and renewable energy power, predict the load change curve for the next few hours to 24 hours; S3.3, Operation Mode Evolution Prediction: Based on the predicted load and renewable energy distribution, drive the digital twin module to perform power flow calculations to predict the power flow distribution, voltage level and potential overloaded / overloaded equipment of the power grid at a specific point in the future. S3.4 Virtual Verification: The monitored state and the predicted state are analyzed for the rationality of the current set value using the virtual verification module. If an anomaly occurs, the set value is optimized. S3.5, Setpoint Generation: Prioritize selectivity while ensuring reliability, and then maximize sensitivity to generate initial optimized setpoints; S3.6, Setpoint Optimization: Within the scope permitted by the procedures and the safety of the equipment, a search is conducted, and multiple candidate setpoint schemes are generated based on the initial optimized setpoints. Each scheme is rapidly simulated in the digital twin module and the virtual verification module for the predicted operating mode and the preset fault set, and its score on each optimization objective is evaluated. S3.7 Strategy Recommendation and Risk Quantification: After optimization, the system will generate a dynamic fixed value adjustment strategy recommendation report. Its core contents include: providing 1-3 optimal fixed value adjustment schemes, clearly showing the trade-offs of different schemes on multiple optimization objectives in the form of charts, clearly informing about the benefits after adjustment, and clearly pointing out any side effects that may be brought about by the adjustment.

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