Method and apparatus for validation of power quality control application, device, and storage medium

Abstract

A method and apparatus for validation of power quality control application, a device, and a storage medium, the method being implemented by means of a transparent full-scale distribution transformer area platform. The method comprises: on the basis of testing requirements, and in combination with the transparent full-scale distribution transformer area platform, editing and generating a test scheme; on the basis of the test scheme, setting parameters for the transparent full-scale distribution transformer area platform and setting parameters for a validation scenario; testing an Internet-of-Things platform constructed by means of an intelligent gateway, intelligent switches, and intelligent sensing terminals in the transparent full-scale distribution transformer area platform after parameter setting, and monitoring test data during testing to acquire terminal sensing data; and by means of the Internet-of-Things platform, and on the basis of the terminal sensing data, analyzing and evaluating test results of a control device to be tested or a control method to be evaluated, and generating a test analysis report. According to the solution, the technical problems in the existing technology of low reliability of power quality control application validation platforms and methods and low power quality level in distribution transformer areas are solved.

Description

A method, apparatus, equipment and storage medium for verifying the application of power quality management. Technical Field

[0001] This invention relates to the field of power quality management technology, and in particular to a power quality management application verification method, apparatus, equipment, and storage medium. Background Technology

[0002] With the rapid development of new energy technologies and power electronics technologies, a large number of distributed power sources and power electronic devices have been connected to distribution transformer substations, reducing the system inertia and increasing uncertainty, which seriously affects the power quality of the substations. Therefore, reliable power quality management methods are particularly important to ensure the safe and stable operation of new distribution transformer substations.

[0003] Common power quality problems in distribution networks include voltage fluctuations, low voltage at the end of the distribution line, three-phase imbalance, and harmonic pollution. While there are many devices and methods for addressing these common power quality issues, there is a lack of mature application verification methods. This prevents effective testing and verification of the effectiveness of these devices and methods before actual grid connection, hindering the improvement of power quality and stable operation in distribution areas. This is especially true in new smart distribution networks, where the structure and functions are more complex, and various new types of electrical equipment have increasingly higher requirements for power quality.

[0004] However, existing technical solutions for verifying power quality management applications, which provide the necessary testing environment by constructing simplified distribution network models and simulating power quality interference in the distribution network, have the following shortcomings: 1) Regarding the reliability of test results, the distribution network models they construct are designed for traditional distribution networks and lack key elements such as distributed power sources and AC / DC charging piles found in new smart distribution networks. They also cannot construct typical scenarios for the distribution Internet of Things (IoT), making it difficult to realistically simulate the operating characteristics of the current actual distribution network, thus compromising the reliability of test results; 2) Regarding the richness of test scenarios, due to limitations in platform elements, existing technical solutions struggle to reliably simulate power quality management applications such as three-phase imbalance in distribution areas and voltage drop at the end of the distribution line; 3) Regarding testing convenience and ease of use, existing technical solutions lack standardized design for specific test procedures such as test scenario setup, data acquisition, and result analysis, resulting in low test efficiency. Therefore, a reliable power quality management application verification platform and method are urgently needed to effectively improve the power quality level of distribution areas. Summary of the Invention

[0005] In view of this, the first aspect of this application provides a method, apparatus, equipment and storage medium for power quality management application verification, in order to solve the technical problems of low reliability and low power quality level in the power quality management application verification platform and method in the prior art.

[0006] To address the aforementioned technical problems, this invention provides a power quality management application verification method, implemented through a transparent transformer substation simulation platform, comprising:

[0007] Based on the test requirements and in conjunction with the transparent transformer substation full-scale platform, a test plan is edited and generated; wherein, the test plan includes: the treatment equipment to be tested or the treatment method to be evaluated, and the transparent transformer substation full-scale platform is used to provide verification scenarios for several types of power quality treatment functions;

[0008] According to the test plan, the parameter settings for the transparent platform and the parameter settings for the verification scenario are as follows:

[0009] The IoT platform constructed by the smart gateway, smart switches and smart sensing terminals in the transparent transformer area real-model platform after parameter settings were tested, and the test data was monitored during the test to obtain terminal sensing data.

[0010] The IoT platform is used to analyze and evaluate the test results of the treatment equipment or treatment method under test based on the terminal sensing data, and to generate a test analysis report.

[0011] As a preferred embodiment, the step of editing and generating a test plan based on test requirements and the transparent platform model specifically includes:

[0012] The test requirements are analyzed to determine the types of power quality problems that need to be simulated, thus obtaining the test type;

[0013] Based on the test requirements and the configuration of the transparent transformer area real-type platform, test topology modeling is performed to confirm the source-load equipment and data acquisition equipment that need to be put into the test topology.

[0014] Based on the experimental requirements, determine the degree of power quality anomaly to be simulated in the experiment, and determine the experimental data to be monitored;

[0015] Based on the degree of power anomaly and the test data to be monitored, a typical verification scenario is compiled, and a test result analysis process is set. In this way, the test implementation process is planned in conjunction with the typical verification scenario, and the test execution steps are determined.

[0016] The test type, the corresponding edited test topology, the test data to be monitored, the typical verification scenarios, and the test execution steps are pre-saved as typical implementation cases, which serve as the edited and generated test schemes.

[0017] As a preferred embodiment, the parameter settings for the transparent platform and the verification scenario, based on the test plan, specifically include:

[0018] Based on the platform network configuration of the test topology in the test plan, a real-type platform test topology network that meets the test requirements is constructed, and the corresponding treatment equipment to be tested is connected and initialized, thereby completing the parameter settings of the transparent transformer area real-type platform;

[0019] Based on the source-load equipment and data acquisition equipment required for the test topology in the test plan, and the test data to be monitored, the parameters of the verification scenario are set in conjunction with the corresponding connected and initialized governance equipment under test; wherein, the governance equipment under test is connected to the grid and operated together with different power quality abnormal operation conditions.

[0020] As a preferred embodiment, the IoT platform constructed by the smart gateway, smart switches, and smart sensing terminals in the transparent transformer area real-world platform after parameter settings is tested, and test data is monitored during the test to obtain terminal sensing data, specifically including:

[0021] The device under test, after parameter settings and initialization, is used as a smart sensing terminal. It is then connected to the corresponding smart switch, and a corresponding smart gateway is set for each connected smart switch, thereby building an Internet of Things platform.

[0022] After constructing the IoT platform, power management tests of a transparent distribution area real-model platform are conducted based on the test plan and the simulation of different abnormal power quality operating conditions corresponding to the equipment under test; wherein, the power management test includes a power quality abnormal operating condition simulation stage and a management stage;

[0023] Based on the intelligent sensing terminals and power quality analyzers in the IoT platform, test data is monitored during the test, thereby sensing and collecting the status of key equipment and key node parameters in real time, and then collecting them as terminal sensing data to the intelligent gateway; wherein, the terminal sensing data includes abnormal stage data, governance stage data, and post-governance data;

[0024] The terminal sensing data collected at the smart gateway is forwarded directly or after edge computing to the IoT platform for data display and advanced application analysis.

[0025] As a preferred embodiment, the step of analyzing and evaluating the test results of the treatment equipment or treatment method under test based on the terminal sensing data through the IoT platform, and generating a test analysis report, specifically includes:

[0026] The actual scene is obtained by analyzing the collected terminal sensing data through the IoT platform.

[0027] The actual scenario is compared with the verification scenario. When the actual scenario is consistent with the verification scenario, the abnormal stage data in the terminal perception data is analyzed to obtain the corresponding actual abnormal working condition and to determine the actual perception device.

[0028] If the actual sensing device corresponds to the device under test, and the actual abnormal operating condition of the actual sensing device is the same as the abnormal power quality operating condition corresponding to the device under test, then the data of the treatment stage and the data after treatment in the terminal sensing data are analyzed, and the data of the treatment stage and the data after treatment are automatically analyzed according to the preset evaluation model, thereby automatically generating a test analysis report.

[0029] As a preferred embodiment, the method for constructing the preset evaluation model includes:

[0030] Obtain sample data corresponding to the treatment stage data and post-treatment data of the power treatment equipment under test, as well as the annotation data corresponding to the sample data;

[0031] An initial preset evaluation model is constructed, and the sample data and the labeled data are used as training data for the initial preset evaluation model. The initial preset evaluation model is trained until the loss function of the initial preset evaluation model tends to fit, and then the final trained preset evaluation model is obtained.

[0032] As a preferred embodiment, the transparent distribution area real-world platform includes: key equipment for traditional distribution areas, new distribution area equipment, a power quality management area for accessing power quality management equipment through standardized interfaces, and an intelligent gateway for IoT networking of various smart switches and smart sensing terminals within the distribution area.

[0033] As a preferred embodiment, the verification scenarios for the power quality management function include: voltage quality management function verification scenario, three-phase imbalance management function verification scenario, harmonic management function verification scenario, and photovoltaic backfeed management function verification scenario.

[0034] As a preferred embodiment, the parameter settings for the voltage quality management function verification scenario specifically include:

[0035] The power supply of the entire transparent transformer substation is carried out by combining isolation transformers and voltage regulators. The voltage of the transformer substation is controlled by setting the voltage regulator parameters, thereby generating and providing transformer substation voltage fluctuation and overvoltage operation scenarios.

[0036] By adjusting the line impedance parameters through the line simulation device, different feeder lengths are simulated. Combined with the controllable simulated load in the platform, different combinations of feeder lengths and different loads are performed to reproduce the low voltage operation conditions at the end of the transformer area.

[0037] Based on the Internet of Things in low-voltage power distribution, the voltage of the transformer area is acquired in real time as the initial voltage data for the transformer area voltage fluctuation test, and the changes in the transformer area voltage during the test are continuously monitored as test data for the voltage quality governance function verification scenario, thereby completing the setting of the voltage quality governance function verification scenario.

[0038] As a preferred embodiment, the control of the transformer area voltage by setting voltage regulator parameters specifically includes:

[0039] By adjusting the voltage regulator, the contact position between the brush and the coil is changed, thereby altering the turns ratio of the primary and secondary coils, and thus regulating the output voltage to control the regional voltage.

[0040] As a preferred embodiment, the parameter settings for the three-phase imbalance mitigation function verification scenario specifically include:

[0041] Based on the aforementioned test scheme, the load imbalance of the transformer area is determined, and according to the load imbalance of the transformer area, a controllable simulated load with energy feedback is configured to set the three-phase power, thereby enabling the feeder of the transparent transformer area real-model platform to operate in an unbalanced state.

[0042] By configuring an intelligent phase-switching switch, the imbalance state of the transparent transformer area real-model platform is managed. The intelligent phase-switching switch provides a standardized interface, thereby demonstrating the three-phase imbalance management while simultaneously connecting and functionally testing the device under test, thus completing the setup of the three-phase imbalance management function verification scenario.

[0043] As a preferred embodiment, the parameter settings for the harmonic mitigation function verification scenario specifically include:

[0044] Based on the positive harmonic output of the energy-feedable controllable simulated load, harmonics are injected into the power grid in the transparent transformer substation platform through energy feedback, thereby enabling the transparent transformer substation platform to simulate a harmonic pollution scenario.

[0045] The device under test is connected to the interface of the pre-reserved harmonic mitigation device in the transformer substation, and the changes in harmonics in the transformer substation are monitored in real time through the Internet of Things of the transformer substation power distribution, thereby completing the setting of the harmonic mitigation function verification scenario.

[0046] As a preferred embodiment, the parameter settings for the photovoltaic backfeeding control function verification scenario specifically include:

[0047] Based on the aforementioned test plan, the characteristics of the photovoltaic modules to be simulated are determined, and the light intensity, temperature, and shadow parameters corresponding to the special effects of the photovoltaic modules are simulated by configuring programmable simulated photovoltaic cells.

[0048] Based on the photovoltaic inverter with active and reactive power outputs corresponding to the test scheme, a photovoltaic simulation system is constructed in conjunction with the photovoltaic cells, and the photovoltaic output curve of the transparent transformer area real platform is set through the photovoltaic simulation system.

[0049] By combining the preset load power curve within the distribution area, the simulation operation of the photovoltaic system in the distribution area can be realized from normal operation to photovoltaic reverse power scenario.

[0050] During the simulation operation, the voltage, current and power generation data of the distribution area are acquired in real time by smart meters and smart sensors in the distribution area. This data serves as test data for the photovoltaic backfeeding control function verification scenario, thereby completing the setting of the photovoltaic backfeeding control function verification scenario.

[0051] Accordingly, the present invention also provides a power quality management application verification device for a transparent transformer substation real-model platform, comprising: a scheme editing module, a parameter setting module, a data monitoring module, and a result analysis module;

[0052] The scheme editing module is used to edit and generate test schemes based on test requirements and in conjunction with the transparent transformer substation model platform; wherein, the test scheme includes: the treatment equipment to be tested or the treatment method to be evaluated, and the transparent transformer substation model platform is used to provide verification scenarios for several types of power quality treatment functions;

[0053] The parameter setting module is used to set the parameters of the transparent platform and the verification scenario according to the test plan.

[0054] The data monitoring module is used to test the Internet of Things platform constructed by the smart gateway, smart switches and smart sensing terminals in the transparent transformer area real-model platform after parameter settings, and to monitor the test data and obtain terminal sensing data during the test.

[0055] The result analysis module is used to analyze and evaluate the test results of the treatment equipment or treatment method under test based on the terminal sensing data through the Internet of Things platform, and generate a test analysis report.

[0056] Accordingly, the present invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the power quality management application verification method as described in any of the above.

[0057] Accordingly, the present invention also provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the power quality management application verification method as described in any of the above claims.

[0058] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0059] The technical solution of this invention, through editing the test plan and setting parameters for the transparent transformer substation platform and verification scenarios, can accurately and reliably build a platform for simulation operation, enabling it to possess the simulation capabilities for operating a new type of intelligent power distribution system. This supports the verification of various power quality management application functions under the background of a new power system. Simultaneously, the construction of the Internet of Things (IoT) enables panoramic perception of the platform status and transparent display of the test process, intuitively showcasing the test results, accurately and reliably collecting and acquiring the simulated data, providing a systematic and realistic testing environment, and ensuring highly reliable test results. Finally, the analysis of the test results improves test efficiency and ease of operation. Furthermore, based on the terminal sensing data collected by the IoT platform, automatic hierarchical analysis can be performed, improving the accuracy and efficiency of power quality analysis and enhancing the user's operational experience in power quality analysis and testing. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0061] Figure 1: A flowchart of the steps of a power quality management application verification method provided in an embodiment of the present invention;

[0062] Figure 2: A schematic diagram of the test implementation process provided in an embodiment of the present invention;

[0063] Figure 3: A schematic diagram of the low-voltage true-type distribution radio station area architecture provided in an embodiment of the present invention;

[0064] Figure 4: A flowchart of data transmission process of the smart gateway provided in an embodiment of the present invention;

[0065] Figure 5: A structural diagram of the real-model platform intelligent monitoring system provided in an embodiment of the present invention;

[0066] Figure 6: A schematic diagram of a real-world platform architecture for an implementation use case provided in an embodiment of the present invention;

[0067] Figure 7: A schematic diagram of an implementation use case test topology provided in an embodiment of the present invention;

[0068] Figure 8: A structural diagram of the power quality management application verification device provided in an embodiment of the present invention. Detailed Implementation

[0069] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0070] Example 1

[0071] Please refer to Figure 1, which illustrates a power quality management application verification method provided by an embodiment of the present invention. This method is implemented through a transparent transformer substation simulation platform and includes the following steps S101-S104:

[0072] Step S101: Based on the test requirements and in conjunction with the transparent transformer substation model platform, edit and generate a test plan; wherein, the test plan includes: the treatment equipment to be tested or the treatment method to be evaluated, and the transparent transformer substation model platform is used to provide verification scenarios for several types of power quality treatment functions.

[0073] In this embodiment, the test plan guides the overall test process. As shown in Figure 2, the real-world platform management system has a typical case editing function, which can edit and preset typical test plans. The specific test plan content includes: test requirements analysis, test topology determination, test parameter determination, test detection data determination, and test result analysis.

[0074] As a preferred embodiment, the transparent distribution area real-world platform includes: traditional distribution area key equipment, new distribution area equipment, a power quality management area for accessing power quality management equipment through standardized interfaces, and a smart gateway for IoT networking of smart switches and smart sensing terminals within the distribution area.

[0075] It should be noted that the transparent distribution area simulation platform can realistically simulate the operating characteristics of new distribution areas with a high proportion of distributed power sources and power electronic equipment access. It can also set up typical test scenarios and connect the devices under test for different power quality problems, realizing diversified power quality governance scenario simulation. This supports the functional verification of power quality governance equipment and methods in distribution areas under the background of new power systems, and improves the power quality level of distribution areas.

[0076] In this embodiment, the transparent distribution area simulation platform, as shown in Figure 3, is used to simulate the operational characteristics of new distribution areas and provide a verification environment for power quality management applications that conforms to actual on-site conditions. The transparent distribution area simulation platform includes key equipment of traditional distribution areas such as distribution transformers, integrated distribution boxes (JP cabinets), branch boxes, household meter boxes, and user equipment; it also features characteristic elements of new distribution areas such as distributed simulated power supplies and simulated charging piles, enabling the simulation of typical operating scenarios for new distribution areas; simultaneously, the simulation platform is configured with a power quality management area, providing standardized interfaces for the actual connection of power quality management equipment such as smart capacitors, active power filters, and static var generators.

[0077] It should be noted that the low-voltage simulation platform is configured with intelligent gateways and various sensing devices for IoT networking in the distribution area. The intelligent gateway is an IoT edge computing terminal applied to the low-voltage intelligent distribution area, integrating functions such as distribution area power supply information collection, equipment status monitoring and communication networking, local analysis and decision-making, and master station communication.

[0078] In this embodiment, the terminal adopts a platform-based hardware design and edge computing architecture, supporting local data storage and decision analysis. The data transmission flow of the smart gateway is shown in Figure 4. Internally, the gateway uses the MQTT protocol as its data bus. Various monitoring data from the distribution area are accessed through different protocols and then distributed to different applications via the MQTT bus for edge computing or storage. The smart gateway interacts with the IoT platform via the MQTT protocol, receiving instructions from the IoT platform and uploading monitoring data information from the distribution area. In this invention, the IoT platform function is implemented by a real-world platform test management system.

[0079] In this embodiment, the intelligent gateway serves as the core, and intelligent switches and intelligent sensing terminals within the distribution area are networked together via the Internet of Things (IoT) to construct a true-model intelligent monitoring system as shown in Figure 5. This system enables real-time monitoring of various data, including electrical protection and control, environmental monitoring, video surveillance, and security alarms, creating a transparent, true-model test platform with panoramic status awareness. In the proposed power quality management application verification technology solution, the entire test process can be collected and displayed in real-time through the distribution network IoT, providing a clear visual representation of the test results.

[0080] Step S102: According to the test plan, set the parameters of the transparent platform and the verification scenario.

[0081] In this embodiment, the test parameter settings are based on the one-click generated test plan, and specific test parameter settings are performed, including two parts: platform parameter settings and scenario parameter settings. Platform parameter settings configure a true-type platform network according to the topology model in the test plan, constructing a true-type platform test topology network that meets the test requirements, and completing the connection and initialization of the corresponding devices. Scenario parameter settings are used to set platform device parameters and connect and set parameters for the device under test (DUT), to simulate different abnormal power quality operating conditions and the DUT's grid-connected operation. The specific parameter settings are those determined in step S1, "Test Parameter Determination".

[0082] Step S103: Conduct an experiment on the IoT platform constructed by the smart gateway, smart switches and smart sensing terminals in the transparent transformer area real-model platform after parameter settings, and monitor the test data during the experiment to obtain terminal sensing data.

[0083] In this embodiment, online monitoring of test data can be achieved through a distribution Internet of Things (IoT) built around a smart gateway. Various smart sensing terminals and power quality analyzers in the prototype platform collect real-time data on the status of key equipment and key node parameters during the test, which is then sent to the smart gateway. The smart gateway directly forwards the collected terminal sensing data or, after edge computing, forwards it to the IoT platform for data display and advanced application analysis.

[0084] Step S104: Through the IoT platform, analyze and evaluate the test results of the treatment equipment to be tested or the treatment method to be evaluated based on the terminal sensing data, and generate a test analysis report.

[0085] In this embodiment, the IoT platform automatically analyzes and evaluates the test results of the treatment equipment or treatment method under test based on the status perception data of the entire test process, and automatically generates a test analysis report.

[0086] Implementing the above embodiments has the following effects:

[0087] The technical solution of this invention, through editing the test plan and setting parameters for the transparent transformer substation platform and verification scenarios, can accurately and reliably build a platform for simulation operation, enabling it to possess the simulation capabilities for operating a new type of intelligent power distribution system. This supports the verification of various power quality management application functions under the background of a new power system. Simultaneously, the construction of the Internet of Things (IoT) enables panoramic perception of the platform status and transparent display of the test process, intuitively showcasing the test results, accurately and reliably collecting and acquiring the simulated data, providing a systematic and realistic testing environment, and ensuring highly reliable test results. Finally, the analysis of the test results improves test efficiency and ease of operation. Furthermore, based on the terminal sensing data collected by the IoT platform, automatic hierarchical analysis can be performed, improving the accuracy and efficiency of power quality analysis and enhancing the user's operational experience in power quality analysis and testing.

[0088] Example 2

[0089] This embodiment provides a preferred implementation scheme for each step (including steps S101-S104) in Embodiment 1.

[0090] As a preferred embodiment, the step of editing and generating the test plan based on the test requirements and in conjunction with the transparent platform area specifically includes:

[0091] The test requirements are analyzed to determine the types of power quality problems to be simulated, thus obtaining the test type. Based on the test requirements and the configuration of the transparent transformer substation platform, a test topology model is created to confirm the source-load equipment and data acquisition equipment required in the test topology. Based on the test requirements, the degree of power quality anomaly to be simulated is determined, and the test data to be monitored is identified. According to the degree of power quality anomaly and the test data to be monitored, a typical verification scenario is edited, and a test result analysis process is set. The test implementation process is then planned based on the typical verification scenario, and the test execution steps are determined. The test type, the corresponding edited test topology, the test data to be monitored, the typical verification scenario, and the test execution steps are pre-saved as typical implementation cases, serving as the generated test plan.

[0092] In this embodiment, the test plan is used to guide the overall test process. The real-world platform management system has a typical case editing function, which can edit and preset typical test cases. Specifically, the implementation is as follows: First, test requirements are analyzed to clarify the types of power quality problems to be simulated. Then, based on the test requirements and platform configuration, test topology modeling and typical test scenario editing are performed, and the test implementation process is planned to determine detailed test execution steps. Finally, the test type and the corresponding edited test topology, test scenario, and test process are pre-saved as typical implementation cases. This allows for one-click generation of typical test plans when conducting similar experiments, improving test efficiency.

[0093] In this embodiment, a typical implementation case may include: test requirements analysis, test topology determination, test parameter determination, test detection data determination, and test result analysis. Specifically, test requirements analysis involves determining the type of power quality problem to be simulated in the test area; test topology determination involves determining the topology required to construct the power quality anomaly scenario, i.e., confirming the source and load equipment and data acquisition equipment required for the test; test parameter determination involves determining the degree of power quality anomaly to be simulated, such as the expected voltage value in voltage quality anomaly problems, the load imbalance degree in three-phase imbalance problems, the harmonic order and harmonic content in harmonic anomaly problems, and the photovoltaic output and load power in photovoltaic backfeeding problems; test data acquisition involves determining the key test data that needs to be monitored in real time, including real-time voltage and current data in voltage quality management; three-phase power of distribution transformers in three-phase imbalance management; harmonic content of each order in harmonic anomaly management; and voltage, current, and meter energy data of photovoltaic power generation branches in photovoltaic backfeeding management; and test result analysis involves determining the evaluation criteria and judging the effectiveness of power quality management based on different test scenarios. The evaluation criteria are the key data collected during the experimental data acquisition process.

[0094] As a preferred embodiment, the parameter settings for the transparent platform and the verification scenario, based on the test plan, specifically include:

[0095] Based on the platform network configuration of the test topology in the test plan, a real-type platform test topology network that meets the test requirements is constructed, and the corresponding equipment under test is connected and initialized, thereby completing the parameter settings of the transparent transformer area real-type platform; based on the source-load equipment and data acquisition equipment required by the test topology in the test plan and the test data to be monitored, combined with the corresponding connected and initialized equipment under test, the parameters of the verification scenario are set; wherein, the equipment under test is connected to the grid and operated together with different power quality abnormal operation conditions.

[0096] In this embodiment, the test parameter settings are based on the one-click generated test plan, and specific test parameter settings are performed, including two parts: platform parameter settings and scenario parameter settings. Platform parameter settings configure a true-type platform network according to the topology model in the test plan, constructing a true-type platform test topology network that meets the test requirements, and completing the connection and initialization of the corresponding devices. Scenario parameter settings are used to set platform device parameters and connect and set parameters for the device under test (DUT), so as to simulate different abnormal power quality operating conditions and enable the DUT to operate on the grid.

[0097] In this embodiment, the specific parameter settings are those determined in step S1 of embodiment one, under "Determining Experimental Parameters". By using the source-load equipment, data acquisition equipment, and test data to be monitored required by the experimental topology in the experimental plan, combined with the corresponding connected and initialized governance equipment, the parameters of the corresponding verification scenario are set, thereby improving the accuracy of the simulation scenario.

[0098] As a preferred embodiment, the step of testing the IoT platform constructed from the smart gateway, smart switches, and smart sensing terminals in the transparent transformer area real-world platform after parameter settings, and monitoring the test data and acquiring terminal sensing data during the test, specifically includes:

[0099] The devices under test (DUTs), after parameter settings and initialization, are used as intelligent sensing terminals. These terminals are connected to their respective intelligent switches, and each connected intelligent switch is configured with a corresponding intelligent gateway, thus constructing an IoT platform. After constructing the IoT platform, a transparent distribution area power management test is conducted based on the test plan and simulations of different abnormal power quality operating conditions corresponding to the DUTs. The power management test includes a power quality abnormal operating condition simulation phase and a management phase. Based on the intelligent sensing terminals and power quality analyzers within the IoT platform, test data is monitored during the test, thereby real-time sensing and collection of key equipment status and key node parameters. This data is then aggregated to the intelligent gateway as terminal sensing data. The terminal sensing data includes abnormal phase data, management phase data, and post-management data. The terminal sensing data aggregated to the intelligent gateway is directly forwarded or forwarded to the IoT platform via edge computing for data display and advanced application analysis.

[0100] In this embodiment, online monitoring of test data can be achieved through a distribution Internet of Things (IoT) built around a smart gateway. Various smart sensing terminals and power quality analyzers in the prototype platform collect real-time data on the status of key equipment and key node parameters during the test, which is then sent to the smart gateway. The smart gateway then forwards the collected terminal sensing data directly or via edge computing to the IoT platform for data display and advanced application analysis.

[0101] In this embodiment, the device under test (DUT) acts as a smart sensing terminal and needs to be connected to the system after parameter settings. These devices will be connected to corresponding smart switches to achieve data acquisition and control signal transmission. After the smart switches are connected to the smart sensing terminals, corresponding smart gateways need to be set up for these connections. The smart gateway, as a key device for data acquisition, transmission, and processing, is responsible for aggregating and initially processing the data from the front-end devices. This allows the construction of an Internet of Things (IoT) platform that integrates functions such as device access, data transmission, data processing, and application services. This platform will support the connection of massive numbers of devices and provide data services such as data access, parsing, storage, and analysis. Based on the test plan, different abnormal power quality operating conditions will be simulated to test the performance of the DUT. This includes the simulation of power quality indicators such as voltage deviation, frequency deviation, harmonics, and three-phase voltage imbalance. The power quality management test includes a power quality abnormal operating condition simulation phase and a management phase. In the simulation phase, we will simulate various abnormal situations in the power grid; in the management phase, the DUT will attempt to compensate for and adjust these abnormalities. During the trial, intelligent sensing terminals and power quality analyzers will monitor and collect the status of key equipment and parameters of critical nodes in real time. This data will serve as terminal sensing data, including data from anomaly phases, remediation phases, and post-remediation phases. The terminal sensing data will be aggregated at a smart gateway and then forwarded directly or after edge computing processing to the IoT platform. Edge computing allows data processing near the data source, reducing latency and improving response speed. On the IoT platform, the aggregated data will be used for data visualization and advanced application analysis, including evaluating the effectiveness of power remediation, monitoring equipment performance, developing optimization strategies, and other extended functions.

[0102] As a preferred embodiment, the step of analyzing and evaluating the test results of the treatment equipment or treatment method under test based on the terminal sensing data through the IoT platform, and generating a test analysis report, specifically includes:

[0103] Through the IoT platform, the actual scenario is obtained by parsing the collected terminal sensing data. The actual scenario is then compared with the verification scenario. When the actual scenario matches the verification scenario, the abnormal stage data in the terminal sensing data is analyzed to obtain the corresponding actual abnormal operating conditions, and the actual sensing device is identified. If the actual sensing device corresponds to the device under test, and the actual abnormal operating conditions of the actual sensing device are the same as the power quality abnormal operating conditions corresponding to the device under test, then the treatment stage data and post-treatment data in the terminal sensing data are analyzed. Based on a preset evaluation model, the treatment stage data and post-treatment data are automatically analyzed to automatically generate a test analysis report.

[0104] In this embodiment, the IoT platform automatically analyzes and evaluates the test results of the treatment equipment or treatment method under test based on the status perception data throughout the test process, and automatically generates a test analysis report. The basis for test result analysis varies significantly depending on the type of test; the detailed judgment is based on the parameters determined within the "Test Data Acquisition" section.

[0105] In this embodiment, a large amount of data is collected from intelligent sensing terminals through an IoT platform. This data includes electrical parameters such as voltage, current, and frequency, as well as the operating status of the equipment and environmental conditions. Using big data analytics, the actual operating scenario can be extracted from this complex data, providing a foundation for subsequent verification and comparison. The extracted actual scenario is compared with a pre-set verification scenario. If they match, it indicates that the collected data accurately reflects the actual power quality. Based on this, further analysis of abnormal stage data in the terminal sensing data is conducted to determine the actual abnormal operating conditions and identify the equipment malfunctioning.

[0106] In this embodiment, once the actual abnormal operating condition is identified, it is necessary to determine whether the device experiencing the abnormality is the device under test (DUT) of interest. If the actual sensing device corresponds to the DUT, and its abnormal operating condition matches the preset abnormal power quality operating condition of the DUT, this indicates that the DUT is undergoing the expected test conditions. After confirming the abnormal operating condition, the governance phase data in the terminal sensing data is analyzed, including the DUT's response to the abnormal operating condition and compensation measures, as well as the effectiveness of these measures. After the governance phase, post-governance data continues to be collected and analyzed to evaluate the performance and effectiveness of the DUT, including the recovery of power parameters and the stability of the device. Based on a preset evaluation model, the IoT platform can automatically analyze the governance phase data and post-governance data. The preset evaluation model may include the degree of improvement in power quality indicators, the device's response time, compensation efficiency, etc. Through these analyses, the platform can automatically generate a test analysis report, which will include a detailed description of the abnormal operating condition, an evaluation of the effectiveness of the governance measures, and suggestions for subsequent improvements.

[0107] In this embodiment, the generated test analysis report will provide crucial insights to help users and operators understand the performance of the power treatment equipment under test and guide them to make necessary adjustments. The report may include the following: a detailed description of the actual abnormal operating conditions and the time of occurrence, the response time and compensation effect of the power treatment equipment under test, the improvement in power quality after treatment, a comprehensive evaluation of equipment performance, and optimization suggestions.

[0108] As a preferred embodiment, the method for constructing the preset evaluation model includes:

[0109] Obtain sample data corresponding to the treatment stage data and post-treatment data of the power treatment equipment under test, as well as the labeled data corresponding to the sample data; construct an initial preset evaluation model, and use the sample data and the labeled data as training data for the initial preset evaluation model, respectively, and train the initial preset evaluation model until the loss function of the initial preset evaluation model tends to fit, and then obtain the final trained preset evaluation model.

[0110] In this embodiment, to construct an evaluation model, it is first necessary to acquire sample data of the power governance equipment under test during the power governance process. This sample data includes real-time power parameters (such as voltage, current, frequency, harmonic content, etc.) during the governance phase, as well as data on the system's recovery state after governance. Simultaneously, corresponding labeled data, i.e., data labeled by experts or known results, is also required to guide model learning. Before using the sample data for training, preprocessing is necessary to improve data quality and make it suitable for model training. Preprocessing steps may include data cleaning (removing outliers and noise), normalization (making the data on the same scale), and feature engineering (extracting features that are helpful for model learning). An initial preset evaluation model is constructed, capable of evaluating the effectiveness of power governance based on data from the governance phase and after governance. This model may be based on machine learning algorithms, such as random forests, support vector machines, neural networks, etc., with the specific choice depending on data characteristics and problem complexity. Then, the initial evaluation model is trained using the preprocessed sample data and labeled data. During training, the model gradually adjusts its internal parameters to reduce prediction errors by learning the features of the sample data and the output of the labeled data. During training, the model's loss function (such as mean squared error, cross-entropy, etc.) is used to measure the difference between the predicted results and the actual labels. The goal of training is to minimize this loss function, making the model's predictions as close as possible to the actual results. During model training, it is necessary to periodically evaluate the model's performance to ensure it does not overfit (i.e., perform well on training data but poorly on unseen test data) or underfit (i.e., the model is too simple to capture the complex relationships in the data). Model performance can be optimized through methods such as cross-validation and hyperparameter tuning. After multiple iterations of training and parameter tuning, when the loss function stabilizes and the model's performance on the validation set reaches a satisfactory level, the final trained preset evaluation model can be obtained. This preset evaluation model can accurately assess the effectiveness of power governance and provide decision support for operators.

[0111] Understandably, pre-set evaluation models can accurately predict the effectiveness of power quality management, providing reliable data support for subsequent equipment optimization. Furthermore, these models possess strong generalization capabilities, enabling them to operate stably under diverse grid conditions and management scenarios. Automated evaluation using pre-set models reduces human intervention, improves evaluation efficiency and objectivity, and allows for continuous learning and adaptation to the incorporation of new data, thus addressing changes in grid conditions related to power quality management.

[0112] It is understood that this embodiment constructs a transparent, realistic distribution area platform, possessing the capability to simulate the operation of a new intelligent power distribution system. It supports the application verification of intelligent distribution area power quality management under the background of a new power system, and has comprehensive simulation capabilities for distribution area power quality anomalies such as voltage quality anomalies, three-phase imbalance, harmonic pollution, and photovoltaic backfeeding. It supports the verification of various power quality management application functions. Simultaneously, by constructing a realistic platform IoT intelligent monitoring system, it achieves panoramic perception of the platform status and transparent display of the testing process, intuitively showcasing the test results. The realistic simulation method is used to conduct power quality management function verification, providing a systematic and realistic testing environment with highly reliable test results. Furthermore, the platform management system provides functions such as scheme editing, parameter setting, and process management, enabling one-click generation of typical cases, improving testing efficiency and ease of operation.

[0113] Implementing the above embodiments has the following effects:

[0114] The technical solution of this invention, through editing the test plan and setting parameters for the transparent transformer substation platform and verification scenarios, can accurately and reliably build a platform for simulation operation, enabling it to possess the simulation capabilities for operating a new type of intelligent power distribution system. This supports the verification of various power quality management application functions under the background of a new power system. Simultaneously, the construction of the Internet of Things (IoT) enables panoramic perception of the platform status and transparent display of the test process, intuitively showcasing the test results, accurately and reliably collecting and acquiring the simulated data, providing a systematic and realistic testing environment, and ensuring highly reliable test results. Finally, the analysis of the test results improves test efficiency and ease of operation. Furthermore, based on the terminal sensing data collected by the IoT platform, automatic hierarchical analysis can be performed, improving the accuracy and efficiency of power quality analysis and enhancing the user's operational experience in power quality analysis and testing.

[0115] Example 3

[0116] This embodiment is a preferred implementation of Embodiments 1 and 2.

[0117] As a preferred embodiment, the verification scenarios for the power quality management function include: voltage quality management function verification scenario, three-phase imbalance management function verification scenario, harmonic management function verification scenario, and photovoltaic backfeed management function verification scenario.

[0118] In this embodiment, the transparent transformer substation real-model platform can completely and realistically simulate the intelligent transformer substation operation characteristics in a new power system, providing a real transformer substation test environment for carrying out application function verification of transformer substation power quality management.

[0119] As a preferred embodiment, the parameter settings for the voltage quality management function verification scenario specifically include:

[0120] A fully transparent, real-scale power supply platform for the entire distribution area is implemented using a combination of isolation transformers and voltage regulators. By setting the voltage regulator parameters, the voltage in the distribution area is controlled, thereby generating and providing scenarios for voltage fluctuations and overvoltage operation. Line impedance parameters are adjusted using a line simulation device to simulate different feeder lengths. Combined with controllable simulated loads within the platform, different combinations of feeder lengths and loads are implemented to reproduce low-voltage operation conditions at the end of the distribution area. Based on the Internet of Things (IoT) in low-voltage power distribution, the distribution area voltage is acquired in real time as the initial voltage data for the voltage fluctuation test. The voltage changes during the test are continuously monitored, serving as test data for the voltage quality management function verification scenario, thus completing the setup of the voltage quality management function verification scenario.

[0121] In this embodiment, a combination of isolation transformer and voltage regulator is used to power the entire real-model platform. By setting the voltage regulator parameters, the voltage of the transformer area is controlled, thereby providing scenarios of voltage fluctuation and overvoltage operation in the transformer area. By adjusting the line impedance parameters through the line simulation device, different feeder lengths are simulated. Combined with the controllable simulated load in the platform, different combinations of feeder lengths and different loads are performed to reproduce the low-voltage operation conditions at the end of the transformer area.

[0122] It should be noted that voltage quality issues in transformer substations mainly focus on two aspects: voltage fluctuations, overvoltage, and low voltage at the terminal. The transparent, full-scale experimental platform uses a combination of isolation transformers and voltage regulators for overall platform power supply. By setting the voltage regulator parameters, rapid and precise control of the transformer substation voltage can be achieved, providing scenarios for voltage fluctuations and overvoltage operation. Low voltage at the terminal of a transformer substation is usually caused by unreasonable line length or feeder load configuration. The full-scale platform uses a line simulation device to flexibly adjust line impedance parameters, simulating different feeder lengths. Combined with controllable simulated loads within the platform, different combinations of feeder lengths and loads can be implemented to realistically reproduce the low voltage operating conditions at the terminal of the transformer substation.

[0123] As a preferred embodiment, the step of controlling the voltage of the distribution area by setting the voltage regulator parameters specifically includes:

[0124] By adjusting the voltage regulator, the contact position between the brush and the coil is changed, thereby altering the turns ratio of the primary and secondary coils, and thus regulating the output voltage to control the regional voltage.

[0125] In this embodiment, the three-phase voltage regulator is a contact-type autotransformer connected to the output terminal of the isolation transformer. After confirming reliable wiring, the output voltage is regulated by adjusting the regulator knob to change the contact position between the brushes and the coils, thereby altering the turns ratio of the primary and secondary coils. The prototype platform can acquire the transformer substation voltage in real time based on the low-voltage distribution IoT, serving as the initial voltage data for the transformer substation voltage fluctuation test, and continuously monitor the voltage change process during the test to verify the effectiveness of transformer substation voltage fluctuation and overvoltage mitigation.

[0126] As a preferred embodiment, the parameter settings for the three-phase imbalance mitigation function verification scenario specifically include:

[0127] Based on the aforementioned test plan, the load imbalance of the transformer area is determined. According to this load imbalance, a controllable, feeder-type simulated load is configured to set the three-phase power, thereby enabling the feeders of the transparent transformer area simulation platform to operate in an unbalanced state. By configuring an intelligent phase-switching switch, the unbalanced operation in the transparent transformer area simulation platform is mitigated. The intelligent phase-switching switch provides a standardized interface, allowing for the demonstration of three-phase unbalance mitigation while simultaneously connecting and functionally testing the device under test, thus completing the setup of the three-phase unbalance mitigation function verification scenario.

[0128] In this embodiment, three-phase imbalance in the distribution area increases line and transformer line losses, reduces power supply efficiency, and may endanger the safety of distribution transformers and user equipment. The transparent distribution area simulation platform is equipped with a controllable, rechargeable simulated load capable of operating under unbalanced conditions, allowing the platform feeders to operate stably within a certain unbalance range. Intelligent phase-switching switches are commonly used to manage three-phase imbalance in distribution areas. The simulation platform is equipped with intelligent phase-switching switches and provides standardized interfaces, facilitating demonstrations of three-phase imbalance management while also enabling easy connection and functional testing of the switchgear under test.

[0129] In this embodiment, the transparent distribution substation platform is equipped with a regenerative controllable simulated load capable of unbalanced operation. This regenerative controllable simulated load can independently set the power of its three phases (A, B, and C). Based on the specific requirements of the three-phase imbalance mitigation function test, various substation load imbalance degrees can be flexibly set, providing test scenarios with different power and imbalance degrees for the intelligent phase-switching switch. The full-scale distribution substation is equipped with an intelligent phase-switching switch, a commonly used device for mitigating three-phase imbalance in distribution substations. After the full-scale platform sets the substation's unbalanced operating state based on the regenerative controllable load, it communicates with the intelligent phase-switching switch and controls the load phase switching in the substation through the intelligent phase-switching switch, ensuring overall three-phase balanced operation of the distribution substation and completing the demonstration of the three-phase imbalance mitigation function.

[0130] As a preferred embodiment, the parameter settings for the harmonic mitigation function verification scenario specifically include:

[0131] Based on the positive harmonic output of the energy-feedable controllable simulated load, harmonics are injected into the power grid in the transparent transformer substation platform through energy feedback, thereby simulating a harmonic pollution scenario. The device under test is connected to the interface of the transformer substation's reserved harmonic mitigation device, and the changes in harmonics in the transformer substation are monitored in real time through the Internet of Things of the transformer substation power distribution, thereby completing the setting of the harmonic mitigation function verification scenario.

[0132] In this embodiment, based on the harmonic output capability of the energy-feedable controllable simulated load, harmonics are injected into the power grid through energy feedback, thereby realizing the simulation of typical harmonic pollution scenarios of a transparent transformer substation platform.

[0133] It should be noted that the energy-feeding controllable simulated load in the transparent transformer substation full-scale platform has harmonic output capability. It injects specific harmonics into the power grid through energy feedback, thereby simulating typical harmonic pollution scenarios of the full-scale platform.

[0134] In this embodiment, the energy-feedable controllable simulated load has a bidirectional energy flow function, enabling automatic and seamless switching between forward and reverse directions. It also supports customized generation of harmonics of different frequencies and their injection into the real-world platform, thus constructing operating scenarios for transformer area harmonic pollution of different frequencies and concentrations. After completing the construction of the harmonic pollution scenario, the device under test is connected based on the interface of the transformer area's reserved harmonic mitigation device, and the changes in transformer area harmonics are monitored in real time through the transformer area's power distribution IoT, completing the verification of the harmonic mitigation function of the device under test.

[0135] As a preferred embodiment, the parameter settings for the photovoltaic backfeeding control function verification scenario specifically include:

[0136] Based on the aforementioned test plan, the characteristics of the photovoltaic modules to be simulated are determined. A programmable photovoltaic cell is configured to simulate the light intensity, temperature, and shading parameters corresponding to the photovoltaic module's special effects. A photovoltaic simulation system is constructed based on a photovoltaic inverter with active and reactive power outputs corresponding to the test plan, combined with the photovoltaic cell. This system is used to set the photovoltaic output curve of a transparent distribution area's full-scale platform. Combined with a preset load power curve within the distribution area, the simulation of the distribution area's photovoltaic system transitioning from normal operation to a photovoltaic backfeed scenario is achieved. During the simulation, smart meters and sensors within the distribution area are used to acquire real-time voltage, current, and power generation data, which serve as test data for the photovoltaic backfeed governance function verification scenario, thus completing the setup of the photovoltaic backfeed governance function verification scenario.

[0137] In this embodiment, by configuring a programmable simulated photovoltaic cell, the characteristics of the photovoltaic module under different light intensities, temperatures, and shading conditions are simulated. A photovoltaic curve editing function is set up, and the photovoltaic system transitions from normal operation to photovoltaic backfeed state by setting a preset photovoltaic characteristic curve, thereby providing a test field for verifying the photovoltaic backfeed control function.

[0138] It should be noted that the rapid development of new energy technologies has led to the large-scale integration of distributed photovoltaic (PV) systems into low-voltage distribution substations. While bringing convenience to users, this also presents the potential risk of PV backfeeding. PV backfeeding occurs when factors such as shading of the PV system, uneven local illumination, or temperature gradients cause the output voltage of the PV modules to be lower than the voltage at the load end, resulting in current flowing from the load end to the PV modules. PV backfeeding can cause excessively high voltage at the load end and elevated bus voltage in the distribution substation, severely impacting the power quality of the area.

[0139] The programmable simulated photovoltaic cells configured in the real-model distribution transformer area can simulate the characteristics of photovoltaic modules under different light intensities, temperatures, and shading conditions. It also supports photovoltaic curve editing functions. By preset photovoltaic characteristic curves, the transition of the photovoltaic system from normal operation to photovoltaic backfeed state can be set, providing test scenarios for verifying photovoltaic backfeed control functions.

[0140] In this embodiment, a high-power programmable photovoltaic (PV) simulation system is configured in the full-scale distribution substation, including a programmable simulated PV cell and a PV inverter. The PV simulated cell can simulate the characteristics of PV modules under different light intensities, temperatures, and shading conditions; the PV inverter can be set to different active and reactive power outputs and supports power curve settings. Combined with the PV simulated cell, various PV power generation system operating characteristics can be simulated within the full-scale platform of the substation. Based on the PV output curve set in the full-scale platform using the PV simulation system, and in conjunction with the programmable simulated load power curve set within the substation, flexible coordination between PV power generation and load power within the substation can be achieved. This allows for realistic simulation of the transition from normal PV operation to PV backfeed scenarios, providing a simulation scenario for PV backfeed control function verification. During the function verification process, smart meters and smart sensors within the distribution substation acquire real-time substation voltage, current, and power generation data, providing data support for evaluating the control effect.

[0141] Implementing the above embodiments has the following effects:

[0142] The technical solution of this invention, through editing the test plan and setting parameters for the transparent transformer substation platform and verification scenarios, can accurately and reliably build a platform for simulation operation, enabling it to possess the simulation capabilities for operating a new type of intelligent power distribution system. This supports the verification of various power quality management application functions under the background of a new power system. Simultaneously, the construction of the Internet of Things (IoT) enables panoramic perception of the platform status and transparent display of the test process, intuitively showcasing the test results, accurately and reliably collecting and acquiring the simulated data, providing a systematic and realistic testing environment, and ensuring highly reliable test results. Finally, the analysis of the test results improves test efficiency and ease of operation. Furthermore, based on the terminal sensing data collected by the IoT platform, automatic hierarchical analysis can be performed, improving the accuracy and efficiency of power quality analysis and enhancing the user's operational experience in power quality analysis and testing.

[0143] Example 4

[0144] Based on the transparent transformer area true-form platform architecture shown in Figure 2, a transparent transformer area true-form platform consisting of two interconnected transformer areas is constructed, as shown in Figure 6.

[0145] Based on the transparent transformer substation full-scale platform shown in Figure 6, the application function verification of three-phase imbalance and harmonic pollution control in the transformer substation was carried out. The main implementation steps include:

[0146] (1) Experimental Protocol Editing

[0147] Based on the experimental requirements and the hardware configuration of the real platform shown in Figure 6, the required experimental topology model is determined as shown in Figure 7.

[0148] In the test topology, the three-phase simulated load Load1 has a rated power of 20kW; the single-phase simulated loads Load2 to Load4 have a rated power of 3.3kW, and are connected to the A, B, and C phases of the AC feeder, respectively; the commutator switch SB can be remotely deactivated via software and connected to the commutator switch under test via the platform's device under test interface to conduct verification of the three-phase imbalance mitigation function.

[0149] (2) Experimental parameter design

[0150] First, set Load1 to run normally with all three phases having a current of 20A. After running for 1 minute, switch to three-phase unbalanced operation with the three phases having currents of 10A for phase A, 30A for phase B, and 20A for phase C. Then, set the load current of the single-phase simulated loads Load2 to Load4 to be 10A. Finally, set the platform phase commutation switch SB to exit operation and connect the phase commutation switch SB' to be tested before starting the test.

[0151] (3) Test data monitoring

[0152] During the test, the power quality monitoring equipment acquires the three-phase current data at the outlet T1 of the distribution transformer (including the voltage regulator) in real time, and transmits it to the IoT management platform for data display and analysis via a smart gateway based on the IoT of the distribution area; similarly, the switch under test SB' uploads its own switch status to the IoT platform in real time through the smart gateway.

[0153] (4) Analysis of experimental results

[0154] Based on the three-phase current data at T1 obtained from the IoT platform and the status data of the tested commutator SB', the three-phase imbalance mitigation function of the commutator can be analyzed. In this embodiment, this is mainly reflected in the following: after the three-phase simulated load enters an unbalanced operating state at 1 minute, three-phase unbalanced current data will be detected at T1. Simultaneously, the commutator SB' controller also acquires the feeder's three-phase unbalanced current. Without power outage, it should trigger a commutation action, switching the single-phase simulated load Load3 from phase B to phase A, so that the detected three-phase current data at the transformer outlet T1 returns to a balanced state. By observing whether the commutator operates and its operation delay during the test, its three-phase imbalance mitigation application function can be evaluated.

[0155] Implementing the above embodiments has the following effects:

[0156] (1) A transparent distribution area simulation platform was constructed, which has the ability to simulate the operation of a new type of intelligent power distribution system and can support the application verification of intelligent distribution area power quality governance under the background of new power system.

[0157] (2) It has comprehensive simulation capabilities for power quality anomalies in distribution areas, such as voltage quality anomalies, three-phase imbalance, harmonic pollution, and photovoltaic backfeeding, and supports the verification of various power quality governance application functions.

[0158] (3) By constructing a real-world platform IoT intelligent monitoring system, we can achieve panoramic perception of the platform status and transparent display of the test process, and intuitively show the test results;

[0159] (4) The power quality management function is verified by adopting a real-model simulation method, which provides a systematic and realistic test environment and the test results are highly reliable;

[0160] (5) Based on the platform management system, it provides functions such as scheme editing, parameter setting, and process management, which can realize one-click generation of typical cases, improve experimental efficiency and ease of operation.

[0161] Example 5

[0162] Please refer to Figure 8, which is a power quality management application verification device provided by the present invention for a transparent transformer substation real-model platform, including: a scheme editing module 201, a parameter setting module 202, a data monitoring module 203, and a result analysis module 204;

[0163] The scheme editing module 201 is used to edit and generate a test scheme according to the test requirements and in conjunction with the transparent transformer substation model platform; wherein, the test scheme includes: the treatment equipment to be tested or the treatment method to be evaluated, and the transparent transformer substation model platform is used to provide verification scenarios for several types of power quality treatment functions;

[0164] The parameter setting module 202 is used to set the parameters of the transparent platform and the verification scenario according to the test plan.

[0165] The data monitoring module 203 is used to conduct experiments on the Internet of Things platform constructed by the smart gateway, smart switches and smart sensing terminals in the transparent transformer area real-model platform after parameter settings, and to monitor the experimental data and obtain terminal sensing data during the experiment.

[0166] The result analysis module 204 is used to analyze and evaluate the test results of the treatment equipment to be tested or the treatment method to be evaluated based on the terminal sensing data through the Internet of Things platform, and generate a test analysis report.

[0167] As a preferred embodiment, the step of editing and generating a test plan based on test requirements and the transparent platform model specifically includes:

[0168] The test requirements are analyzed to determine the types of power quality problems that need to be simulated, thus obtaining the test type;

[0169] Based on the test requirements and the configuration of the transparent transformer area real-type platform, test topology modeling is performed to confirm the source-load equipment and data acquisition equipment that need to be put into the test topology.

[0170] Based on the experimental requirements, determine the degree of power quality anomaly to be simulated in the experiment, and determine the experimental data to be monitored;

[0171] Based on the degree of power anomaly and the test data to be monitored, a typical verification scenario is compiled, and a test result analysis process is set. In this way, the test implementation process is planned in conjunction with the typical verification scenario, and the test execution steps are determined.

[0172] The test type, the corresponding edited test topology, the test data to be monitored, the typical verification scenarios, and the test execution steps are pre-saved as typical implementation cases, which serve as the edited and generated test schemes.

[0173] As a preferred embodiment, the parameter settings for the transparent platform and the verification scenario, based on the test plan, specifically include:

[0174] Based on the platform network configuration of the test topology in the test plan, a real-type platform test topology network that meets the test requirements is constructed, and the corresponding treatment equipment to be tested is connected and initialized, thereby completing the parameter settings of the transparent transformer area real-type platform;

[0175] Based on the source-load equipment and data acquisition equipment required for the test topology in the test plan, and the test data to be monitored, the parameters of the verification scenario are set in conjunction with the corresponding connected and initialized governance equipment under test; wherein, the governance equipment under test is connected to the grid and operated together with different power quality abnormal operation conditions.

[0176] As a preferred embodiment, the IoT platform constructed by the smart gateway, smart switches, and smart sensing terminals in the transparent transformer area real-world platform after parameter settings is tested, and test data is monitored during the test to obtain terminal sensing data, specifically including:

[0177] The device under test, after parameter settings and initialization, is used as a smart sensing terminal. It is then connected to the corresponding smart switch, and a corresponding smart gateway is set for each connected smart switch, thereby building an Internet of Things platform.

[0178] After constructing the IoT platform, power management tests of a transparent distribution area real-model platform are conducted based on the test plan and the simulation of different abnormal power quality operating conditions corresponding to the equipment under test; wherein, the power management test includes a power quality abnormal operating condition simulation stage and a management stage;

[0179] Based on the intelligent sensing terminals and power quality analyzers in the IoT platform, test data is monitored during the test, thereby sensing and collecting the status of key equipment and key node parameters in real time, and then collecting them as terminal sensing data to the intelligent gateway; wherein, the terminal sensing data includes abnormal stage data, governance stage data, and post-governance data;

[0180] The terminal sensing data collected at the smart gateway is forwarded directly or after edge computing to the IoT platform for data display and advanced application analysis.

[0181] As a preferred embodiment, the step of analyzing and evaluating the test results of the treatment equipment or treatment method under test based on the terminal sensing data through the IoT platform, and generating a test analysis report, specifically includes:

[0182] The actual scene is obtained by analyzing the collected terminal sensing data through the IoT platform.

[0183] The actual scenario is compared with the verification scenario. When the actual scenario is consistent with the verification scenario, the abnormal stage data in the terminal perception data is analyzed to obtain the corresponding actual abnormal working condition and to determine the actual perception device.

[0184] If the actual sensing device corresponds to the device under test, and the actual abnormal operating condition of the actual sensing device is the same as the abnormal power quality operating condition corresponding to the device under test, then the data of the treatment stage and the data after treatment in the terminal sensing data are analyzed, and the data of the treatment stage and the data after treatment are automatically analyzed according to the preset evaluation model, thereby automatically generating a test analysis report.

[0185] As a preferred embodiment, the method for constructing the preset evaluation model includes:

[0186] Obtain sample data corresponding to the treatment stage data and post-treatment data of the power treatment equipment under test, as well as the annotation data corresponding to the sample data;

[0187] An initial preset evaluation model is constructed, and the sample data and the labeled data are used as training data for the initial preset evaluation model. The initial preset evaluation model is trained until the loss function of the initial preset evaluation model tends to fit, and then the final trained preset evaluation model is obtained.

[0188] As a preferred embodiment, the transparent distribution area real-world platform includes: key equipment for traditional distribution areas, new distribution area equipment, a power quality management area for accessing power quality management equipment through standardized interfaces, and an intelligent gateway for IoT networking of various smart switches and smart sensing terminals within the distribution area.

[0189] As a preferred embodiment, the verification scenarios for the power quality management function include: voltage quality management function verification scenario, three-phase imbalance management function verification scenario, harmonic management function verification scenario, and photovoltaic backfeed management function verification scenario.

[0190] As a preferred embodiment, the parameter settings for the voltage quality management function verification scenario specifically include:

[0191] The power supply of the entire transparent transformer substation is carried out by combining isolation transformers and voltage regulators. The voltage of the transformer substation is controlled by setting the voltage regulator parameters, thereby generating and providing transformer substation voltage fluctuation and overvoltage operation scenarios.

[0192] By adjusting the line impedance parameters through the line simulation device, different feeder lengths are simulated. Combined with the controllable simulated load in the platform, different combinations of feeder lengths and different loads are performed to reproduce the low voltage operation conditions at the end of the transformer area.

[0193] Based on the Internet of Things in low-voltage power distribution, the voltage of the transformer area is acquired in real time as the initial voltage data for the transformer area voltage fluctuation test, and the changes in the transformer area voltage during the test are continuously monitored as test data for the voltage quality governance function verification scenario, thereby completing the setting of the voltage quality governance function verification scenario.

[0194] As a preferred embodiment, the control of the transformer area voltage by setting voltage regulator parameters specifically includes:

[0195] By adjusting the voltage regulator, the contact position between the brush and the coil is changed, thereby altering the turns ratio of the primary and secondary coils, and thus regulating the output voltage to control the regional voltage.

[0196] As a preferred embodiment, the parameter settings for the three-phase imbalance mitigation function verification scenario specifically include:

[0197] Based on the aforementioned test scheme, the load imbalance of the transformer area is determined, and according to the load imbalance of the transformer area, a controllable simulated load with energy feedback is configured to set the three-phase power, thereby enabling the feeder of the transparent transformer area real-model platform to operate in an unbalanced state.

[0198] By configuring an intelligent phase-switching switch, the imbalance state of the transparent transformer area real-model platform is managed. The intelligent phase-switching switch provides a standardized interface, thereby demonstrating the three-phase imbalance management while simultaneously connecting and functionally testing the device under test, thus completing the setup of the three-phase imbalance management function verification scenario.

[0199] As a preferred embodiment, the parameter settings for the harmonic mitigation function verification scenario specifically include:

[0200] Based on the positive harmonic output of the energy-feedable controllable simulated load, harmonics are injected into the power grid in the transparent transformer substation platform through energy feedback, thereby enabling the transparent transformer substation platform to simulate a harmonic pollution scenario.

[0201] The device under test is connected to the interface of the pre-reserved harmonic mitigation device in the transformer substation, and the changes in harmonics in the transformer substation are monitored in real time through the Internet of Things of the transformer substation power distribution, thereby completing the setting of the harmonic mitigation function verification scenario.

[0202] As a preferred embodiment, the parameter settings for the photovoltaic backfeeding control function verification scenario specifically include:

[0203] Based on the aforementioned test plan, the characteristics of the photovoltaic modules to be simulated are determined, and the light intensity, temperature, and shadow parameters corresponding to the special effects of the photovoltaic modules are simulated by configuring programmable simulated photovoltaic cells.

[0204] Based on the photovoltaic inverter with active and reactive power outputs corresponding to the test scheme, a photovoltaic simulation system is constructed in conjunction with the photovoltaic cells, and the photovoltaic output curve of the transparent transformer area real platform is set through the photovoltaic simulation system.

[0205] By combining the preset load power curve within the distribution area, the simulation operation of the photovoltaic system in the distribution area can be realized from normal operation to photovoltaic reverse power scenario.

[0206] During the simulation operation, the voltage, current and power generation data of the distribution area are acquired in real time by smart meters and smart sensors in the distribution area. This data serves as test data for the photovoltaic backfeeding control function verification scenario, thereby completing the setting of the photovoltaic backfeeding control function verification scenario.

[0207] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0208] Implementing the above embodiments has the following effects:

[0209] The technical solution of this invention, through editing the test plan and setting parameters for the transparent transformer substation platform and verification scenarios, can accurately and reliably build a platform for simulation operation, enabling it to possess the simulation capabilities for operating a new type of intelligent power distribution system. This supports the verification of various power quality management application functions under the background of a new power system. Simultaneously, the construction of the Internet of Things (IoT) enables panoramic perception of the platform status and transparent display of the test process, intuitively showcasing the test results, accurately and reliably collecting and acquiring the simulated data, providing a systematic and realistic testing environment, and ensuring highly reliable test results. Finally, the analysis of the test results improves test efficiency and ease of operation. Furthermore, based on the terminal sensing data collected by the IoT platform, automatic hierarchical analysis can be performed, improving the accuracy and efficiency of power quality analysis and enhancing the user's operational experience in power quality analysis and testing.

[0210] Example 6

[0211] Accordingly, the present invention also provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the power quality management application verification method as described in any of the above embodiments.

[0212] The terminal device of this embodiment includes a processor, a memory, and a computer program and computer instructions stored in the memory and executable on the processor. When the processor executes the computer program, it implements the various steps in Embodiment 1 above, such as steps S101 to S104 shown in FIG1. ​​Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above device embodiment, such as the data monitoring module 203.

[0213] For example, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the terminal device. For example, the data monitoring module 203 is used to test the IoT platform constructed by the smart gateway, smart switches, and smart sensing terminals in the transparent transformer area simulation platform after parameter settings, and to monitor test data and acquire terminal sensing data during the test.

[0214] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the schematic diagram 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 illustrated, or combine certain components, or different components. For example, the terminal device may also include input / output devices, network access devices, buses, etc.

[0215] The processor can 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 can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0216] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the mobile terminal, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0217] Wherein, if the modules / units integrated in the terminal device are implemented as software functional units and sold or used as independent products, they 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 of the present invention 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 the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. Wherein, the computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, portable hard drive, magnetic disk, optical disk, 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 contained 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, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0218] Example 7

[0219] Accordingly, the present invention also provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the power quality management application verification method as described in any of the above embodiments.

[0220] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of 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, indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0221] 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.

[0222] Furthermore, the functional units in the various embodiments of the present invention 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.

[0223] If the integrated 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, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0224] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention 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. Such 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 the present invention.

Claims

1. A power quality management application verification method, characterized in that, This is achieved through a transparent, real-world platform, including: Based on the test requirements and in conjunction with the transparent transformer substation full-scale platform, a test plan is edited and generated; wherein, the test plan includes: the treatment equipment to be tested or the treatment method to be evaluated, and the transparent transformer substation full-scale platform is used to provide verification scenarios for several types of power quality treatment functions; According to the test plan, the parameter settings for the transparent platform and the parameter settings for the verification scenario are as follows: The IoT platform constructed by the smart gateway, smart switches and smart sensing terminals in the transparent transformer area real-model platform after parameter settings were tested, and the test data was monitored during the test to obtain terminal sensing data. The IoT platform is used to analyze and evaluate the test results of the treatment equipment or treatment method under test based on the terminal sensing data, and to generate a test analysis report.

2. The power quality management application verification method as described in claim 1, characterized in that, The process of editing and generating a test plan based on test requirements and the transparent platform model specifically includes: The test requirements are analyzed to determine the types of power quality problems that need to be simulated, thus obtaining the test type; Based on the test requirements and the configuration of the transparent transformer area real-type platform, test topology modeling is performed to confirm the source-load equipment and data acquisition equipment that need to be put into the test topology. Based on the experimental requirements, determine the degree of power quality anomaly to be simulated in the experiment, and determine the experimental data to be monitored; Based on the degree of power anomaly and the test data to be monitored, a typical verification scenario is compiled, and a test result analysis process is set. In this way, the test implementation process is planned in conjunction with the typical verification scenario, and the test execution steps are determined. The test type, the corresponding edited test topology, the test data to be monitored, the typical verification scenarios, and the test execution steps are pre-saved as typical implementation cases, which serve as the edited and generated test schemes.

3. The power quality management application verification method as described in claim 2, characterized in that, The parameter settings for the transparent platform and the verification scenario, according to the test plan, specifically include: Based on the platform network configuration of the test topology in the test plan, a real-type platform test topology network that meets the test requirements is constructed, and the corresponding treatment equipment to be tested is connected and initialized, thereby completing the parameter settings of the transparent transformer area real-type platform; Based on the source-load equipment and data acquisition equipment required for the test topology in the test plan, and the test data to be monitored, the parameters of the verification scenario are set in conjunction with the corresponding connected and initialized governance equipment under test; wherein, the governance equipment under test is connected to the grid and operated together with different power quality abnormal operation conditions.

4. The power quality management application verification method as described in claim 3, characterized in that, The experiment involves testing the IoT platform constructed from the smart gateway, smart switches, and smart sensing terminals in the transparent transformer area real-model platform after parameter settings, and monitoring the test data and acquiring terminal sensing data during the experiment. Specifically, this includes: The device under test, after parameter settings and initialization, is used as a smart sensing terminal. It is then connected to the corresponding smart switch, and a corresponding smart gateway is set for each connected smart switch, thereby building an Internet of Things platform. After constructing the IoT platform, power management tests of a transparent distribution area real-model platform are conducted based on the test plan and the simulation of different abnormal power quality operating conditions corresponding to the equipment under test; wherein, the power management test includes a power quality abnormal operating condition simulation stage and a management stage; Based on the intelligent sensing terminals and power quality analyzers in the IoT platform, test data is monitored during the test, thereby sensing and collecting the status of key equipment and key node parameters in real time, and then collecting them as terminal sensing data to the intelligent gateway; wherein, the terminal sensing data includes abnormal stage data, governance stage data, and post-governance data; The terminal sensing data collected at the smart gateway is forwarded directly or after edge computing to the IoT platform for data display and advanced application analysis.

5. The power quality management application verification method as described in claim 4, characterized in that, The process involves analyzing and evaluating the test results of the treatment equipment or treatment method under test based on the terminal sensing data through the IoT platform, and generating a test analysis report, specifically including: The actual scene is obtained by analyzing the collected terminal sensing data through the IoT platform. The actual scenario is compared with the verification scenario. When the actual scenario is consistent with the verification scenario, the abnormal stage data in the terminal perception data is analyzed to obtain the corresponding actual abnormal working condition and to determine the actual perception device. If the actual sensing device corresponds to the device under test, and the actual abnormal operating condition of the actual sensing device is the same as the abnormal power quality operating condition corresponding to the device under test, then the data of the treatment stage and the data after treatment in the terminal sensing data are analyzed, and the data of the treatment stage and the data after treatment are automatically analyzed according to the preset evaluation model, thereby automatically generating a test analysis report.

6. The power quality management application verification method as described in claim 5, characterized in that, The method for constructing the preset evaluation model includes: Obtain sample data corresponding to the treatment stage data and post-treatment data of the power treatment equipment under test, as well as the annotation data corresponding to the sample data; An initial preset evaluation model is constructed, and the sample data and the labeled data are used as training data for the initial preset evaluation model. The initial preset evaluation model is trained until the loss function of the initial preset evaluation model tends to fit, and then the final trained preset evaluation model is obtained.

7. A power quality management application verification method as described in any one of claims 1-6, characterized in that, The transparent distribution area real-world platform includes: key equipment for traditional distribution areas, new distribution area equipment, a power quality management area for connecting power quality management equipment through standardized interfaces, and an intelligent gateway for IoT networking of various smart switches and smart sensing terminals within the distribution area.

8. A power quality management application verification method as described in any one of claims 1-6, characterized in that, The verification scenarios for the power quality management function include: voltage quality management function verification scenario, three-phase imbalance management function verification scenario, harmonic management function verification scenario, and photovoltaic backfeeding management function verification scenario.

9. The power quality management application verification method as described in claim 8, characterized in that, The parameter settings for the voltage quality management function verification scenario specifically include: The power supply of the entire transparent transformer substation is carried out by combining isolation transformers and voltage regulators. The voltage of the transformer substation is controlled by setting the voltage regulator parameters, thereby generating and providing transformer substation voltage fluctuation and overvoltage operation scenarios. By adjusting the line impedance parameters through the line simulation device, different feeder lengths are simulated. Combined with the controllable simulated load in the platform, different combinations of feeder lengths and different loads are performed to reproduce the low voltage operation conditions at the end of the transformer area. Based on the Internet of Things in low-voltage power distribution, the voltage of the transformer area is acquired in real time as the initial voltage data for the transformer area voltage fluctuation test, and the changes in the transformer area voltage during the test are continuously monitored as test data for the voltage quality governance function verification scenario, thereby completing the setting of the voltage quality governance function verification scenario.

10. The power quality management application verification method as described in claim 9, characterized in that, The control of the transformer substation voltage by setting voltage regulator parameters specifically includes: By adjusting the voltage regulator, the contact position between the brush and the coil is changed, thereby altering the turns ratio of the primary and secondary coils, and thus regulating the output voltage to control the regional voltage.

11. The power quality management application verification method as described in claim 8, characterized in that, The parameter settings for the three-phase imbalance mitigation function verification scenario specifically include: Based on the aforementioned test scheme, the load imbalance of the transformer area is determined, and according to the load imbalance of the transformer area, a controllable simulated load with energy feedback is configured to set the three-phase power, thereby enabling the feeder of the transparent transformer area real-model platform to operate in an unbalanced state. By configuring an intelligent phase-switching switch, the imbalance state of the transparent transformer area real-model platform is managed. The intelligent phase-switching switch provides a standardized interface, thereby demonstrating the three-phase imbalance management while simultaneously connecting and functionally testing the device under test, thus completing the setup of the three-phase imbalance management function verification scenario.

12. The power quality management application verification method according to claim 8, characterized in that, The parameter settings for the harmonic mitigation function verification scenario specifically include: Based on the positive harmonic output of the energy-feedable controllable simulated load, harmonics are injected into the power grid in the transparent transformer substation platform through energy feedback, thereby enabling the transparent transformer substation platform to simulate a harmonic pollution scenario. The device under test is connected to the interface of the pre-reserved harmonic mitigation device in the transformer substation, and the changes in harmonics in the transformer substation are monitored in real time through the Internet of Things of the transformer substation power distribution, thereby completing the setting of the harmonic mitigation function verification scenario.

13. The power quality management application verification method according to claim 8, characterized in that, The parameter settings for the photovoltaic backfeeding control function verification scenario specifically include: Based on the aforementioned test plan, the characteristics of the photovoltaic modules to be simulated are determined, and the light intensity, temperature, and shadow parameters corresponding to the special effects of the photovoltaic modules are simulated by configuring programmable simulated photovoltaic cells. Based on the photovoltaic inverter with active and reactive power outputs corresponding to the test scheme, a photovoltaic simulation system is constructed in conjunction with the photovoltaic cells, and the photovoltaic output curve of the transparent transformer area real platform is set through the photovoltaic simulation system. By combining the preset load power curve within the distribution area, the simulation operation of the photovoltaic system in the distribution area can be realized from normal operation to photovoltaic reverse power scenario. During the simulation operation, the voltage, current and power generation data of the distribution area are acquired in real time by smart meters and smart sensors in the distribution area. This data serves as test data for the photovoltaic backfeeding control function verification scenario, thereby completing the setting of the photovoltaic backfeeding control function verification scenario.

14. A power quality management application verification device, characterized in that, The transparent transformer area simulation platform includes: a scheme editing module, a parameter setting module, a data monitoring module, and a result analysis module. The scheme editing module is used to edit and generate test schemes based on test requirements and in conjunction with the transparent transformer substation model platform; wherein, the test scheme includes: the treatment equipment to be tested or the treatment method to be evaluated, and the transparent transformer substation model platform is used to provide verification scenarios for several types of power quality treatment functions; The parameter setting module is used to set the parameters of the transparent platform and the verification scenario according to the test plan. The data monitoring module is used to test the Internet of Things platform constructed by the smart gateway, smart switches and smart sensing terminals in the transparent transformer area real-model platform after parameter settings, and to monitor the test data and obtain terminal sensing data during the test. The result analysis module is used to analyze and evaluate the test results of the treatment equipment or treatment method under test based on the terminal sensing data through the Internet of Things platform, and generate a test analysis report.

15. A terminal device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the power quality management application verification method as described in any one of claims 1 to 13.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the power quality management application verification method as described in any one of claims 1 to 13.

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