Test simulation device and method for power load simulation

Abstract

The invention discloses a test simulation device and method for power load simulation, and relates to the technical field of power testing, and the method comprises the steps: building a basic component library for the type of a power load, and enabling the basic component library to comprise a mapped mathematical component library and a load component library; load test requirements of a test power scene are determined, the basic component library is called to perform modeling and non-mechanism simplification based on a digital controller, a simulation power scene is determined, and only input-output is concerned as a simplification standard; uncertain simulation elements are introduced, and simulation parameters are set as simulation conditions; and based on the simulation condition, performing a simulation test on the simulated power scene, and determining a test data stream, including a steady state test and a transient state test. According to the invention, the technical problem of poor simulation accuracy in power load simulation in the prior art is solved, and the technical effects of improving the accuracy of the simulation power scene and the comprehensiveness of the simulation test are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power testing, in particular to a test simulation device and method for power load simulation. BACKGROUND

[0002] In traditional power load simulation, as the complexity of power systems increases, existing simulation methods often face several technical bottlenecks, especially in terms of accuracy and comprehensiveness of simulation. Specifically, current power load simulation techniques mainly rely on empirical models and simplified assumptions, which cannot fully consider the dynamic changes of loads and variable power scenarios, resulting in a large deviation between simulation results and actual operating conditions. SUMMARY

[0003] The present application provides a test simulation device and method for power load simulation, which solves the technical problem of poor simulation accuracy in the prior art during power load simulation.

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

[0005] In a first aspect of the present application, a test simulation device for power load simulation is provided, which comprises: a basic component library construction module, which constructs a basic component library for power load types, wherein the basic component library contains a mapped mathematical component library and a load component library; a load test requirement determination module, which determines the load test requirements of the test power scenario, calls the basic component library for modeling and non-mechanism simplification based on a digital controller, and determines the simulated power scenario, wherein the simplification standard is only to focus on input-output; a simulation parameter setting module, which introduces uncertain simulation elements and sets simulation parameters as simulation conditions; a simulation test module, which performs simulation test on the simulated power scenario based on the simulation conditions to determine test data flow, including steady-state test and transient test.

[0006] Further, the load test requirement determination module comprises: a twin modeling module, which calls the basic component library to perform component calling and twin modeling on the test power scenario to determine the initial power scenario; a non-mechanism simplification module, which identifies the load test requirements, performs non-mechanism simplification on the initial power scenario, and determines the simulated power scenario.

[0007] Further, the non-mechanism simplification module comprises: A test subject determination module determines a test subject of the initial power scenario based on a load test requirement; A non-test subject division module divides a first non-test subject and a second non-test subject for a non-test subject of the initial power scenario, wherein a division criterion is whether intermediate logic simulation is needed; A first simplification module simplifies the first non-test subject into an incomplete mechanism component; A second simplification module simplifies the second non-test subject into a non-mechanism component, wherein the non-mechanism component takes a power load condition as an input and takes a behavior characteristic as an output; A simulated power scenario generation module generates a simulated power scenario by reorganizing the test subject, the incomplete mechanism component, and the non-mechanism component according to the initial power scenario.

[0008] Further, the simulation parameter setting module comprises: A data retrieval module performs industrial big data retrieval for the test power scenario, and calls a homologous scenario record meeting a preset approximation degree; An influence factor mining module mines a power influence factor based on the homologous scenario record, wherein a factor mining criterion is a preset frequency, and the power influence factor is identified with a linear influence relationship; An uncertain simulation factor determination module takes the power influence factor as an uncertain simulation factor, wherein a factor random simulation under a scenario constraint is an introduction criterion.

[0009] Further, the simulation parameter setting module comprises: A test part setting module sets a steady-state test part and a transient-state test part based on the load test requirement, wherein a fault occurrence is a transient-state test condition; A 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 time-sharing manner; A simulation parameter determination module determines a simulation parameter based on the time test sequence.

[0010] Further, the load test requirement determination module comprises: A training sample acquisition module acquires a training sample, wherein the training sample comprises a mapped sample power scenario and a call reorganization sample based on the basic component library. A digital controller construction module, which is based on the training sample, uses the basic component library as a resource pool, uses calling logic and reorganization logic as training targets, and supervises the training of the digital controller.

[0011] Further, the simulation test module comprises: An abnormality trace information determination module, which identifies test data flow, performs state abnormality determination on the test subject, locates an abnormality time node, traces based on the test data flow, and determines abnormality trace information. A load operation management module, which performs load operation management based on the abnormality trace information.

[0012] In a second aspect of the present application, a test simulation method for power load simulation is provided, which comprises: A basic component library is constructed for power load types, wherein the basic component library comprises a mapped mathematical component library and a load component library; load test requirements of a test power scene are determined; based on a digital controller, the basic component library is called to perform modeling and non-mechanism simplification, and a simulated power scene is determined, wherein the simplification standard is only input-output; uncertain simulation elements are introduced and simulation parameters are set as simulation conditions; based on the simulation conditions, the simulated power scene is simulated to determine test data flow, which includes steady-state test and transient-state test.

[0013] The one or more technical solutions provided by the present application have at least the following technical effects or advantages: The present application solves the technical problem of poor simulation accuracy of existing power load simulation, by constructing a basic component library comprising a mathematical component library and a load component library, combining a digital controller to model and non-mechanically simplify a test power scene, using an input-output simplification standard to determine a simulated power scene, introducing uncertain simulation elements and setting simulation parameters as simulation conditions for simulation testing, covering steady-state and transient-state testing to obtain test data flow, thereby achieving the technical effects of improving the accuracy of simulated power scenes and the comprehensiveness of simulation testing. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0015] Figure 1A schematic diagram of a test simulation device for simulating power load provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a test simulation method for simulating power load, provided as an embodiment of the present invention.

[0016] 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

[0017] 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.

[0018] 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.

[0019] 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.

[0020] Example 1, as Figure 1 As shown, this embodiment of the invention provides a test simulation device for simulating power loads, the device comprising: 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.

[0021] 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.

[0022] Specifically, first, for different characteristics of power loads (such as resistive, inductive, capacitive and nonlinear loads, etc.), by classifying and analyzing the mathematical models of the loads, a structured mathematical component library is formed. The mathematical component library includes mathematical expressions and logical control relationships of the operating mechanism of power load equipment. These mathematical models are used to describe the behavior characteristics of the equipment under different electrical conditions, such as power transmission, phase control, and current-voltage relationship, etc. These mathematical models are uploaded in advance. The load component library contains specific physical model components, which describe the electrical characteristics of different load types, such as the characteristics of resistive, inductive, capacitive and nonlinear loads.

[0023] The load test requirement determination module 12 determines the load test requirement of the test power scenario, calls the basic component library for modeling and non-mechanism simplification based on the digital controller, and determines the simulated power scenario, wherein the input-output is only concerned as the simplification standard.

[0024] In the embodiment of the present application, the load test requirement determination module first calls various models in the basic component library through the pre-trained digital controller, performs component calling and twin modeling, and thus determines the initial power scenario. Then, the load test requirement is identified and analyzed to determine the load type and system characteristics that need to be tested. Then, the initial power scenario is non-mechanically simplified, mainly focusing on the relationship between input and output, and ignoring some internal mechanisms to simplify the calculation and improve the simulation efficiency, and finally determining the simulated power scenario suitable for testing.

[0025] Further, in the apparatus provided by the embodiment of the present application, the load test requirement determination module 12 comprises: A training sample acquisition module, which acquires training samples, wherein the training samples include mapped sample power scenarios and reorganized samples based on calling of the basic component library; a digital controller construction module, which, based on the training samples, takes the basic component library as a resource pool, takes calling logic and reorganization logic as training targets, and supervises training of the digital controller.

[0026] In the embodiments of the present application, the training sample acquisition module is responsible for generating training samples, which include mapped sample power scenarios and call reorganization samples based on the basic component library. The mapped sample power scenarios are generated by simulating the load types in the power system, modeling the power system using tools such as Matlab / Simulink, calculating electrical parameters such as current, voltage, and power under different load conditions (such as resistive, inductive, and capacitive loads), and then generating power scenario samples. These simulation data can accurately reflect the behavior characteristics of the load under different environments. On the other hand, the call reorganization samples based on the basic component library are created by combining existing models using reorganization algorithms, creating a diverse training dataset, and ensuring the comprehensiveness and diversity of the simulation scenarios. This process generates new load test samples by randomly combining and reorganizing mathematical and physical models in the basic component library.

[0027] Next, the digital controller construction module trains the digital controller using the obtained training samples. This process uses a supervised learning method, such as a support vector machine, to learn how the controller accurately calls models in the basic component library and performs reasonable reorganization based on load requirements by inputting training samples. Specifically, the application of the supervised learning method is to give the input and the corresponding expected output (i.e., simulation results) of each training sample, so that the digital controller learns the mapping relationship between the input and the output. During the training process, the internal parameters of the controller are continuously adjusted to gradually optimize its call logic and reorganization logic by minimizing the error between the output and the actual expected result.

[0028] Through the above process, the digital controller is finally trained.

[0029] Further, the device provided by the embodiments of the present application further comprises: a twin modeling module, which calls the basic component library to perform component calling and twin modeling on the test power scenario to determine an initial power scenario; and a non-mechanism simplification module, which identifies the load test requirement, performs non-mechanism simplification on the initial power scenario, and determines a simulation power scenario.

[0030] In embodiments of the present application, the twin modeling module calls mathematical and physical models in the basic component library to perform component calling and twin modeling for the test power scenario. This process simulates the operation behavior of the actual equipment and load characteristics of the power system in a virtual manner by abstracting them into mathematical and physical models. In this process, the twin modeling module establishes a preliminary simulation scenario by component calling according to the given load type, working condition and electrical parameters. Specifically, the twin modeling module simulates the electrical behavior of power equipment (such as inverters, transformers, power loads, etc.) in different working conditions through a simulation platform (such as Matlab / Simulink) to ultimately determine the initial power scenario, i.e., obtain a preliminary model of the power system in a virtual environment.

[0031] Next, the initial power scenario is simplified by the non-mechanism simplification module. Specifically, the non-mechanism simplification module first identifies the specific requirements of the power load test and determines the electrical parameters and system behavior that need to be focused on for simulation. The process of identifying load test requirements usually includes analyzing test objectives (e.g., whether to focus on power fluctuations, instantaneous current changes, etc.), determining the outputs to be measured (such as 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 to ignore certain complex physical details or internal mechanisms (such as the precise working principle of the equipment) and only focus on the relationship between the input and output of the system, thereby reducing the computational complexity of the simulation model. This process makes the simulation more efficient and easier to implement by simplifying parts of the system that do not affect the final test results, 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 switching element action inside the inverter, but can represent the relationship between its voltage and current through a simplified mathematical model, further reducing the computational burden. Finally, the simulation model after non-mechanism simplification becomes the simulated power scenario.

[0032] Further, in the apparatus provided by embodiments of the present application, the non-mechanism simplification module includes: a test subject determination module configured to determine a test subject of the initial power scenario based on the load test requirement; a non-test subject division module configured to divide, for a non-test subject of the initial power scenario, a first non-test subject and a second non-test subject, wherein a division criterion is whether intermediate logic simulation is needed; a first simplification module configured to simplify the first non-test subject into an incomplete mechanism component; a second simplification module configured to simplify the second non-test subject into a non-mechanism component, wherein the non-mechanism component takes a power load condition as an input and takes a behavior characteristic as an output; and a simulated power scenario generation module configured to generate a simulated power scenario by reorganizing the test subject, the incomplete mechanism component, and the non-mechanism component according to the initial power scenario.

[0033] In the embodiment of the present application, the test subject determination module first determines the core equipment or component that needs to be tested according to the load test requirement, that is, the test subject. This process is based on the analysis of the operation requirement of the power system to identify the key equipment that needs to be focused on in the test. Generally, the core component in the power system is analyzed by methods such as functional requirement analysis or failure mode and effects analysis (FMEA). The test subject is usually the equipment that directly affects the test result, for example, if the test target is to evaluate the inverter state of the inverter, the inverter is determined as the test subject. At this time, the twin modeling technology is applied to virtual simulation, and a digital simulation model is established by combining the physical model of the inverter with its mathematical model, so as to analyze the dynamic performance of the inverter under different load conditions in detail. The final result of this step is to determine the test subject in the initial power scenario, that is, the behavior of the inverter under certain conditions.

[0034] After the test subject is determined, the non-test subject division module is used to classify the non-test subject in the initial power scenario. The non-test subject refers to the power system components that do not directly participate in the load test but may affect the behavior of the test subject, such as power distribution lines, transformers, etc. The non-test subject division module further divides the non-test subject into a first non-test subject and a second non-test subject according to the role of these components in simulation and their influence on the test subject. The division criterion is whether intermediate logic simulation is needed. If the behavior of the non-test subject affects the dynamic response of the test subject but does not need complex simulation, it is divided into the first non-test subject; if the behavior of the non-test subject can be represented by simple behavior characteristics and does not need complex intermediate logic simulation, it is divided into the second non-test subject.

[0035] Subsequently, the first and second simplification modules simplify the first and second non-test subjects, respectively. The first non-test subject is simplified into an incomplete mechanism component, which retains its basic physical characteristics but reduces detailed modeling, simplifying it into a lower complexity model to improve computational efficiency. The second non-test subject is simplified into a non-mechanism component, whose input is the power load condition and whose output is the behavior characteristics. In this way, the simplified non-test subject can still effectively reflect its impact on the test subject without paying too much attention to its detailed operation.

[0036] Finally, the simulated power scenario generation module reorganizes the test subject, incomplete mechanism component, and non-mechanism component based on the initial power scenario and generates the final simulated power scenario. In this process, all components, whether test subjects or simplified non-test subjects, 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.

[0037] The simulation parameter setting module 13 introduces uncertain simulation elements and sets simulation parameters as simulation conditions.

[0038] In the embodiments of the present application, the task of the simulation parameter setting module is to introduce uncertain simulation elements and set simulation parameters to ensure that the simulation process can reflect the uncertainty in the power system. Specifically, the simulation parameter setting module first retrieves similar historical data records to the test power scenario through industrial big data, and these homologous scenario records have a pre-set approximation standard for providing a reference for the current simulation. Then based on these records, the power impact elements are mined, the linear factors that affect the behavior of the power system are identified through a pre-set frequency standard, and they are introduced as uncertain simulation elements into the simulation. To simulate the changes of these elements, the random simulation method under the scene constraint is used for processing. Finally, according to the load test requirements, the steady-state test part and the transient test part are set, and the two parts are integrated 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.

[0039] Further, the device provided by the embodiments of the present application includes: a data retrieval module configured to retrieve, for the test power scenario, an industrial big data, and call a homologous scenario record satisfying a preset approximation degree; an influence factor mining module configured to mine, based on the homologous scenario record, a power influence factor, wherein a factor mining standard is performed at a preset frequency, and the power influence factor is identified to have a linear influence relationship; and an uncertain simulation factor determination module configured to take the power influence factor as an uncertain simulation factor, wherein a factor random simulation under a scenario constraint is taken as an introduction standard.

[0040] In the embodiment of the present application, 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 based on known power scenario characteristics. By comparing the key parameters (such as power load, device status, environmental conditions, etc.) of the current test power scenario and the historical records, the similarity is calculated. In this way, the most suitable homologous scenario record for the current test scenario is found from a large amount of historical data, and common algorithms such as cosine similarity or Euclidean distance are usually used to match the historical scenario and the test scenario. Finally, the data retrieval module returns the homologous scenario record that satisfies the preset approximation degree. The preset approximation degree is set by a technical expert in advance, and the similarity calculated by the cosine similarity or Euclidean distance is greater than the preset approximation degree.

[0041] Subsequently, the influence factor mining module analyzes and mines the key influence factors in the power system based on the selected homologous scenario record. In this process, the influence factor mining module uses frequency analysis method to determine which power parameters have an important influence on the system performance by performing factor mining according to the preset frequency. Specifically, by analyzing the time series of historical data, factors that have a significant impact on the power system at different time frequencies are identified, such as load fluctuations, current changes, etc. These power influence factors usually exhibit linear influence relationships, i.e., they have linear dependence on power system output parameters (such as voltage, current, power, etc.), i.e., when these factors change, the system output will also change accordingly. Through this process, the mining of power influence factors is completed, and the power influence factors are determined.

[0042] Finally, the uncertain simulation element determination module determines the power impact elements as uncertain simulation elements, with the introduction of the element random simulation under the scenario constraint as the standard. Specifically, the power impact elements are constrained by the scenario constraint condition to ensure that they are within a certain range and meet the physical characteristics and working rules of the actual power system. The scenario constraint condition is set by technical experts in advance. Then, based on the random simulation method, the uncertainty of these power impact elements is modeled. By randomly changing the elements under the scenario constraint condition, 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 extensive simulation data. Through this process, the introduction of uncertain simulation elements is completed.

[0043] The uncertain simulation elements generated by random simulation will be used as input conditions in the simulation process to help establish more comprehensive power load test scenarios and ensure that the simulation can adapt to various different power load fluctuations, thereby improving the accuracy and usability of the test results.

[0044] Further, the device provided by the embodiment of the present application further comprises: a test part setting module, which sets a steady-state test part and a transient-state test part based on the load test requirement, wherein the transient-state test condition is fault occurrence; a time test sequence determination module, which 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; and a simulation parameter determination module, which determines simulation parameters based on the time test sequence.

[0045] In the embodiment of the present application, the test part setting module is used to set a steady-state test part and a transient-state test part according to the load test requirement. The steady-state test part refers to the test of a device or system under normal operating conditions, which is mainly used to verify the performance and reliability of the system under stable state. The steady-state test is performed on the load under normal working conditions, and the device continuously operates without faults or abnormal conditions. For example, for a power system, the efficiency, temperature, power factor, voltage stability and other parameters of the device under conventional load can be evaluated through the steady-state test, which ensures the safety and reliability of the device in the normal working environment.

[0046] The transient test part is a test conducted in the presence of faults, disturbances or contingencies in the device or system. Faults such as short circuits, voltage surges or load fluctuations can cause the system to enter a transient state, and the device will experience rapidly changing voltage, current, frequency and other parameters. The purpose of testing in this state is to evaluate the recovery ability and stability of the device in abnormal conditions. For example, when a short circuit occurs in the power system, the voltage and frequency will change rapidly, and transient testing can verify the response capability of the device to these sudden changes.

[0047] The function of the time test sequence determination module is to combine the steady-state test part and the transient test part to form a complete test process. In actual application, steady-state testing and transient testing are not independent, but are alternately performed. The time test sequence determination module cooperates with steady-state testing and transient testing to perform interleaving according to a certain time sequence. That is, a steady-state test is first performed, then a transient fault condition is simulated, and then the steady-state test is restored. This alternating test can comprehensively reflect the performance of the device under different working conditions.

[0048] Finally, the simulation parameter determination module determines the specific simulation parameters based on the above time test sequence. This step needs to develop simulation parameters suitable for different test scenarios (steady state or transient state) according to the arrangement of the time test sequence. The steady-state part needs to set stable current, voltage, power factor and other parameters; while the transient part needs to set electrical response, change rate and other parameters when the fault occurs. The setting of simulation parameters is based on the specific test target, device characteristics and load demand, and is inputted manually. Through this process, the simulation parameters are determined.

[0049] The simulation test module 14 performs simulation testing on the simulated power scene based on the simulation conditions to determine the test data stream, which includes steady-state testing and transient testing.

[0050] In the embodiment of the present application, the simulation test module performs simulation testing on the simulated power scene based on the set simulation conditions, thereby obtaining the test data stream. The simulation conditions include uncertain simulation elements and simulation parameters. The uncertain simulation elements refer to random change factors that can be introduced in both steady-state and transient-state testing stages, such as random fluctuations in device operation, environmental factors, load fluctuations, etc. The simulation parameters are specific numerical values determined based on the time test sequence, including voltage, current, power and other parameters, which define the input conditions in different test stages.

[0051] In the simulation process, firstly, the simulation conditions are loaded, and different simulation parameters in the steady-state and transient-state test stages are set. In the steady-state test stage, uncertain simulation elements still exist, which are used to simulate uncertain factors in the actual power system operation. For example, in the case of normal load operation, the power system may produce small fluctuations due to factors such as equipment aging and load fluctuation, which will affect the stability of the power system. Therefore, these factors are added in the simulation test to more truly reflect the performance of the system under normal operation. In the transient-state test stage, in addition to introducing uncertain simulation elements, extreme conditions such as faults are also simulated, which will usually cause great disturbance to the power system. For example, a short-circuit fault may cause voltage to drop, current to fluctuate, and even cause equipment protection action. By adding uncertain simulation elements, the dynamic response after the occurrence of these faults is simulated.

[0052] In the entire simulation process, the test data stream is recorded and output in real time according to the set time test sequence, including the changes of voltage, current, power and other electrical characteristics in different test stages.

[0053] Further, the device provided by the embodiment of the present application comprises: an abnormality trace information determination module, which identifies test data stream, performs state abnormality determination on the test subject, locates an abnormal time node and performs trace based on the test data stream, and determines abnormality trace information; and a load operation management module, which performs load operation management based on the abnormality trace information.

[0054] In the embodiment of the present application, in the abnormality trace information determination module, firstly, the abnormality existing in the simulation process is identified through continuous monitoring of the test data stream. The test data stream includes various parameters (such as voltage, current, power, etc.) for different test stages (such as steady-state or transient-state) in the simulation test process. These data reflect the working state of the test subject (such as an inverter, etc.). The data are analyzed in real time, and it is judged which test data exceeds the normal working range through the pre-set threshold and pre-defined rules, and then the abnormal event is identified.

[0055] Once the abnormality is identified, the time node identification technology is used to locate the time node of the abnormality occurrence. Specifically, the occurrence time of the abnormal event is determined by analyzing the time sequence of the abnormal data points. For example, in the steady-state test, if the voltage fluctuation is too large, the time point is marked as the abnormal occurrence time; in the transient-state test stage, if the test data suddenly changes, the specific time of the event will also be quickly captured and recorded.

[0056] Next, based on the traceability analysis method, the abnormal time nodes identified are traced to find the root cause of the abnormality. This is done by comparing the test data with the preset working parameters to find the potential factors that cause the abnormality. For example, if an inverter appears abnormal, through the traceability data flow, it is found out whether it is caused by abnormal battery state, load mutation or external grid fluctuation, etc. Through causal analysis, the problem is found out, and detailed abnormal traceability information is generated.

[0057] Finally, based on the obtained abnormal traceability information, the load operation management module is started. The main task of this module is to adjust or intervene the relevant load operation according to the abnormal cause obtained by traceability analysis. For example, if the traceability analysis shows that the abnormal inverter is caused by the poor battery state, the battery load is adjusted, or the staff is notified to adjust.

[0058] In the embodiments of the present application, as described above, the embodiments of the present application have at least the following technical effects: The present application constructs a basic component library for power load types, wherein the basic component library contains a mapped mathematical component library and a load component library; determines the load test requirements of the test power scene, calls the basic component library for modeling and non-mechanism simplification based on the digital controller, determines the simulated power scene, wherein the input-output is only concerned as the simplification standard; introduces uncertain simulation elements and sets simulation parameters as simulation conditions; based on the simulation conditions, simulates the test data flow of the simulated power scene, which includes steady-state test and transient test. The present application solves the technical problem of poor simulation accuracy of existing technology in power load simulation. By constructing a basic component library containing a mathematical component library and a load component library, combining a digital controller for modeling and non-mechanism simplification of a test power scene, using an input-output simplification standard to determine a simulated power scene, introducing uncertain simulation elements and setting simulation parameters as simulation conditions for simulation testing, covering steady-state and transient testing, obtaining test data flow, the technical effects of improving the accuracy of simulated power scene and the comprehensiveness of simulation testing are achieved.

[0059] Embodiment two, based on the same inventive concept as the test simulation device for power load simulation in the foregoing embodiments, as shown in Figure 2 The present application provides a test simulation method for power load simulation, which comprises: A basic component library is constructed for a power load type, wherein the basic component library contains a mapped mathematical component library and a load component library; load test requirements of a test power scene are determined, based on a digital controller, the basic component library is called for modeling and non-mechanism simplification, a simulated power scene is determined, wherein only input-output is focused on as a simplification standard; uncertain simulation elements are introduced and simulation parameters are set as simulation conditions; based on the simulation conditions, the simulated power scene is simulated to determine test data flow, wherein steady-state test and transient-state test are included.

[0060] Further, the basic component library is called for modeling and non-mechanism simplification to determine a simulated power scene, specifically including: The basic component library is called to perform component calling and twin modeling on the test power scene to determine an initial power scene; load test requirements are identified to perform non-mechanism simplification on the initial power scene to determine a simulated power scene.

[0061] Further, the non-mechanism simplification on the initial power scene specifically includes: Based on load test requirements, a test subject of the initial power scene is determined; for non-test subjects of the initial power scene, a first non-test subject and a second non-test subject are divided, wherein whether intermediate logic simulation is needed is taken as a division standard; 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 behavior characteristics as output; according to the initial power scene, the test subject, the incomplete mechanism component and the non-mechanism component are reorganized to generate a simulated power scene.

[0062] Further, the introduction of uncertain simulation elements specifically includes: For the test power scene, industrial big data retrieval is performed to call homologous scene records meeting a preset approximation degree; based on the homologous scene records, power influence elements are mined, wherein a preset frequency is taken as an element mining standard, and the power influence elements are identified with linear influence relationships; the power influence elements are taken as uncertain simulation elements, wherein element random simulation under scene constraints is taken as an introduction standard.

[0063] Further, the setting of simulation parameters specifically includes: Based on the load test requirements, a steady-state test part and a transient-state test part are set, wherein fault occurrence is taken as a transient-state test condition; the steady-state test part and the transient-state test part are integrated in a classified and time-sharing manner to determine a time test sequence; based on the time test sequence, simulation parameters are determined.

[0064] Further, a digital controller is constructed, specifically including: Obtaining 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, taking the basic component library as a resource pool, taking call logic and reorganization logic as training targets, and supervising training of a digital controller.

[0065] Further, after determining the test data stream, the method further includes: Identifying the test data stream, performing state anomaly determination on the test subject, locating an abnormal time node, and performing tracing based on the test data stream to determine abnormal tracing information; and performing load operation management based on the abnormal tracing information.

[0066] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes a specific embodiment of the present application. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0067] The above only describes the preferred embodiments of the present application and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0068] The present application is only an exemplary description of the present application, and any and all modifications, changes, combinations or equivalents within the scope of the present application are considered to be covered. Obviously, those skilled in the art can make various modifications and changes to the present application without departing from the scope of the present application. Thus, if these modifications and changes of the present application belong to the scope of the present application and its equivalent technology, the present application is intended to include these modifications and changes.

Claims

1. A test simulation device for simulating electrical load, characterized in that, include: A basic component library construction module, which 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; The load test requirement determination module 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. The simulation parameter setting module introduces uncertain simulation elements and sets simulation parameters as simulation conditions. The simulation test module 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.

2. The test simulation device for simulating electrical load as described in claim 1, characterized in that, The load testing requirement determination module includes: 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 load testing requirements, performs non-mechanism simplification on the initial power scenario, and determines the simulated power scenario.

3. The test simulation device for simulating electrical load as described in claim 2, characterized in that, The aforementioned non-mechanism-simplification module includes: The test subject determination module determines the test subject of the initial power scenario based on load test requirements; 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. A first simplification module simplifies the first non-test subject into an incomplete mechanistic component; 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; 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.

4. The test simulation device for simulating electrical load as described in claim 1, characterized in that, The simulation parameter setting module includes: 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. 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. 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.

5. The test simulation device for simulating electrical load as described in claim 1, characterized in that, The simulation parameter setting module includes: 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. 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; A simulation parameter determination module determines simulation parameters based on the time test sequence.

6. The test simulation device for simulating electrical load as described in claim 1, characterized in that, The load testing requirement determination module includes: 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; 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.

7. The test simulation device for simulating electrical load as described in claim 3, characterized in that, The simulation testing module includes: 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. The load operation management module performs load operation management based on the anomaly tracing information.

8. A test simulation method for simulating electrical load, characterized in that, The method is executed by a test simulation device for simulating electrical loads according to any one of claims 1 to 7, comprising: A basic component library is constructed for each type of power load, wherein the basic component library includes a mapped mathematical component library and a load component library; The load testing requirements of the power scenario are determined. Based on the digital controller, the basic component library is called to perform modeling and non-mechanistic simplification to determine the simulated power scenario, wherein the simplification standard is to focus only on the input-output. Uncertainty simulation elements are introduced and simulation parameters are set as simulation conditions; Based on the simulation conditions, the simulated power scenario is simulated and tested to determine the test data stream, which includes steady-state testing and transient testing.

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