Real-time power grid dynamic constant value checking method for new energy access

Abstract

The invention is applicable to the technical field of electrical systems, and provides a new energy access-oriented real-time power grid dynamic constant value checking method, which comprises the following steps of: constructing a full model by acquiring multi-aspect data of a power grid, generating various research state operation modes, and calculating setting parameters by adopting an iterative algorithm considering a new energy short-circuit characteristic, so that the real-time dynamic constant value checking of the power grid is realized. The sensitivity and selectivity of the protection setting value can be accurately checked in real time. Compared with an existing static checking mode, the implementation mode of the invention can adapt to dynamic changes of a power grid operation mode after new energy access, timely discover potential problems of a protection constant value in a new energy environment, generate early warning information and a constant value recommendation interval, effectively avoid failure of the protection constant value, improve reliability and safety of a power grid protection system, and improve the safety of the power grid protection system. Stable operation of the power grid under the condition of new energy high-permeability grid connection is guaranteed, the problem that the prior art cannot adapt to new energy dynamic changes, and consequently a protection constant value may fail is solved, and powerful support is provided for safe operation of the power grid.

Description

Technical Field

[0001] This application belongs to the field of electrical system technology, and in particular relates to a real-time grid dynamic setting verification method for new energy access. Background Technology

[0002] With the advancement of smart grid construction and the high penetration rate of renewable energy in the grid, the power supply structure and power flow distribution of the power grid have undergone profound changes. New energy power generation equipment (such as photovoltaic power plants and wind farms) is typically connected to the grid through power electronic interfaces (such as inverters). These interfaces can quickly adjust the magnitude and phase of fault currents, resulting in fault current characteristics that are significantly different from those of traditional synchronous generator systems. For example, when a fault occurs on the weak feed side (the side with smaller power capacity), the presence of transition resistance (including grounding resistance or phase-to-phase fault resistance) can significantly affect the accuracy of distance protection: transition resistance changes the amplitude and phase of the fault current, causing the measured impedance to deviate from the true value, which may lead to maloperation (unnecessary tripping) or failure to operate (inability to promptly clear the fault) of the protection device.

[0003] In existing technologies, the setting and verification of protection settings mainly adopt a static approach, that is, based on preset operating scenarios and offline calculations, and verification is performed periodically. This method cannot adapt to the dynamic changes in the power grid operation mode after the integration of new energy sources, which may lead to the failure of protection settings under the condition of new energy integration, threatening the safety of the power grid. Summary of the Invention

[0004] In view of this, the embodiments of this application provide a real-time dynamic power grid setting verification method for new energy access, which can solve the problem that static setting and verification in related technologies cannot adapt to the dynamic changes in the power grid operation mode after new energy access, which may lead to the failure of protection settings under the condition of new energy access and threaten the safety of the power grid.

[0005] In a first aspect, embodiments of this application provide a real-time grid dynamic setting verification method for new energy access, including: Acquire static models of primary power grid equipment, real-time power grid operation data, and protection setting information; Based on the static model of primary equipment, real-time operation data of the power grid, and protection setting information, a complete power grid model is constructed, which includes the mapping relationship between the primary equipment topology and secondary protection. Based on the full power grid model and the commissioning status of new energy power plants, and combined with power grid planning data, the research state operation mode is generated; Based on the research-state operation mode and the full power grid model, the setting parameters of the verification branch are calculated using an iterative algorithm that takes into account the short-circuit characteristics of new energy sources. Based on the setting parameters and the protection setting information in the full power grid model, the sensitivity and selectivity of the protection settings are checked, and the check results are generated. For set values ​​that do not meet the preset verification rules, generate early warning information and recommended set value ranges; Output the verification results, early warning information, and recommended value range.

[0006] Secondly, embodiments of this application provide a real-time grid dynamic setting verification device for new energy access, comprising: The acquisition module is used to acquire static models of primary power grid equipment, real-time power grid operation data, and protection setting information. The construction module is used to build a complete power grid model that includes the mapping relationship between the primary equipment topology and secondary protection, based on the static model of the primary equipment, real-time operation data of the power grid, and protection setting information. The first generation module is used to generate the research state operation mode based on the full power grid model and the commissioning status of new energy power stations, combined with power grid planning data. The calculation module is used to calculate the setting parameters of the verification branch based on the research-state operation mode and the full power grid model, using an iterative algorithm that takes into account the short-circuit characteristics of new energy sources. The verification module is used to verify the sensitivity and selectivity of the protection settings based on the setting parameters and the protection setting information in the full power grid model, and generate verification results. The second generation module is used to generate early warning information and recommended ranges for fixed values ​​that do not meet the preset verification rules. The output module is used to output the verification results, early warning information, and recommended range of fixed values.

[0007] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the above-mentioned method for real-time grid dynamic setting verification for new energy access.

[0008] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method for real-time grid dynamic setting verification for new energy access.

[0009] Fifthly, embodiments of this application provide a computer program product that, when run on a terminal device, causes the terminal device to execute the aforementioned real-time grid dynamic setting verification method for new energy access.

[0010] The beneficial effects of this application's embodiments compared to existing technologies are as follows: This application's embodiments construct a complete model by acquiring multi-faceted data from the power grid, generating various research-state operating modes, and employing an iterative algorithm that considers the short-circuit characteristics of new energy sources to calculate setting parameters. This enables real-time and accurate verification of the sensitivity and selectivity of protection settings. Compared to existing static verification methods, this application's implementation method can adapt to the dynamic changes in power grid operation modes after new energy integration, promptly identify potential problems with protection settings in the new energy environment, generate early warning information and recommended setting ranges, effectively avoid protection setting failures, improve the reliability and security of the power grid protection system, ensure the stable operation of the power grid under high new energy penetration grid connection conditions, solve the problem that existing technologies cannot adapt to the dynamic changes of new energy sources, leading to potential protection setting failures, and provide strong support for the safe operation of the power grid. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram illustrating the implementation process of the real-time grid dynamic setting verification method for new energy access provided in this application embodiment.

[0013] Figure 2 This is a schematic diagram of the structure of the real-time grid dynamic setting verification device for new energy access provided in the embodiments of this application.

[0014] Figure 3 This is a schematic diagram of the structure of the terminal device provided in the embodiments of this application. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are protected by this application.

[0016] It should be noted that the terms "comprising," "including," and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application, are intended to cover non-exclusive inclusion. For example, a process, method, terminal, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. Terms such as "first" and "second" in the claims, specification, and accompanying drawings of this application, as well as relational terms, are used merely to distinguish one entity / operation / object from another entity / operation / object, and do not necessarily require or imply any such immediate relationship or order between these entities / operations / objects.

[0017] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0018] With the advancement of smart grid construction and the high penetration rate of renewable energy in the grid, the power supply structure and power flow distribution of the power grid have undergone profound changes. New energy power generation equipment (such as photovoltaic power plants and wind farms) is typically connected to the grid through power electronic interfaces (such as inverters). These interfaces can quickly adjust the magnitude and phase of fault currents, resulting in fault current characteristics that are significantly different from those of traditional synchronous generator systems. For example, when a fault occurs on the weak feed side (the side with smaller power capacity), the presence of transition resistance (including grounding resistance or phase-to-phase fault resistance) can significantly affect the accuracy of distance protection: transition resistance changes the amplitude and phase of the fault current, causing the measured impedance to deviate from the true value, which may lead to maloperation (unnecessary tripping) or failure to operate (inability to promptly clear the fault) of the protection device.

[0019] In existing technologies, the setting and verification of protection settings mainly adopt a static approach, that is, based on preset operating scenarios and offline calculations, and verification is performed periodically. This method cannot adapt to the dynamic changes in the power grid operation mode after the integration of new energy sources, which may lead to the failure of protection settings under the condition of new energy integration, threatening the safety of the power grid.

[0020] In view of this, this application provides a real-time dynamic power grid setting verification method for renewable energy integration. By acquiring multi-faceted power grid data to construct a complete model, multiple operational modes are generated, and an iterative algorithm considering the short-circuit characteristics of renewable energy is used to calculate setting parameters. This method can verify the sensitivity and selectivity of protection settings in real time and accurately. Compared with existing static verification methods, this application's implementation can adapt to the dynamic changes in power grid operation modes after renewable energy integration, promptly identify potential problems with protection settings in a renewable energy environment, generate early warning information and recommended setting ranges, effectively avoid protection setting failures, improve the reliability and security of the power grid protection system, ensure the stable operation of the power grid under high renewable energy penetration, and solve the problem that existing technologies cannot adapt to the dynamic changes of renewable energy, leading to potential protection setting failures. This provides strong support for the safe operation of the power grid.

[0021] To illustrate the technical solution of this application, specific embodiments are described below.

[0022] Figure 1 This illustration shows a flowchart of a real-time grid dynamic setting verification method for new energy access provided in an embodiment of this application. This method can be applied to terminal devices. Terminal devices can be servers, service clusters, mobile phones, tablets, laptops, ultra-mobile personal computers (UMPCs), netbooks, etc.

[0023] Specifically, the above-mentioned real-time grid dynamic setting verification method for new energy access may include the following steps S101 to S107.

[0024] Step S101: Obtain the static model of primary equipment in the power grid, real-time operation data of the power grid, and protection setting information.

[0025] Among them, the static model of primary equipment in the power grid refers to the collection of static information such as physical parameters (e.g., impedance, capacity) and connection relationships of primary equipment such as transformers, transmission lines, and circuit breakers in the power grid, which is used to describe the initial structure of the primary system of the power grid.

[0026] Real-time power grid operation data is information on electrical quantities such as voltage, current, power, and frequency, as well as equipment operating status, collected in real time by power grid monitoring systems (such as SCADA systems), reflecting the current operating status of the power grid.

[0027] Protection setting information consists of parameters preset in the protection device, such as overcurrent protection setting and distance protection setting, which are used to determine faults and trigger protection actions.

[0028] In the embodiments of this application, the terminal device can obtain the static model of the primary equipment of the power grid (including equipment impedance and topology connection relationships) through the integrated power grid operation intelligent system interface, and obtain protection setting information (such as setting sheet data) in the "executed" state through the setting calculation system or OMS system (OMS (Operation Management System) is a platform focused on power grid equipment management and protection setting maintenance, commonly used for setting calculation, setting sheet management, and equipment status tracking). Simultaneously, it can collect real-time power grid operation data, including telemetry data (bus voltage, line power flow) and tele-signaling data (switch status), from the OS2 system (OS2 (Operational Support System) is a comprehensive power grid monitoring and management platform used for real-time acquisition, processing, and analysis of power grid operation data). This provides accurate and real-time input data for subsequent model construction, solving the data silos and lag problems in traditional methods, and ensuring that the verification is based on the latest power grid status.

[0029] Step S102: Based on the static model of the primary equipment of the power grid, the real-time operation data of the power grid, and the protection setting information, construct a full power grid model that includes the mapping relationship between the primary equipment topology and secondary protection.

[0030] Among them, the power grid full model refers to a comprehensive digital model that integrates the static model of primary equipment, real-time operating data, and secondary protection mapping relationships, and is used to support dynamic verification calculations.

[0031] In the embodiments of this application, the terminal device can first match the static model of the primary equipment with real-time operating data to generate a primary model reflecting the current topology; then, by associating the protection setting information with the primary equipment through the equipment MRID identifier, a secondary protection mapping relationship is established to form a complete power grid model, including equipment connections, real-time status, and protection settings. By creating a power grid representation that maps virtual and real data, a unified basis is provided for dynamic verification, solving the problem of model disconnect in traditional methods and enhancing the accuracy of verification.

[0032] Step S103: Based on the full power grid model and the commissioning status of new energy power plants, and combined with power grid planning data, generate the research state operation mode.

[0033] Among them, the research-state operation mode refers to the simulated operation state generated by superimposing planned data (such as power generation plan, maintenance plan) and new commissioning and change scenarios based on the real-time operation mode. It is used to simulate the power grid behavior under future or specific conditions and provide a dynamic test environment for setting value verification.

[0034] In the embodiments of this application, when a new renewable energy power station experiences new commissioning or changes, the terminal equipment can map the parameters and topology of the newly commissioned or changed equipment based on the real-time operating mode in the full power grid model. Then, combined with power grid planning data (such as generation plans, maintenance plans, and load forecasts), the operating mode parameters (such as power flow distribution and power output) are automatically or manually adjusted. Through scenario simulation and power flow calculation, a study-state operating mode is generated. This provides a flexible testing environment for verification, simulating changes after renewable energy access, solving the problem that static verification cannot adapt to changes in operating mode, and improving the coverage of verification.

[0035] Step S104: Based on the research state operation mode and the power grid full model, the setting parameters of the verification branch are calculated using an iterative algorithm that takes into account the short-circuit characteristics of new energy sources.

[0036] Among them, the setting parameters refer to the key calculation outputs of the verification branch, such as the maximum current, branch coefficient and measured impedance. These parameters are used to evaluate the performance of the protection setting and are derived based on short-circuit calculations.

[0037] In the embodiments of this application, the terminal device can form a node impedance matrix (positive sequence, negative sequence, zero sequence) based on the research state operation mode. Then, for the verification branch, fault type and transition resistance are set, and an iterative algorithm is adopted: the new energy source is equivalent to a voltage-controlled current source, the initial fault current is calculated, and the new energy injection current and node voltage are iteratively updated until convergence (convergence condition is voltage deviation <0.001 pu). Through the symmetrical component method and iterative calculation, the setting parameters such as maximum current, branch coefficient, and measured impedance are output, thereby accurately simulating the short-circuit characteristics of the new energy source, solving the problem of fault current variation, ensuring the reliability of calculation results, and providing a solid data foundation for setting value verification.

[0038] Step S105: Based on the setting parameters and the protection setting information in the full power grid model, verify the sensitivity and selectivity of the protection settings and generate verification results.

[0039] Sensitivity refers to the protection device's ability to detect faults, usually expressed as a sensitivity coefficient (e.g., K). sen >1.5) indicates that reliable operation is ensured during a fault. Selectivity refers to the ability of the protection device to disconnect only the faulty area without erroneously tripping other areas, as verified by fault detection outside the avoidance zone (such as I). dz >K k * I k This can be achieved through [the following].

[0040] In the embodiments of this application, the terminal device can extract protection setting information from the full power grid model, and in conjunction with the setting parameters, perform a step-by-step verification for each setting item (such as phase current protection and distance protection) according to a preset verification principle: selective verification can use I dz>K k * I k or Z dz <K k * (Z L + K' z * Z' dz) Equal criteria. Sensitivity checks can use K... sen = I kmin / I dz >1.5 criteria. By applying the criteria and recording the results, a verification result (satisfied or not satisfied) is generated. Multi-dimensional verification ensures the performance of the set value, solves the problem of the singleness of traditional verification, and provides a comprehensive evaluation output.

[0041] Among them, I dz K is the setting value for the line current protection. k For the reliability coefficient, I k Z represents the maximum current flowing through the protection during an external fault. dz Z is the distance protection setting for this line. L The impedance of this line is K' z Z' is the amplification factor. dz K is the protection setting for the distance between adjacent lines. sen I is the sensitivity coefficient. kmin This is the minimum current flowing through the protection system in the event of a fault at the end of this line.

[0042] Step S106: Generate early warning information and recommended value ranges for fixed values ​​that do not meet the preset verification rules.

[0043] The recommended value range is a reasonable range of values ​​provided for protection settings that do not meet the requirements, based on the verification results and preset rules.

[0044] In the embodiments of this application, the terminal device can automatically generate early warning information for protection settings that do not meet the preset verification rules based on the verification results, prompting the user that the protection settings may pose a safety hazard. Simultaneously, combining power grid operation experience and verification algorithms, it provides reasonable recommended value ranges for settings that do not meet the requirements, guiding users to adjust the protection settings. This helps users promptly understand problems with the protection settings and take effective measures to rectify them, ensuring the safe operation of the power grid.

[0045] Step S107: Output the verification result, the warning information, and the recommended value range.

[0046] In the embodiments of this application, the terminal device can output the verification results, early warning information, and recommended setting ranges to the user in an intuitive manner (such as reports, graphical interfaces, etc.) for easy viewing and analysis. Based on this output information, the user can understand the current status and existing problems of the power grid protection settings, and adjust the protection settings in a timely manner to ensure the safe and stable operation of the power grid under the condition of new energy access.

[0047] The beneficial effects of this application's embodiments compared to existing technologies are as follows: This application's embodiments construct a complete model by acquiring multi-faceted data from the power grid, generating various research-state operating modes, and employing an iterative algorithm that considers the short-circuit characteristics of new energy sources to calculate setting parameters. This enables real-time and accurate verification of the sensitivity and selectivity of protection settings. Compared to existing static verification methods, this application's implementation method can adapt to the dynamic changes in power grid operation modes after new energy integration, promptly identify potential problems with protection settings in the new energy environment, generate early warning information and recommended setting ranges, effectively avoid protection setting failures, improve the reliability and security of the power grid protection system, ensure the stable operation of the power grid under high new energy penetration grid connection conditions, solve the problem that existing technologies cannot adapt to the dynamic changes of new energy sources, leading to potential protection setting failures, and provide strong support for the safe operation of the power grid.

[0048] In some specific embodiments of this application, the above-mentioned construction of a full power grid model containing the mapping relationship between primary equipment topology and secondary protection based on the real-time operation data of the power grid and the protection setting information may specifically include steps S401 to S403.

[0049] Step S401: Establish the matching relationship between the static model of the primary equipment of the power grid and the real-time operation data of the power grid, and generate the primary model of the power grid.

[0050] Among them, the primary power grid model is a dynamic model generated by matching the static model of primary equipment with real-time operating data. It integrates equipment topology and real-time status (such as power flow distribution and switch position).

[0051] In the embodiments of this application, the terminal device can obtain the static model and real-time operating data of the primary equipment of the power grid from the interface of the integrated intelligent power grid operation system (OS2 system). Then, it performs data matching through device identifiers (such as MRID), mapping the real-time data to the static model. For example, it runs algorithms to verify consistency and reconstructs the topology to reflect the current state. This process generates a dynamic primary power grid model, including real-time topology and operating parameters. The terminal device can perform actions such as data querying, running matching algorithms, and updating the model to create a model that accurately reflects the real-time state of the power grid, providing a reliable foundation for subsequent steps. This solves the problem of the disconnect between the static model and real-time data in traditional methods, making subsequent verification more closely reflect actual operation.

[0052] Step S402: Map the protection setting information to the primary equipment in the primary power grid model to establish the association between the primary model and the secondary protection model. The secondary protection model is composed of the protection setting information, including protection device configuration and setting data.

[0053] The secondary protection model is composed of protection setting information, including the configuration and setting data of the protection device, which is used to represent the logical structure of the secondary protection system.

[0054] In the embodiments of this application, the terminal device can obtain protection setting information from the setting calculation system or OMS system interface, and combine it with the primary power grid model. Using device identifiers (such as MRID), it associates the protection setting information with primary devices, for example, by parsing setting sheets and establishing mapping relationships, thereby constructing a secondary protection model and obtaining association relationships, such as mapping tables or database links. The terminal device can perform identifier matching, data association, and storage operations, thereby achieving seamless integration of physical devices and protection logic, ensuring that each device has corresponding protection rules, avoiding data silos, providing a crucial bridge for the construction of the entire model, and enabling the protection system to intelligently adapt to real-time changes.

[0055] Step S403: Based on the association between the primary model and the secondary protection model, generate and store the full power grid model, which includes the primary equipment topology, real-time operating data, and secondary protection mapping relationship.

[0056] In the embodiments of this application, the terminal device can utilize the association relationship to integrate data from the primary model and the secondary protection model, perform data fusion and structured storage, for example, serialize the information into a standard format (such as JSON or XML) and save it to a database, and generate a comprehensive power grid full model, including equipment topology, real-time data and protection mapping. This creates a complete digital power grid representation, providing a comprehensive and consistent data foundation for subsequent dynamic setting verification, improving verification accuracy and efficiency, and supporting future expansion, such as addressing complex scenarios involving new energy integration.

[0057] In some specific embodiments of this application, the above-mentioned research mode of operation is generated based on the full power grid model and the commissioning status of new energy power stations, combined with power grid planning data, and may specifically include steps S501 to S504.

[0058] Step S501: When a new energy power station is put into operation or undergoes an anomaly, the real-time operation mode in the full power grid model is mapped to the new operation or anomaly scenario to form an initial research state mode.

[0059] New commissioning or changes at renewable energy power plants refer to the construction and commissioning of new renewable energy power plants (such as wind farms or photovoltaic power plants) or changes to existing equipment, such as capacity increases, equipment modifications, or technological upgrades. These events alter the power grid structure, requiring dynamic adjustments to operating methods to reflect these changes.

[0060] Real-time operation mode refers to the real-time monitoring of the power grid's operating status, including switch positions, disconnector status, bus voltage, and line power flow.

[0061] In the embodiments of this application, the terminal device can extract the real-time operating mode from the full power grid model and combine it with the new power generation or change information (such as new capacity or equipment changes) of the new energy power station. Through the device identifier (such as MRID), the real-time data is mapped to the changed scenario. For example, the algorithm is run to update the topology connection and initialize the power flow, and generate the initial study state mode, so as to quickly respond to the changes in the power grid, create the basic simulation state, provide a starting point for subsequent adjustments, ensure that the verification can cover the latest structure, and avoid errors caused by delay.

[0062] Step S502: Obtain power grid planning data, which includes power generation plans, maintenance plans, and bus load forecast data.

[0063] Among them, power grid planning data refers to pre-established power grid operation plans, including power generation plans (such as renewable energy output forecasts and traditional unit power generation arrangements), maintenance plans (such as equipment outage schedules), and bus load forecast data (such as future load change trends). These data are used to guide adjustments to operating modes and ensure that simulated scenarios conform to actual plans.

[0064] In the embodiments of this application, the terminal device can obtain power grid planning data from the interface of the scheduling planning system or energy management system, including power generation plans (such as new energy output curves and unit arrangements), maintenance plans (such as equipment outage lists), and load forecast data (such as bus load changes). During processing, the terminal device can verify data integrity and format it into a standard structure to obtain a structured planning dataset, thereby integrating future operation guidance information, providing a basis for adjusting the operation mode, ensuring that the simulated scenario fits the actual plan, and improving the practicality and accuracy of the verification.

[0065] Step S503: Based on the initial research state, adjust the operating mode parameters to obtain the adjusted operating mode parameters.

[0066] Among them, the operating mode parameters refer to the variables involved in adjusting the operating status, such as power flow distribution, power output level, load size and topology.

[0067] In the embodiments of this application, the terminal device can automatically or through interface interaction adjust operating parameters using the initial research state mode and power grid planning data. For example, it can modify the power flow distribution to match the power generation plan, simulate topology changes under maintenance conditions, or update the load level based on the prediction data to achieve dynamic optimization of the operating state, incorporate the influence of the plan, generate more realistic simulation parameters, lay the foundation for the final mode generation, and enhance the adaptability and reliability of the verification.

[0068] Step S504: Generate the final research state operation mode based on the adjusted operation mode parameters.

[0069] In the embodiments of this application, the terminal device can integrate the adjusted operating parameters, perform data fusion and model generation, such as serializing the parameters into a standard format and constructing a complete operating state to generate the final research state operating mode, so as to create the final simulation environment, support subsequent setting value verification calculations, ensure that the verification is based on a comprehensive and accurate scenario, and improve the response capability and safety of power grid protection.

[0070] The implementation method of this application realizes the dynamic generation of the research state operation mode, which not only solves the limitations of static simulation in traditional methods, but also ensures the synchronization of verification with real-time changes and planned data, enabling the power grid to cope more intelligently with the complexity and uncertainty of new energy access and improve the overall operational reliability.

[0071] In some specific embodiments of this application, the above-mentioned calculation of the setting parameters of the verification branch based on the research state operation mode and the power grid full model, using an iterative algorithm that takes into account the short-circuit characteristics of new energy sources, may specifically include steps S601 to S605.

[0072] Step S601: Extract the real-time operating status of the power grid based on the research operating mode, and obtain network topology parameters based on the full power grid model.

[0073] Among them, the real-time operating status of the power grid refers to the power grid operation data collected in real time from the monitoring system, including bus voltage, line power flow, and switch status, which reflects the current dynamics of the power grid. Network topology parameters are parameters that describe the connection relationships of the power grid, such as line impedance, transformer turns ratio, and node connection methods.

[0074] In the embodiments of this application, the terminal device can extract real-time operating status, such as bus voltage, line power flow and switch position, from the research operating mode, and at the same time obtain network topology parameters, including line impedance and transformer parameters, from the full power grid model, thereby providing the basic data required for calculation, ensuring that subsequent short-circuit calculations are based on accurate and up-to-date power grid conditions, and avoiding errors caused by data lag.

[0075] Step S602: Based on the network topology parameters, form the power grid node impedance matrix using the symmetric component method.

[0076] The power grid node impedance matrix is ​​a matrix that represents the impedance relationship between nodes in the power grid and is used to calculate fault current and voltage.

[0077] In the embodiments of this application, the terminal device can utilize network topology parameters and apply the symmetric component method to calculate the positive-sequence, negative-sequence, and zero-sequence impedance matrices. Specifically, it can run a matrix generation algorithm, such as inverting the branch admittance matrix to obtain the node impedance matrix, thus obtaining a complete set of impedance matrices. This creates a mathematical representation of the power grid, simplifies fault analysis, ensures that short-circuit calculations can handle unbalanced conditions, and improves computational efficiency and accuracy.

[0078] Step S603: Calculate the initial current at the fault point without considering the injection of new energy sources based on the impedance matrix of the power grid nodes.

[0079] In the embodiments of this application, the terminal device can calculate the initial current at the fault point without considering the injection of new energy sources based on the impedance matrix and fault scenarios (such as setting fault type and transition resistance). By running the short-circuit calculation algorithm, the initial current value at the fault point can be obtained, avoiding the initial disturbance caused by the characteristics of new energy sources and improving the iteration convergence speed.

[0080] Step S604: Update the new energy injection current and fault point current through an iterative algorithm until convergence.

[0081] Among them, the new energy injection current refers to the short-circuit current provided by the new energy power station (such as the power supply through the inverter interface) during a fault. Due to its power electronic characteristics, the current amplitude and phase may change rapidly, requiring dynamic simulation.

[0082] In the embodiments of this application, the terminal device can employ an iterative process: first, calculate the voltage of the renewable energy node based on the initial current at the fault point; then, update the injected current according to the equivalent model of the renewable energy (such as a voltage-controlled current source); next, recalculate the current at the fault point; and check whether the voltage deviation meets the convergence condition (e.g., <0.001 pu). During the processing, the terminal device can run a loop iteration until the system stabilizes, obtaining the converged current and voltage values. This dynamically simulates the short-circuit characteristics of the renewable energy, accurately reflects the changes in fault current, and solves the problem of traditional methods neglecting the dynamic response of renewable energy.

[0083] Step S605: Calculate the tuning parameters of the verification branch based on the converged system state.

[0084] In the embodiments of this application, the terminal device can use the converged system state (such as node voltage and branch current) to calculate the setting parameters of the verification branch, including the maximum current, branch coefficient and measured impedance. Specifically, it can run a parameter extraction algorithm to obtain a structured set of setting parameters, thereby generating accurate verification data, providing input for subsequent setting verification, ensuring that the protection device can still maintain sensitivity and selectivity under the access of new energy sources, and reducing the risk of false tripping or failure to trip.

[0085] This application's implementation method automates the entire process from data extraction to iterative convergence, dynamically incorporating the short-circuit characteristics of new energy sources, thus overcoming the limitations of static assumptions in traditional short-circuit calculations. This ensures the accuracy and reliability of the setting parameters, enabling better handling of fault current variations caused by new energy integration and improving the adaptability and overall safety level of the protection system.

[0086] In some specific embodiments of this application, the above-mentioned updating of the new energy injection current and the fault point current through an iterative algorithm until convergence may specifically include steps S701 to S707.

[0087] Step S701: The new energy power station is equivalent to a voltage-controlled current source.

[0088] Among them, new energy power stations refer to renewable energy power generation facilities such as wind farms or photovoltaic power stations, which are connected to the power grid through power electronic interfaces (such as inverters). Their fault current characteristics are different from those of traditional synchronous generators, and they are characterized by the ability to quickly adjust the current amplitude and phase.

[0089] In the embodiments of this application, the terminal device can extract the parameters of the new energy power station (such as rated capacity and control mode) from the full power grid model and model them as a source whose current output changes with the terminal voltage, thereby accurately simulating the fault response characteristics of new energy, solving the shortcomings of the traditional fixed current model, providing a real basis for iterative calculation, and ensuring that subsequent steps can dynamically reflect the behavior of new energy.

[0090] Step S702: Calculate the initial voltage of the new energy node using the initial current at the fault point.

[0091] Among them, the initial fault current refers to the initial value of the fault current obtained based on traditional short-circuit calculations (such as using the symmetrical component method) without considering the injection of new energy sources.

[0092] In embodiments of this application, the terminal device can calculate the initial voltage of the new energy node based on the initial current at the fault point (obtained from previous short-circuit calculations) and the grid impedance matrix. By providing an iterative starting voltage value, a reasonable starting point is ensured, the convergence process is accelerated, and a foundation is laid for the calculation of the injected current.

[0093] Step S703: Calculate the short-circuit current injected into the new energy source based on the initial voltage of the new energy node and the equivalent model parameters of the new energy power station.

[0094] In the embodiments of this application, the terminal device can use the initial voltage of the new energy node and model parameters to calculate the short-circuit current injected by the new energy and perform dynamic updates, thereby dynamically quantifying the current contribution of the new energy during a fault, ensuring that the model truly reflects the regulatory role of the power electronic interface, and improving the accuracy of the calculation.

[0095] Step S704: Use the injected short-circuit current from the new energy source to update the fault point current.

[0096] In the embodiments of this application, the terminal device can integrate the short-circuit current injected by the new energy source with the initial fault point current, update the total fault point current, thereby integrating the influence of the new energy source to obtain a more comprehensive fault current representation, avoiding underestimation caused by ignoring the contribution of the new energy source, and providing input for voltage recalculation.

[0097] Step S705: Recalculate the voltage of each node based on the updated fault point current.

[0098] In the embodiments of this application, the terminal device can use the updated fault point current and node impedance matrix to recalculate all node voltages, and obtain the recalculated node voltage values, thereby reflecting the impact of current changes on system voltage and ensuring state synchronization.

[0099] Step S706: Check whether the deviation between the recalculated node voltage and the voltage of the previous iteration meets the convergence condition.

[0100] In the embodiments of this application, the terminal device can compare the current node voltage with the value of the previous iteration, calculate the maximum voltage deviation, and check whether it is less than the threshold. By running the deviation calculation and condition judgment logic, the convergence state (Boolean value) is obtained to ensure that the iteration result is stable and reliable, avoid infinite loops, and improve the calculation efficiency.

[0101] Step S707: If the convergence condition is not met, repeat the steps of calculating the short-circuit current injected into the new energy based on the initial voltage of the new energy node and the equivalent model parameters of the new energy power station, updating the fault point current using the short-circuit current injected into the new energy, and recalculating the voltage of each node based on the updated fault point current, until convergence is achieved.

[0102] In the embodiments of this application, the terminal device can automatically and iteratively execute steps S703 to S705 based on the convergence state. If the conditions are not met, the injected current, fault point current, and node voltage are recalculated to obtain the final converged system state (including stable current and voltage). By refining the results through multiple iterations, the calculation is ensured to accurately reflect the dynamic characteristics of new energy sources, solving the problem that traditional methods cannot handle nonlinear responses and improving the reliability of verification.

[0103] This application's implementation dynamically updates the renewable energy injection current and fault point current until convergence. It automatically handles the entire process from model equivalence to iterative checks, ensuring accurate calculations that incorporate the renewable energy short-circuit characteristics. This overcomes the limitations of static assumptions in traditional short-circuit calculations and improves the reliability of the setting parameters.

[0104] In some specific embodiments of this application, the above-mentioned verification of the sensitivity and selectivity of the protection settings based on the setting parameters and the protection setting information in the full power grid model, and the generation of verification results, may specifically include steps S801 to S803.

[0105] Step S801: Extract protection setting information from the full power grid model.

[0106] In the embodiments of this application, the terminal device can query and extract protection setting information from the full power grid model, for example, by accessing stored protection device configuration and setting data through device identifiers (such as MRID). Specifically, a data extraction algorithm can be run to verify data integrity and format it into a standard structure to obtain a structured set of protection setting information, including current settings, impedance settings, etc., thereby providing accurate basic data for verification, ensuring that subsequent verification is based on the latest and most authoritative setting information, avoiding errors caused by data inconsistency, and improving the reliability of verification.

[0107] Step S802: Based on the protection setting information and the setting parameters, for each protection setting item, verify whether the protection setting avoids faults outside the zone according to the preset verification principle, and verify the sensitivity of the protection setting to faults at the end of the line, to obtain the verification status of each protection setting item.

[0108] In the embodiments of this application, the terminal device can use protection setting information and setting parameters (such as maximum current and branch coefficient) to calculate and compare for each setting item (such as phase current protection stage I or distance protection stage II) using preset verification principles; for example, for selective verification, the formula Idz>Kk * Ik or Zdz is used. <kk * (zl + k'z z'dz)，来检查定值是否躲过区外故障。对于灵敏性校核，可以使用公式ksen="Ikmin" idz>1.5 is used to assess the sensitivity to faults at the end of the line. The terminal equipment can run a verification algorithm to evaluate and record the status item by item, and obtain the verification status of each setting item (such as "satisfied" or "not satisfied"), thereby comprehensively evaluating the setting performance, ensuring that the protection device still has selectivity and sensitivity under the access of new energy sources, and reducing the risk of false tripping or failure to trip.

[0109] Step S803: Generate the verification result based on the verification status.

[0110] In the embodiments of this application, the terminal device can integrate all verification statuses and generate structured verification results. For example, the status data can be converted into a table or document format through a report generation algorithm, including detailed verification results, warning levels and possible optimization suggestions, thereby providing user-friendly output, supporting operators to quickly identify problematic settings and take optimization measures, enhancing the real-time performance and adaptability of power grid protection, and improving the overall safety management efficiency.

[0111] The implementation method of this application automates the entire process from data extraction to result generation, ensuring the accuracy and comprehensiveness of the verification, and also solves the problems of inefficiency and error in manual verification in traditional methods.

[0112] In some specific embodiments of this application, the step of generating early warning information and recommended value ranges for fixed values ​​that do not meet the preset verification rules may specifically include steps S901 to S904.

[0113] Step S901: Based on the verification results, obtain the fixed value items that do not meet the preset verification rules and the corresponding verification principle types.

[0114] Among them, the setting item refers to the specific protection setting parameter, such as current protection setting, impedance protection setting, or time setting. The verification principle type refers to the classification of verification, such as "selectivity" or "sensitivity," which is used to distinguish the focus of verification.

[0115] In the embodiments of this application, the terminal device can query and extract setting items that do not meet the verification rules from the verification results. For example, by analyzing the verification status list, it can identify which current or impedance settings have failed the selectivity or sensitivity verification and record the corresponding verification principle type (such as "selectivity not met" or "sensitivity not met"). This enables precise location of problematic settings, provides clear targets for subsequent warnings and recommendations, ensures processing efficiency, avoids overlooking key issues, and improves the targeting of the verification.

[0116] Step S902: Extract the fault current, measured impedance, and branch coefficient related to the non-satisfied setting from the setting parameters.

[0117] The fault current is the current flowing through the fault point, including positive-sequence, negative-sequence, and zero-sequence components. The measured impedance is the impedance value measured by the protection device during a fault, used for distance protection verification, and is affected by transition resistance and system parameters. The branch coefficient is the ratio of the current flowing through the end of the verification branch to the current flowing through the beginning of the branch during a fault; it is used to quantify the current distribution in multi-source networks and affects selectivity verification.

[0118] In the embodiments of this application, the terminal device can retrieve relevant parameter values ​​from the setting parameter database based on unmet setting items, such as matching fault current, measured impedance, and branch coefficient according to setting identifiers. During processing, the terminal device can run a parameter query algorithm to ensure accurate data association and obtain a set of key parameters related to the problematic setting. By acquiring the core data required for calculation, input is provided for determining the warning level and back-calculation, ensuring that subsequent steps are based on accurate and consistent parameters, thereby improving the reliability of recommendations.

[0119] Step S903: Determine the warning level based on the verification principle type and fault type, and obtain the warning information.

[0120] In the embodiments of this application, the terminal device can assess the severity of risks using verification principle types and fault types (such as those obtained from verification results). For example, it can assign warning levels through a rule engine: high risk is used for situations where selectivity failure may lead to malfunctions, and medium risk is used for situations where sensitivity failure may reduce reliability. During processing, the terminal device can run a risk assessment algorithm to generate warning descriptions and obtain warning information, including the level and detailed description, thereby providing intuitive risk alerts, helping operators quickly identify priority issues, optimize decision-making processes, and enhance the responsiveness of power grid safety management.

[0121] Step S904: Based on the fault type, transition resistance range, and the setting parameters, reverse-engineer the minimum setpoint that satisfies sensitivity and the maximum setpoint that satisfies selectivity, and generate a recommended setpoint range.

[0122] In the embodiments of this application, the terminal device can combine the fault type, transition resistance range (e.g., preset value 0-200Ω), and setting parameters to calculate the recommended setting value using a mathematical inverse calculation method. For example, for setting values ​​that do not meet sensitivity requirements, the minimum setting value is calculated; for setting values ​​that do not meet selectivity requirements, the maximum setting value is calculated to ensure that faults outside the protection zone are avoided. During the processing, the terminal device can run an inverse calculation algorithm (e.g., iterative solution or table lookup) to generate a setting value range, such as [minimum setting value, maximum setting value], thereby providing scientific and operable optimization suggestions, supporting setting value adjustment, ensuring that the protection device maintains performance under the access of new energy sources, reducing the risk of false tripping and failure to trip, and improving the adaptability of power grid operation.

[0123] Specifically, the reverse calculation can be performed by iteratively solving the equation Z_min = f(I_fault, R_trans) to obtain the minimum setpoint, where Z_min represents the minimum impedance setpoint that meets the sensitivity requirements, I_fault represents the fault current, i.e., the fault current value measured at the protection installation point, and R_trans represents the transition resistance, i.e., the arc resistance or contact resistance present at the fault point, whose value range is usually preset (e.g., 0-200Ω). Alternatively, the maximum setpoint can be obtained by iteratively solving the equation Z_max = g(Ifault_max, Rtrans_min, Kbranch), where Z_max represents the maximum impedance setting value that the protection device will not malfunction during faults outside the protection zone, I_fault represents the maximum current value flowing through the protection installation point when a fault occurs at the head end of the next level protection zone (the most severe fault point outside the protection zone), Rtrans_min represents the minimum transition resistance that may exist at the fault point, and Kbranch represents the ratio of the current flowing through the end of the fault branch to the current at the head end of the protection branch during a fault.

[0124] This application's implementation method automates the entire process from problem identification to interval reverse calculation, solving the inefficiency and subjectivity problems of manual evaluation in traditional methods. Furthermore, by dynamically incorporating the effects of fault type and transition resistance, it ensures the accuracy and practicality of recommendations, helping operators quickly respond to setting issues, optimize protection settings, and enhance the stability and reliability of the power grid under new energy integration. Figure 3 This illustration shows a structural diagram of a real-time grid dynamic setting verification device for new energy access provided in an embodiment of this application. The aforementioned real-time grid dynamic setting verification device 2 for new energy access can be configured on a terminal device. Specifically, the aforementioned real-time grid dynamic setting verification device 2 for new energy access includes: The acquisition module 201 is used to acquire the static model of the primary equipment of the power grid, the real-time operation data of the power grid, and the protection setting information; The construction module 202 is used to construct a full power grid model containing the mapping relationship between the primary equipment topology and secondary protection based on the static model of the primary equipment of the power grid, the real-time operation data of the power grid and the protection setting information. The first generation module 203 is used to generate a research-state operation mode based on the full power grid model and the commissioning status of new energy power stations, combined with power grid planning data. Calculation module 204 is used to calculate the setting parameters of the verification branch based on the research state operation mode and the full power grid model, using an iterative algorithm that takes into account the short-circuit characteristics of new energy sources. Verification module 205 is used to verify the sensitivity and selectivity of the protection settings based on the setting parameters and the protection setting information in the power grid full model, and generate verification results; The second generation module 206 is used to generate early warning information and recommended range of fixed values ​​for fixed values ​​that do not meet the preset verification rules; The output module 207 is used to output the verification result, the warning information, and the recommended range of fixed values.

[0125] The beneficial effects of this application's embodiments compared to existing technologies are as follows: This application's embodiments construct a complete model by acquiring multi-faceted data from the power grid, generating various research-state operating modes, and employing an iterative algorithm that considers the short-circuit characteristics of new energy sources to calculate setting parameters. This enables real-time and accurate verification of the sensitivity and selectivity of protection settings. Compared to existing static verification methods, this application's implementation method can adapt to the dynamic changes in power grid operation modes after new energy integration, promptly identify potential problems with protection settings in the new energy environment, generate early warning information and recommended setting ranges, effectively avoid protection setting failures, improve the reliability and security of the power grid protection system, ensure the stable operation of the power grid under high new energy penetration grid connection conditions, solve the problem that existing technologies cannot adapt to the dynamic changes of new energy sources, leading to potential protection setting failures, and provide strong support for the safe operation of the power grid.

[0126] In some embodiments of this application, the above-described construction module 202 is further configured to: Establish a matching relationship between the static model of the primary equipment of the power grid and the real-time operation data of the power grid to generate the primary model of the power grid; The protection setting information is mapped and associated with the primary equipment in the primary power grid model to establish the association between the primary model and the secondary protection model. The secondary protection model is composed of the protection setting information, including protection device configuration and setting data. Based on the relationship between the primary model and the secondary protection model, the full power grid model is generated and stored. The full power grid model includes the primary equipment topology, real-time operating data, and secondary protection mapping relationships.

[0127] In some embodiments of this application, the first generation module 203 is further configured to: When a new energy power station is put into operation or undergoes an anomaly, the real-time operation mode in the full power grid model is mapped to the new operation or anomaly scenario to form an initial research state mode. Acquire power grid planning data, which includes power generation plans, maintenance plans, and bus load forecast data; Based on the initial research state, the operating mode parameters are adjusted to obtain the adjusted operating mode parameters; Based on the adjusted operating parameters, the final research-state operating mode is generated.

[0128] In some embodiments of this application, the above-described calculation module 204 is further used for: Based on the research state operation mode, the real-time operation status of the power grid is extracted, and the network topology parameters are obtained based on the full power grid model; Based on the network topology parameters, the power grid node impedance matrix is ​​formed using the symmetric component method. The initial current at the fault point is calculated based on the impedance matrix of the power grid nodes, without considering the injection of new energy sources. The new energy injection current and the fault point current are updated through an iterative algorithm until convergence. The tuning parameters of the verification branch are calculated based on the converged system state.

[0129] In some embodiments of this application, the above-described calculation module 204 is further used for: The new energy power station is equivalent to a voltage-controlled current source; The initial voltage of the new energy node is calculated using the initial current at the fault point. Calculate the short-circuit current injected into the new energy source based on the initial voltage of the new energy node and the equivalent model parameters of the new energy power station; The fault point current is updated by injecting the short-circuit current using the aforementioned new energy source. The voltage of each node is recalculated based on the updated fault point current; Check whether the deviation between the recalculated node voltage and the voltage of the previous iteration meets the convergence condition; If the convergence condition is not met, repeat the steps of calculating the short-circuit current injected into the new energy based on the initial voltage of the new energy node and the equivalent model parameters of the new energy power station, updating the fault point current using the short-circuit current injected into the new energy, and recalculating the voltage of each node based on the updated fault point current, until convergence is achieved.

[0130] In some embodiments of this application, the verification module 205 is further used for: Extract protection setting information from the full power grid model; Based on the protection setting information and the setting parameters, for each protection setting item, the protection setting is checked one by one according to the preset verification principle to see if it avoids faults outside the zone, and the sensitivity of the protection setting to faults at the end of the line is also checked to obtain the verification status of each protection setting item. The verification result is generated based on the verification status.

[0131] In some embodiments of this application, the second generation module 206 is further configured to: Based on the verification results, obtain the fixed value items that do not meet the preset verification rules and the corresponding verification principle types; Extract the fault current, measurement impedance, and branching coefficient related to the non-satisfied setting terms from the setting parameters; Based on the verification principle type and fault type, the warning level is determined, and the warning information is obtained; Based on the fault type, transition resistance range, and setting parameters, the minimum setpoint that satisfies sensitivity and the maximum setpoint that satisfies selectivity are calculated to generate a recommended setpoint range.

[0132] like Figure 3 The diagram shown is a schematic of a terminal device provided in an embodiment of this application. The terminal device 3 may include: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301, such as a real-time grid dynamic setting verification program for new energy access. When the processor 301 executes the computer program 303, it implements the steps in the aforementioned embodiments of real-time grid dynamic setting verification for new energy access, for example... Figure 1 Steps S101 to S107 are shown.

[0133] A computer program can be divided into one or more modules / units. One or more modules / units are stored in memory 302 and executed by processor 301 to complete this application. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0134] The terminal device may include, but is not limited to, processor 301 and memory 302. Those skilled in the art will understand that... Figure 3 This is merely an example of a terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, a terminal device may also include input / output devices, network access devices, buses, etc.

[0135] The processor 301 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0136] The memory 302 can be an internal storage unit of the terminal device, such as the hard drive or RAM of the terminal device. The memory 302 can also be an external storage device of the terminal device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 302 can include both internal and external storage units of the terminal device. The memory 302 is used to store computer programs and other programs and data required by the terminal device. The memory 302 can also be used to temporarily store data that has been output or will be output.

[0137] It should be noted that, for the sake of convenience and brevity, the structure of the terminal device described above can also be referred to the specific description of the structure in the method embodiment, which will not be repeated here.

[0138] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0139] This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement the steps in the above-described method for real-time grid dynamic setting verification for new energy access.

[0140] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps in the above-mentioned real-time grid dynamic setting verification method for new energy access.

[0141] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0142] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for various specific applications, but such implementations should not be considered beyond the scope of this application.

[0143] In the embodiments provided in this application, it should be understood that the disclosed apparatus / terminal devices and methods can be implemented in other ways. For example, the apparatus / terminal device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0144] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0145] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0146] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0147] The embodiments described above are merely illustrative of the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.< / kk>

Claims

1. A real-time grid dynamic setting verification method for new energy access, characterized in that, include: Acquire static models of primary power grid equipment, real-time power grid operation data, and protection setting information; Based on the static model of the primary equipment of the power grid, the real-time operation data of the power grid, and the protection setting information, a complete power grid model containing the mapping relationship between the primary equipment topology and secondary protection is constructed. Based on the aforementioned full power grid model and the operational status of new energy power plants, and combined with power grid planning data, a research-oriented operating mode is generated. Based on the aforementioned operating mode and the aforementioned full power grid model, the setting parameters of the verification branch are calculated using an iterative algorithm that takes into account the short-circuit characteristics of new energy sources. Based on the setting parameters and the protection setting information in the full power grid model, the sensitivity and selectivity of the protection settings are verified, and verification results are generated. For set values ​​that do not meet the preset verification rules, generate early warning information and recommended set value ranges; Output the verification results, the early warning information, and the recommended range of fixed values.

2. The real-time grid dynamic setting verification method for new energy access as described in claim 1, characterized in that, The step of constructing a complete power grid model, including the mapping relationship between primary equipment topology and secondary protection, based on the real-time operation data of the power grid and the protection setting information, includes: Establish a matching relationship between the static model of the primary equipment of the power grid and the real-time operation data of the power grid to generate the primary model of the power grid; The protection setting information is mapped and associated with the primary equipment in the primary power grid model to establish the association between the primary model and the secondary protection model. The secondary protection model is composed of the protection setting information, including protection device configuration and setting data. Based on the relationship between the primary model and the secondary protection model, the full power grid model is generated and stored. The full power grid model includes the primary equipment topology, real-time operating data, and secondary protection mapping relationships.

3. The real-time grid dynamic setting verification method for new energy access as described in claim 1, characterized in that, The process of generating a research-state operation mode based on the full power grid model and the operational status of new energy power plants, combined with power grid planning data, includes: When a new energy power station is put into operation or undergoes an anomaly, the real-time operation mode in the full power grid model is mapped to the new operation or anomaly scenario to form an initial research state mode. Acquire power grid planning data, which includes power generation plans, maintenance plans, and bus load forecast data; Based on the initial research state, the operating mode parameters are adjusted to obtain the adjusted operating mode parameters; Based on the adjusted operating parameters, the final research-state operating mode is generated.

4. The real-time grid dynamic setting verification method for new energy access as described in claim 1, characterized in that, Based on the research-state operation mode and the full power grid model, the iterative algorithm considering the short-circuit characteristics of new energy sources is used to calculate the setting parameters of the verification branch, including: Based on the research state operation mode, the real-time operation status of the power grid is extracted, and the network topology parameters are obtained based on the full power grid model; Based on the network topology parameters, the power grid node impedance matrix is ​​formed using the symmetric component method. The initial current at the fault point is calculated based on the impedance matrix of the power grid nodes, without considering the injection of new energy sources. The new energy injection current and the fault point current are updated through an iterative algorithm until convergence. The tuning parameters of the verification branch are calculated based on the converged system state.

5. The real-time grid dynamic setting verification method for new energy access as described in claim 4, characterized in that, The step of updating the new energy injection current and the fault point current through an iterative algorithm until convergence includes: The new energy power station is equivalent to a voltage-controlled current source; The initial voltage of the new energy node is calculated using the initial current at the fault point. Calculate the short-circuit current injected into the new energy source based on the initial voltage of the new energy node and the equivalent model parameters of the new energy power station; The fault point current is updated by injecting the short-circuit current using the aforementioned new energy source. The voltage of each node is recalculated based on the updated fault point current; Check whether the deviation between the recalculated node voltage and the voltage of the previous iteration meets the convergence condition; If the convergence condition is not met, repeat the steps of calculating the short-circuit current injected into the new energy based on the initial voltage of the new energy node and the equivalent model parameters of the new energy power station, updating the fault point current using the short-circuit current injected into the new energy, and recalculating the voltage of each node based on the updated fault point current, until convergence is achieved.

6. The real-time grid dynamic setting verification method for new energy access as described in claim 1, characterized in that, The process of verifying the sensitivity and selectivity of the protection settings based on the setting parameters and the protection setting information in the full power grid model, and generating verification results, includes: Extract protection setting information from the full power grid model; Based on the protection setting information and the setting parameters, for each protection setting item, the protection setting is checked one by one according to the preset verification principle to see if it avoids faults outside the zone, and the sensitivity of the protection setting to faults at the end of the line is also checked to obtain the verification status of each protection setting item. The verification result is generated based on the verification status.

7. The real-time grid dynamic setting verification method for new energy access as described in claim 1, characterized in that, The generation of early warning information and recommended value ranges for set values ​​that do not meet the preset verification rules includes: Based on the verification results, obtain the fixed value items that do not meet the preset verification rules and the corresponding verification principle types; Extract the fault current, measurement impedance, and branching coefficient related to the non-satisfied setting terms from the setting parameters; Based on the verification principle type and fault type, the warning level is determined, and the warning information is obtained; Based on the fault type, transition resistance range, and setting parameters, the minimum setpoint that satisfies sensitivity and the maximum setpoint that satisfies selectivity are calculated to generate a recommended setpoint range.

8. A real-time grid dynamic setpoint verification device for new energy access, characterized in that, The device includes: The acquisition module is used to acquire static models of primary power grid equipment, real-time power grid operation data, and protection setting information. The construction module is used to construct a complete power grid model containing the mapping relationship between the primary equipment topology and secondary protection based on the static model of the primary equipment of the power grid, the real-time operation data of the power grid, and the protection setting information. The first generation module is used to generate a research-state operation mode based on the full power grid model and the commissioning status of new energy power stations, combined with power grid planning data. The calculation module is used to calculate the setting parameters of the verification branch based on the research state operation mode and the full power grid model, using an iterative algorithm that takes into account the short-circuit characteristics of new energy sources. The verification module is used to verify the sensitivity and selectivity of the protection settings based on the setting parameters and the protection setting information in the full power grid model, and generate verification results. The second generation module is used to generate early warning information and recommended ranges for fixed values ​​that do not meet the preset verification rules. The output module is used to output the verification result, the early warning information, and the recommended range of fixed values.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the real-time grid dynamic setting verification method for new energy access as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the real-time grid dynamic setting verification method for new energy access as described in any one of claims 1 to 7.

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