A test simulation device and method for power load simulation

Abstract

The application discloses a kind of electric power load simulation test simulation device and method, it is related to electric power test technical field, comprising: basic component library is constructed to electric power load type, wherein the basic component library includes mapped mathematical component library and load component library;Determine the load test demand of test electric power scene, based on digital controller, the basic component library is called to model and non-mechanism simplification, determine simulated electric power scene, wherein, with only pay attention to input-output as simplification standard;Uncertain simulation elements are introduced and simulation parameters are set as simulation conditions;Based on the simulation condition, the simulated electric power scene is simulated and tested to determine test data flow, including steady-state test and transient test.The application solves the technical problems of poor simulation accuracy in the prior art during electric power load simulation, and achieves the technical effects of improving the accuracy of simulated electric power scene and the comprehensiveness of simulation test.

Description

Technical Field

[0001] This invention relates to the field of power testing technology, specifically to a test simulation device and method for simulating power load. Background Technology

[0002] In traditional power load simulation, as the complexity of power systems increases, existing simulation methods often face several technical bottlenecks, particularly in terms of accuracy and comprehensiveness. Specifically, current power load simulation techniques mainly rely on empirical models and simplified assumptions. These methods cannot fully consider the dynamic changes in load and the varied power scenarios, leading to significant deviations between simulation results and actual operating conditions. Summary of the Invention

[0003] This invention provides a test simulation device and method for simulating power load, which solves the technical problem of poor simulation accuracy in existing power load simulation technologies.

[0004] In view of the above problems, the present invention provides a test simulation device and method for simulating power load.

[0005] A first aspect of the present invention provides a test simulation apparatus for simulating electrical loads, the apparatus comprising:

[0006] The system comprises the following modules: a basic component library construction module, which builds a basic component library for each power load type, including a mapped mathematical component library and a load component library; a load test requirement determination module, which determines the load test requirements for the power test scenario, and based on a digital controller, calls the basic component library for modeling and non-mechanistic simplification to determine the simulated power scenario, with input-output as the simplification standard; a simulation parameter setting module, which introduces uncertain simulation elements and sets simulation parameters as simulation conditions; and a simulation testing module, which performs simulation tests on the simulated power scenario based on the simulation conditions to determine the test data stream, including steady-state and transient tests.

[0007] Furthermore, the load testing requirement determination module includes:

[0008] The twin modeling module calls the basic component library to perform component invocation and twin modeling on the test power scenario to determine the initial power scenario;

[0009] The non-mechanism simplification module identifies load testing requirements, performs non-mechanism simplification on the initial power scenario, and determines the simulated power scenario.

[0010] Furthermore, the non-mechanistic simplification module includes:

[0011] The test subject determination module determines the test subject of the initial power scenario based on load test requirements;

[0012] The non-test subject division module divides the non-test subjects of the initial power scenario into a first non-test subject and a second non-test subject, with the division criterion being whether intermediate logic simulation is required.

[0013] A first simplification module simplifies the first non-test subject into an incomplete mechanistic component;

[0014] The second simplification module simplifies the second non-test subject into a non-mechanistic component, wherein the non-mechanistic component takes electrical load conditions as input and behavioral characteristics as output;

[0015] A simulated power scenario generation module, which reorganizes the test subject, the incomplete mechanism component, and the non-mechanism component based on the initial power scenario to generate a simulated power scenario.

[0016] Furthermore, the simulation parameter setting module includes:

[0017] The data retrieval module performs industrial big data retrieval for the test power scenario and calls up source scenario records that meet a preset similarity.

[0018] An influencing factor mining module is used to mine power influencing factors based on the same source scene records. The influencing factor mining standard is set at a preset frequency, and the power influencing factors are identified as having a linear influence relationship.

[0019] The uncertain simulation element determination module takes the power impact element as the uncertain simulation element, wherein the random simulation of the element under scenario constraints is used as the introduction standard.

[0020] Furthermore, the simulation parameter setting module includes:

[0021] The test section setting module sets up a steady-state test section and a transient test section based on the load test requirements, wherein the occurrence of a fault is used as the transient test condition.

[0022] A time test sequence determination module, which coordinates with the steady-state test part and the transient test part, and performs classification and time-division integration to determine the time test sequence;

[0023] A simulation parameter determination module determines simulation parameters based on the time test sequence.

[0024] Furthermore, the load testing requirement determination module includes:

[0025] A training sample acquisition module acquires training samples, wherein the training samples include mapped sample power scenarios and recombined samples based on the basic component library;

[0026] A digital controller construction module, which, based on the training samples, uses the basic component library as a resource pool and the calling logic and reorganization logic as training targets, supervises the training of the digital controller.

[0027] Furthermore, the simulation testing module includes:

[0028] An anomaly tracing information determination module identifies the test data stream, performs anomaly determination on the test subject, locates the anomaly time node, and traces the source based on the test data stream to determine the anomaly tracing information.

[0029] The load operation management module performs load operation management based on the anomaly tracing information.

[0030] A second aspect of the present invention provides a test simulation method for simulating electrical loads, the method comprising:

[0031] A basic component library is constructed for each power load type, comprising a mapped mathematical component library and a load component library. The load testing requirements for the power scenario are determined. Based on a digital controller, the basic component library is used for modeling and non-mechanistic simplification to determine the simulated power scenario, with input-output as the simplification standard. Uncertain simulation elements are introduced and simulation parameters are set as simulation conditions. Based on these simulation conditions, the simulated power scenario is simulated to determine the test data flow, including steady-state and transient tests.

[0032] One or more technical solutions provided by this invention have at least the following technical effects or advantages:

[0033] This invention solves the technical problem of poor simulation accuracy in existing power load simulation technologies. By constructing a basic component library including a mathematical component library and a load component library, and combining it with a digital controller to model and simplify the test power scenario, the invention uses an input-output simplification standard to determine the simulated power scenario, introduces uncertain simulation elements and sets simulation parameters as simulation conditions for simulation testing, covering steady-state and transient tests, and obtaining test data streams. This achieves the technical effect of improving the accuracy of simulated power scenarios and the comprehensiveness of simulation testing. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0035] Figure 1 A schematic diagram of a test simulation device for simulating power load provided in an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of a test simulation method for simulating power load, provided as an embodiment of the present invention.

[0037] Figure labeling: 11-Basic component library construction module, 12-Load test requirement determination module, 13-Simulation parameter setting module, 14-Simulation test module. Detailed Implementation

[0038] This invention provides a test simulation device and method for simulating power loads, addressing the technical problem of poor simulation accuracy in existing power load simulation technologies. It constructs a basic component library including a mathematical component library and a load component library, combines a digital controller to model and simplify the test power scenario using non-mechanistic methods, employs an input-output simplification standard to define the simulated power scenario, introduces uncertain simulation elements and sets simulation parameters as simulation conditions for simulation testing, covering both steady-state and transient tests, and obtaining test data streams. This achieves the technical effect of improving the accuracy of simulated power scenarios and the comprehensiveness of simulation testing.

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0040] It should be noted that any variation of the terms "comprising" and "having" is intended to cover non-exclusive inclusion, for example, a process, method, apparatus, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such process, method, product, or apparatus.

[0041] Example 1, as Figure 1 As shown, this embodiment of the invention provides a test simulation device for simulating power loads, the device comprising:

[0042] The basic component library construction module 11 constructs a basic component library for power load types, wherein the basic component library includes a mapped mathematical component library and a load component library.

[0043] In this embodiment of the invention, the task of the basic component library construction module is to construct a basic component library containing a mapping mathematical component library and a load component library according to different power load types.

[0044] Specifically, firstly, based on the different characteristics of electrical loads (such as resistive, inductive, capacitive, and nonlinear loads), a structured mathematical component library is formed by classifying and analyzing the mathematical models of the loads. This library includes mathematical expressions and logical control relationships of the operating mechanisms of electrical load equipment. These mathematical models describe the behavioral characteristics of the equipment under different electrical conditions, such as power transmission, phase control, and current-voltage relationships. These mathematical models are uploaded beforehand. The load component library contains specific physical model components that describe the electrical characteristics of different load types, such as the characteristics of resistive, inductive, capacitive, and nonlinear loads.

[0045] The load test requirement determination module 12 determines the load test requirements of the test power scenario. Based on the digital controller, it calls the basic component library to perform modeling and non-mechanistic simplification to determine the simulated power scenario, wherein the simplification standard is to focus only on input-output.

[0046] In this embodiment of the invention, the load test requirement determination module first calls various models from the basic component library through a pre-trained digital controller to perform component invocation and twin modeling, thereby determining the initial power scenario. Then, it identifies and analyzes the load test requirements to determine the load type and system characteristics to be tested. Next, it performs non-mechanistic simplification on the initial power scenario, focusing primarily on the relationship between inputs and outputs while ignoring some internal mechanisms to simplify calculations and improve simulation efficiency, ultimately determining a suitable simulated power scenario for testing.

[0047] Furthermore, in the apparatus provided in this embodiment of the invention, the load test requirement determination module 12 includes:

[0048] The training sample acquisition module acquires training samples, which include mapped sample power scenarios and call reassembly samples based on the basic component library; the digital controller construction module supervises the training of the digital controller based on the training samples, using the basic component library as a resource pool, and using call logic and reassembly logic as training targets.

[0049] In this embodiment of the invention, the training sample acquisition module is responsible for generating training samples, which include mapped sample power scenarios and recombined samples based on the basic component library. The mapped sample power scenarios are generated by simulating load types in a power system, using tools such as Matlab / Simulink to model the power system, and calculating electrical parameters such as current, voltage, and power under different load conditions (e.g., resistive, inductive, and capacitive loads). These simulation data accurately reflect the behavioral characteristics of loads under different environments. On the other hand, the recombined samples based on the basic component library combine existing models using a recombination algorithm to create diverse training datasets, ensuring the comprehensiveness and diversity of the simulation scenarios. This process generates new load test samples by randomly combining and recombining mathematical and physical models in the basic component library.

[0050] Next, the digital controller building module trains the digital controller using the obtained training samples. This process employs supervised learning methods, such as support vector machines, which, by inputting training samples, learn how the controller accurately calls upon models from the basic component library according to load requirements and performs reasonable reorganization. Specifically, the application of supervised learning methods involves providing each training sample with its input and corresponding expected output (i.e., simulation results), allowing the digital controller to learn the mapping relationship between input and output. During training, by minimizing the error between the output and the actual expected result, the controller's internal parameters are continuously adjusted, gradually optimizing its calling and reorganization logic.

[0051] Through the above process, the digital controller is finally trained.

[0052] Furthermore, in the apparatus provided in this embodiment of the invention, the load test requirement determination module 12 further includes:

[0053] The twin modeling module calls the basic component library to perform component invocation and twin modeling on the test power scenario to determine the initial power scenario; the non-mechanism simplification module identifies the load test requirements and performs non-mechanism simplification on the initial power scenario to determine the simulated power scenario.

[0054] In this embodiment of the invention, the twin modeling module invokes mathematical and physical models from a basic component library to perform component invocation and twin modeling of the test power scenario. This process involves abstracting the actual equipment and load characteristics of the power system into mathematical and physical models to simulate their operational behavior in a virtual manner. During this process, the twin modeling module establishes a preliminary simulation scenario based on given load type, operating conditions, and electrical parameters through component invocation. Specifically, the twin modeling module simulates the electrical behavior of power equipment (such as inverters, transformers, and power loads) under different operating states using a simulation platform (such as Matlab / Simulink), ultimately determining the initial power scenario, i.e., obtaining a preliminary model of the power system in a virtual environment.

[0055] Next, the non-mechanism simplification module simplifies the initial power scenario. Specifically, the non-mechanism simplification module first identifies the specific requirements of the power load test, clarifying the electrical parameters and system behavior that the simulation needs to focus on. Identifying load test requirements typically involves analyzing the test objectives (e.g., whether power fluctuations, instantaneous current changes, etc. are relevant), determining the outputs that need to be measured (e.g., current, voltage, power, etc.), and selecting the load type (resistive, inductive, capacitive, etc.). Once the load test requirements are clear, the non-mechanism simplification module performs non-mechanism simplification on the initial power scenario. The key to non-mechanism simplification is ignoring certain complex physical details or internal mechanisms (e.g., the precise working principle of equipment), focusing only on the relationship between the system's inputs and outputs, thereby reducing the computational complexity in the simulation model. This process simplifies parts of the system that do not affect the final test results, making the simulation more efficient and easier to implement, while ensuring that the simulation results still have high accuracy. For example, for the simulation of an inverter, non-mechanism simplification may not need to simulate the operation of the inverter's internal switching elements, but instead uses a simplified mathematical model to represent the relationship between its voltage and current, further reducing the computational burden. Ultimately, the simulation model, after being simplified from a non-mechanistic perspective, becomes the simulation of a power scenario.

[0056] Furthermore, in the device provided in this embodiment of the invention, the non-mechanism simplification module includes:

[0057] The system comprises the following modules: a test subject determination module, which determines the test subject of the initial power scenario based on load testing requirements; a non-test subject division module, which divides the non-test subject of the initial power scenario into a first non-test subject and a second non-test subject, with the division criterion being whether intermediate logic simulation is required; a first simplification module, which simplifies the first non-test subject into an incomplete mechanistic component; a second simplification module, which simplifies the second non-test subject into a non-mechanistic component, wherein the non-mechanistic component takes power load conditions as input and behavioral characteristics as output; and a simulated power scenario generation module, which reorganizes the test subject, the incomplete mechanistic component, and the non-mechanistic component based on the initial power scenario to generate a simulated power scenario.

[0058] In this embodiment of the invention, the test subject determination module first determines the core equipment or components to be tested, i.e., the test subject, based on the load testing requirements. This process is based on the analysis of the power system's operational requirements, identifying key equipment that needs to be focused on during testing. Typically, core components in the power system are analyzed using methods such as functional requirements analysis or failure mode and effect analysis (FMEA). The test subject is usually the equipment that directly affects the test results; for example, if the test objective is to evaluate the inverter's inverter state, the inverter is identified as the test subject. At this point, twin modeling technology is applied to virtual simulation, combining the inverter's physical model with its mathematical model to establish a digital simulation model for detailed analysis of the inverter's dynamic performance under different load conditions. The final result of this step is to determine the test subject in the initial power scenario, i.e., the inverter's behavior under specific conditions.

[0059] After identifying the test subjects, the non-test subjects in the initial power scenario are categorized using the non-test subject segmentation module. Non-test subjects refer to power system components that do not directly participate in load testing but may affect the behavior of the test subjects, such as power distribution lines and transformers. The non-test subject segmentation module further divides these components into first-level and second-level non-test subjects based on their roles in the simulation and their impact on the test subjects. The segmentation criterion is whether intermediate logic simulation is required for these non-test subjects. If the behavior of a non-test subject affects the dynamic response of the test subject but does not require complex simulation, it is classified as a first-level non-test subject; conversely, if the behavior of a non-test subject can be represented by simple behavioral characteristics and does not require complex intermediate logic simulation, it is classified as a second-level non-test subject.

[0060] Subsequently, the first and second simplification modules simplify the first and second non-test entities, respectively. The first non-test entity is simplified to an incomplete mechanistic component, retaining its basic physical characteristics but reducing detailed modeling to a lower-complexity model, thus improving computational efficiency. The second non-test entity is simplified to a non-mechanistic component, whose input is the electrical load condition and output is behavioral characteristics. In this way, the simplified non-test entity can still effectively reflect its impact on the test entity without needing to focus too much on its detailed operation.

[0061] Finally, the simulated power scenario generation module reorganizes the test subject, incomplete mechanistic components, and non-mechanistic components based on the initial power scenario, and generates the final simulated power scenario. In this process, all components, whether the test subject or the simplified non-test subject, are integrated into the simulation model to ensure that the test results accurately reflect the dynamic performance of the power system under different load conditions.

[0062] The simulation parameter setting module 13 introduces uncertain simulation elements and sets simulation parameters as simulation conditions.

[0063] In this embodiment of the invention, the simulation parameter setting module's task is to introduce uncertain simulation elements and set simulation parameters to ensure that the simulation process can reflect the uncertainties in the power system. Specifically, the simulation parameter setting module first retrieves historical data records similar to the test power scenario through industrial big data retrieval. These source scenario records have preset approximation standards and are used to provide a reference for the current simulation. Next, based on these records, power influencing factors are identified, and linear factors affecting the power system behavior are identified through preset frequency standards and introduced into the simulation as uncertain simulation elements. To simulate the changes in these elements, a stochastic simulation method under scenario constraints is used. Finally, according to the load test requirements, steady-state test and transient test parts are set, and these two parts are integrated collaboratively to generate the final simulation parameters, providing complete simulation conditions for the simulation test. The obtained simulation conditions include uncertain simulation elements and simulation parameters.

[0064] Furthermore, in the apparatus provided in this embodiment of the invention, the simulation parameter setting module 13 includes:

[0065] The system includes a data retrieval module, which performs industrial big data retrieval for the tested power scenario and retrieves source scenario records that meet a preset similarity. An influence element mining module mines power influence elements based on the source scenario records, using a preset frequency as the element mining standard, and identifying power influence elements with linear influence relationships. An uncertain simulation element determination module uses the power influence elements as uncertain simulation elements, using random element simulation under scenario constraints as the introduction standard.

[0066] In this embodiment of the invention, the data retrieval module is responsible for retrieving historical data similar to the current test power scenario from industrial big data. Specifically, the data retrieval module uses a similarity matching method. This method, based on known power scenario characteristics, calculates the similarity by comparing key parameters (such as power load, equipment status, environmental conditions, etc.) of the current test power scenario and historical records. In this way, the most relevant source scenario record is found from a large amount of historical data. Common algorithms such as cosine similarity or Euclidean distance are typically used to match historical scenarios and test scenarios. Finally, the data retrieval module returns source scenario records that meet a preset similarity threshold. This preset similarity threshold is pre-set by technical experts; meeting the preset similarity threshold means that the similarity calculated using cosine similarity or Euclidean distance is greater than the preset threshold.

[0067] Subsequently, the influencing factor mining module analyzes and mines key influencing factors in the power system based on the selected source scenario records. In this process, the module uses frequency analysis methods to mine factors according to preset frequencies, determining which power parameters significantly impact system performance. Specifically, through time series analysis of historical data, it identifies factors that significantly affect the power system at different time frequencies, such as load fluctuations and current variations. These power influencing factors typically exhibit a linear relationship, meaning they are linearly dependent on power system output parameters (such as voltage, current, and power); that is, when these factors change, the system output also changes accordingly. Through this process, the mining and identification of power influencing factors are completed.

[0068] Finally, the uncertainty simulation element determination module takes power impact factors as uncertain simulation elements, with random simulation of elements under scenario constraints as the introduction standard. Specifically, scenario constraints are used to constrain power impact factors to ensure that they conform to the physical characteristics and operating rules of the actual power system within a certain range. These scenario constraints are pre-set by technical experts. Then, uncertainty modeling is performed on these power impact factors based on random simulation methods. By randomly varying the elements under scenario constraints, the behavior of the power system under different conditions is simulated. The purpose of random simulation is to consider various possible power load changes by introducing uncertainty, thereby generating more realistic and comprehensive simulation data. Through this process, the introduction of uncertain simulation elements is completed.

[0069] These uncertain simulation elements, generated through random simulation, will serve as input conditions during the simulation process, helping to establish a more comprehensive power load test scenario. This ensures that the simulation can adapt to various power load fluctuations, thereby improving the accuracy and usability of the test results.

[0070] Furthermore, in the apparatus provided in this embodiment of the invention, the simulation parameter setting module 13 further includes:

[0071] The test section setting module sets up a steady-state test section and a transient test section based on the load test requirements, wherein the occurrence of a fault is used as the transient test condition; the time test sequence determination module coordinates the steady-state test section and the transient test section and performs classification and time-sharing integration to determine the time test sequence; the simulation parameter determination module determines simulation parameters based on the time test sequence.

[0072] In this embodiment of the invention, the test section setting module is used to set up steady-state test sections and transient test sections according to load test requirements. The steady-state test section refers to the testing of equipment or system under normal operating conditions, mainly used to verify the system's performance and reliability in a stable state. Steady-state testing is performed on loads under normal operating conditions, where the equipment operates continuously without faults or abnormalities. For example, for a power system, steady-state testing can be used to evaluate parameters such as equipment efficiency, temperature, power factor, and voltage stability under normal loads. These tests ensure the safety and reliability of the equipment in normal operating environments.

[0073] Transient testing, on the other hand, is conducted under conditions of equipment or system malfunction, disturbance, or sudden events. Faults such as short circuits, voltage surges, or load fluctuations can cause the system to enter a transient state, where the equipment experiences rapidly changing parameters such as voltage, current, and frequency. The purpose of testing under these conditions is to evaluate the equipment's recovery capability and stability in abnormal situations. For example, when a short circuit occurs in a power system, voltage and frequency change rapidly, and transient testing can verify the equipment's response to these sudden changes.

[0074] The time-based test sequence determination module combines the steady-state and transient testing components to form a complete testing process. In practical applications, steady-state and transient tests are not performed independently but alternately. The time-based test sequence determination module coordinates steady-state and transient tests, interleaving them according to a specific time sequence. That is, a steady-state test is performed first, followed by a simulated transient fault condition, and then a steady-state test is resumed. This alternating testing comprehensively reflects the equipment's performance under different operating conditions.

[0075] Finally, the simulation parameter determination module determines the specific simulation parameters based on the aforementioned time test sequence. This step requires formulating simulation parameters adapted to different test scenarios (steady-state or transient) according to the arrangement of the time test sequence. For the steady-state part, stable parameters such as current, voltage, and power factor need to be set; while for the transient part, parameters such as electrical response and rate of change when a fault occurs need to be set. The simulation parameters are set manually based on the specific test target, equipment characteristics, and load requirements. Through this process, the simulation parameters are determined.

[0076] The simulation test module 14 performs simulation tests on the simulated power scenario based on the simulation conditions to determine the test data stream, including steady-state tests and transient tests.

[0077] In this embodiment of the invention, the simulation testing module performs simulation tests on a simulated power scenario based on set simulation conditions, thereby obtaining a test data stream. The simulation conditions include uncertain simulation elements and simulation parameters. Uncertain simulation elements refer to random variations that may be introduced during both steady-state and transient testing phases, such as random fluctuations in equipment operation, environmental factors, and load fluctuations. Simulation parameters are specific values ​​determined based on a time-series test, including parameters such as voltage, current, and power, which define the input conditions at different testing phases.

[0078] During the simulation, simulation conditions are first loaded, and different simulation parameters are set for the steady-state and transient testing phases. In the steady-state testing phase, uncertain simulation elements remain to simulate uncertainties in the actual operation of the power system. For example, under normal load operation, the power system may experience small fluctuations due to factors such as equipment aging and load fluctuations, which can affect the stability of the power system. Therefore, these factors are included in the simulation to more realistically reflect the system's performance under normal operating conditions. In the transient testing phase, in addition to introducing uncertain simulation elements, extreme situations such as faults are simulated, which typically cause significant disturbances to the power system. For example, a short-circuit fault may cause a sudden voltage drop, current fluctuation, or even trigger equipment protection actions. By incorporating uncertain simulation elements, the dynamic response after these faults occur is simulated.

[0079] Throughout the simulation, the test is executed according to the set time sequence, and the test data stream is recorded and output in real time, including the changes in electrical characteristics such as voltage, current, and power at different test stages.

[0080] Furthermore, in the apparatus provided in this embodiment of the invention, the simulation testing module 14 includes:

[0081] An anomaly tracing information determination module identifies the test data stream, determines the abnormal status of the test subject, locates the abnormal time node, and traces the source based on the test data stream to determine the anomaly tracing information; a load operation management module performs load operation management based on the anomaly tracing information.

[0082] In this embodiment of the invention, the anomaly tracing information determination module first identifies anomalies present during the simulation process by continuously monitoring the test data stream. The test data stream includes various parameters (such as voltage, current, and power) for different test stages (such as steady-state or transient states) during the simulation test. These data reflect the operating state of the test subject (such as an inverter). Real-time analysis of this data, along with pre-set thresholds and predefined rules, determines which test data exceeds the normal operating range, thereby identifying abnormal events.

[0083] Once an anomaly is identified, time-point identification technology is used to pinpoint the exact time of its occurrence. Specifically, by analyzing the time series of anomaly data points, the exact moment of the anomaly event is determined. For example, in steady-state testing, if voltage fluctuations are excessive, this time point is marked as the moment the anomaly occurred; in transient testing, if test data changes abruptly, the specific time of the event is quickly captured and recorded.

[0084] Next, based on the source tracing analysis method, the identified abnormal time points are traced to find the root cause of the anomaly. This is done by comparing test data with preset operating parameters to find potential factors that could cause the anomaly. For example, if an inverter malfunctions, tracing the data stream can help determine if the anomaly is caused by abnormal battery status, sudden load changes, or external grid fluctuations. Through causal analysis, the problem is identified, and detailed anomaly source information is generated.

[0085] Finally, based on the obtained anomaly tracing information, the load operation management module is activated. The main task of this module is to adjust or intervene in the relevant load operation using the causes of the anomalies identified through the tracing analysis. For example, if the tracing analysis shows that poor battery condition is causing inverter malfunctions, the battery load is adjusted, or staff are notified to make adjustments.

[0086] In the embodiments of the present invention, as summarized above, the embodiments of the present invention have at least the following technical effects:

[0087] This invention constructs a basic component library for power load types, comprising a mapped mathematical component library and a load component library. It determines the load testing requirements of a test power scenario, and based on a digital controller, uses the basic component library for modeling and non-mechanistic simplification to determine the simulated power scenario, with input-output simplification as the simplification standard. Uncertain simulation elements are introduced and simulation parameters are set as simulation conditions. Based on these simulation conditions, the simulated power scenario is simulated to determine the test data stream, including steady-state and transient tests. This invention addresses the technical problem of poor simulation accuracy in existing power load simulation technologies. By constructing a basic component library containing mathematical and load component libraries, combining it with a digital controller for modeling and non-mechanistic simplification of the test power scenario, using an input-output simplification standard to determine the simulated power scenario, introducing uncertain simulation elements and setting simulation parameters as simulation conditions for simulation testing, and obtaining the test data stream, it achieves the technical effect of improving the accuracy of simulated power scenarios and the comprehensiveness of simulation testing.

[0088] Example 2, based on the same inventive concept as the power load simulation test device in the foregoing examples, such as... Figure 2 As shown in the figure, an embodiment of the present invention provides a test simulation method for simulating power load, the method comprising:

[0089] A basic component library is constructed for each power load type, comprising a mapped mathematical component library and a load component library. The load testing requirements for the power scenario are determined. Based on a digital controller, the basic component library is used for modeling and non-mechanistic simplification to determine the simulated power scenario, with input-output as the simplification standard. Uncertain simulation elements are introduced and simulation parameters are set as simulation conditions. Based on these simulation conditions, the simulated power scenario is simulated to determine the test data flow, including steady-state and transient tests.

[0090] Furthermore, the basic component library is invoked for modeling and non-mechanistic simplification to determine the simulated power scenario, specifically including:

[0091] The basic component library is invoked to perform component invocation and twin modeling of the test power scenario to determine the initial power scenario; load test requirements are identified, and the initial power scenario is simplified non-mechanically to determine the simulated power scenario.

[0092] Furthermore, the initial power scenario is simplified non-mechanistically, specifically including:

[0093] Based on load testing requirements, the test subject of the initial power scenario is determined; for the non-test subjects of the initial power scenario, a first non-test subject and a second non-test subject are divided, with the division criterion being whether intermediate logic simulation is required; the first non-test subject is simplified into an incomplete mechanism component; the second non-test subject is simplified into a non-mechanism component, wherein the non-mechanism component takes power load conditions as input and behavioral characteristics as output; based on the initial power scenario, the test subject, the incomplete mechanism component, and the non-mechanism component are reorganized to generate a simulated power scenario.

[0094] Furthermore, the introduction of uncertain simulation elements specifically includes:

[0095] For the test power scenario, industrial big data retrieval is performed to call up source scenario records that meet the preset approximation; based on the source scenario records, power influencing factors are mined, wherein the factor mining standard is based on a preset frequency, and the power influencing factors are identified as having a linear influence relationship; the power influencing factors are used as uncertain simulation factors, wherein the random simulation of factors under scenario constraints is used as the introduction standard.

[0096] Furthermore, the setting of simulation parameters specifically includes:

[0097] Based on the load testing requirements, a steady-state test section and a transient test section are set up, wherein the occurrence of a fault is used as the transient test condition; the steady-state test section and the transient test section are coordinated and classified and integrated in a time-sharing manner to determine the time test sequence; based on the time test sequence, simulation parameters are determined.

[0098] Furthermore, a digital controller is constructed, specifically including:

[0099] Acquire training samples, wherein the training samples include mapped sample power scenarios and call reorganization samples based on the basic component library; based on the training samples, using the basic component library as a resource pool and the call logic and reorganization logic as training targets, supervise the training of the digital controller.

[0100] Furthermore, after determining the test data stream, the method further includes:

[0101] Identify the test data stream, determine the abnormal status of the test subject, locate the abnormal time node, trace the source based on the test data stream, and determine the abnormal source information; perform load operation management based on the abnormal source information.

[0102] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0103] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0104] This specification and accompanying drawings are merely illustrative examples of the invention and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its scope. Therefore, if such modifications and modifications fall within the scope of the invention and its equivalents, the invention is intended to include these modifications and modifications.

Claims

1. A test simulation apparatus for electrical load simulation, characterized by, The utility model relates to a load test method and device, including: The basic component library construction module constructs the basic component library for the power load type, wherein the basic component library contains the mapped mathematical component library and the load component library; The load test demand determination module determines the load test demand of the test power scene, calls the basic component library for modeling and non-mechanism simplification based on the digital controller, determines the simulation power scene, wherein the non-mechanism simplification refers to the simplification method with only input-output as the simplification standard; The simulation parameter setting module introduces the uncertain simulation element and sets the simulation parameter as the simulation condition, and the uncertain simulation element refers to the element introduced by random simulation based on the power influence element under the scene constraint; The simulation test module carries out simulation test on the simulation power scene based on the simulation condition and determines the test data flow, which includes steady-state test and transient test.

2. A test simulation apparatus for power load simulation as claimed in claim 1, wherein, The load test demand determination module includes: The twin modeling module calls the basic component library, calls the component and carries out twin modeling on the test power scene, and determines the initial power scene; The non-mechanism simplification module identifies the load test demand, simplifies the initial power scene in a non-mechanism manner, and determines the simulation power scene.

3. A test simulation apparatus for power load simulation as claimed in claim 2, wherein, The non-mechanism simplification module includes: The test subject determination module determines the test subject of the initial power scene based on the load test demand; The non-test subject division module divides the first non-test subject and the second non-test subject for the non-test subject of the initial power scene, wherein the division standard is whether intermediate logic simulation is needed; The first simplification module simplifies the first non-test subject into an incomplete mechanism component, and the incomplete mechanism component refers to a model that retains basic physical properties but reduces detailed modeling; The second simplification module simplifies the second non-test subject into a non-mechanism component, wherein the non-mechanism component takes power load conditions as input and behavior characteristics as output; The simulation power scene generation module generates the simulation power scene according to the initial power scene, reorganizes the test subject, the incomplete mechanism component and the non-mechanism component, and generates the simulation power scene.

4. The test simulation apparatus for power load simulation of claim 1, wherein The simulation parameter setting module includes: The data retrieval module carries out industrial big data retrieval for the test power scene, calls the homologous scene record meeting the preset approximation degree; The influence element mining module mines the power influence element based on the homologous scene record, wherein the element mining standard is preset frequency, and the power influence element is identified with linear influence relationship; The uncertain simulation element determination module takes the power influence element as the uncertain simulation element, wherein the introduction standard is random simulation of the element under the scene constraint.

5. The test simulation apparatus for power load simulation of claim 1, wherein The simulation parameter setting module comprises: The test part setting module sets a steady-state test part and a transient-state test part based on the load test requirement, wherein the fault occurrence is taken as the transient-state test condition; The time test sequence determination module determines a time test sequence by integrating the steady-state test part and the transient-state test part in a classified and time-sharing manner; The simulation parameter determination module determines simulation parameters based on the time test sequence.

6. A test simulation apparatus for power load simulation as recited in claim 1, wherein The load test requirement determination module comprises: The training sample acquisition module acquires training samples, wherein the training samples comprise mapped sample power scenarios and recombined samples based on the basic component library; The digital controller construction module supervises the training of a digital controller based on the training samples, takes the basic component library as a resource pool, and takes the calling logic and the recombination logic as training targets.

7. A test simulation apparatus for power load simulation as recited in claim 3, wherein The simulation test module comprises: The abnormality trace information determination module identifies test data flow, determines state abnormality of the test subject, locates an abnormal time node, traces based on the test data flow, and determines abnormality trace information; The load operation management module manages the load operation based on the abnormality trace information.

8. A test simulation method of power load simulation, characterized by, The method is executed by the test simulation device for simulating the power load according to any one of claims 1 to 7, and comprises: A basic component library is constructed for the power load type, wherein the basic component library comprises a mapped mathematical component library and a load component library; Load test requirements of a test power scenario are determined, a digital controller is called, the basic component library is modeled and non-mechanical simplified, and a simulated power scenario is determined, wherein the input-output is only focused on as a simplified standard; Uncertain simulation elements are introduced and simulation parameters are set as simulation conditions; Based on the simulation conditions, the simulated power scenario is simulated and test data flow is determined, wherein the test comprises steady-state test and transient-state test.

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