CN116861834B - Power installation testing method and system - Google Patents
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Abstract
The invention discloses a power installation test method and a system, which belong to the field of power system engineering, wherein the method comprises the following steps: acquiring a design scheme of power installation, wherein the design scheme comprises a circuit topological structure and a component preassembling bit number; constructing a virtual digital twin circuit according to a design scheme; performing data mining on the installation scene, extracting an electrical performance test case, and performing virtual comprehensive test on the digital twin circuit based on the case to obtain a primary test result; when the primary test result passes, selecting an element preassembly bit number corresponding to the distribution position of the key element, removing the element from the digital twin circuit, and retesting to extract the expected value of the electrical performance of the element; carrying out local actual measurement on the actual element according to the expected value to obtain a secondary test result; the secondary test is passed by namely license-mounting identification is carried out on the pre-mounted bit number of the element. The technical problem that electric power installation stability is poor among the prior art has been solved to this application, has reached the technological effect that improves electric power installation stability.
Description
Technical Field
The invention relates to the field of power system engineering, in particular to a power installation testing method and system.
Background
The electric power system is an infrastructure of the modern society, and the safe and stable operation of the electric power system has important significance for the production and the living of various industries. The quality of the power installation as an important component of the power system directly influences the power supply reliability of the power system. However, the existing power installation test method is mainly based on the entity circuit for comprehensive test, the test mode is easy to be interfered by environment, the accuracy of test data is difficult to ensure, the actual performance of power installation under different operation conditions is difficult to be comprehensively reflected, and the stability of power installation is poor.
Disclosure of Invention
The application provides a power installation test method and system, which aim to solve the technical problem of poor power installation stability in the prior art.
In view of the above, the present application provides a power installation test method and system.
In a first aspect of the present disclosure, a power installation testing method is provided, the method comprising: acquiring an electric power installation plan, wherein the electric power installation plan comprises a circuit topological structure and a component preassembling bit number, and performing circuit simulation according to the circuit topological structure and the component preassembling bit number to construct a simulated digital twin circuit; performing data mining based on the electric power installation scene to obtain an electric performance test case; based on the electrical performance test case, performing virtual test on the simulated digital twin circuit to obtain a primary test result; when the primary test result is that the test passes, the i-th element preassembly bit number of the element preassembly bit number is obtained, and the i-th element distribution position is matched from the circuit topological structure; in the simulation digital twin circuit, updating the electrical performance of a circuit topology structure except for the distribution position of the ith element into a test passing state, and performing virtual test on the simulation digital twin circuit based on an electrical performance test case to obtain an expected value of the electrical performance of the ith element with a preassembled bit number of the ith element; and according to the expected value of the electrical performance, actually measuring the ith element to obtain a secondary test result, and when the secondary test result is passed, carrying out license installation identification on the preassembled bit number of the ith element.
In another aspect of the present disclosure, there is provided a power installation testing system, the system comprising: the installation plan acquisition module is used for acquiring an electric power installation plan, wherein the electric power installation plan comprises a circuit topological structure and a component preassembly bit number; the power circuit simulation module is used for carrying out circuit simulation according to the circuit topological structure and the element preassembling bit number to construct a simulated digital twin circuit; the scene data mining module is used for carrying out data mining based on the electric power installation scene to acquire an electric performance test case; the circuit virtual test module is used for carrying out virtual test on the simulated digital twin circuit based on the electrical performance test case to obtain a primary test result; the element distribution matching module is used for acquiring an ith element preassembly bit number of the element preassembly bit number when the primary test result is that the test passes, and matching the ith element distribution position from the circuit topological structure; the element performance expected module is used for updating the electrical performance of a circuit topology structure except for the distribution position of the ith element into a test passing state in the simulated digital twin circuit, and performing virtual test on the simulated digital twin circuit based on an electrical performance test case to obtain an expected value of the electrical performance of the ith element with a preassembled bit number of the ith element; and the license installation identification module is used for carrying out actual measurement on the ith element according to the expected value of the electrical performance, obtaining a secondary test result, and carrying out license installation identification on the preassembled bit number of the ith element when the secondary test result is passed.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
because the design scheme for acquiring power installation is adopted, the method comprises a circuit topological structure and element preassembling bit numbers; constructing a virtual digital twin circuit according to a design scheme; extracting electrical performance test cases by mining big data of working conditions related to a design scheme, and carrying out virtual comprehensive test on the digital twin circuit based on the test cases to obtain a primary test result; when the primary test result passes, selecting an element preassembly bit number corresponding to the distribution position of the key element, removing the element from the digital twin circuit, and retesting to extract the expected value of the electrical performance of the element; carrying out local actual measurement on the actual element according to the expected value to obtain a secondary test result; the technical scheme of carrying out license installation identification on the element preassembled position number in the secondary test solves the technical problem of poor electric power installation stability in the prior art, and achieves the technical effect of improving the electric power installation stability.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a schematic diagram of a possible flow chart of a power installation test method according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a possible process of obtaining an electrical performance test case in a power installation test method according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a possible process of obtaining a discrete coefficient calibration result in the power installation test method according to the embodiment of the present application;
fig. 4 is a schematic diagram of a possible structure of a power installation test system according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a mounting plan acquisition module 11, a power circuit simulation module 12, a scene data mining module 13, a circuit virtual test module 14, an element distribution matching module 15, an element performance expected module 16 and a license mounting identification module 17.
Detailed Description
The technical scheme provided by the application has the following overall thought:
the embodiment of the application provides a power installation test method and system. Firstly, a power installation design scheme is obtained, wherein the power installation design scheme comprises a circuit topological structure and element preassembling bit numbers, and a virtual digital twin circuit is constructed according to the design scheme. And then, extracting an electrical performance test case through data mining, and performing virtual test on the digital twin circuit based on the test case to obtain a preliminary comprehensive test result. Secondly, when the primary test result passes, the key element pre-installation bit number in the design scheme and the distribution position of the key element pre-installation bit number in the circuit are locked. The element is eliminated in a digital twin circuit by simulation and retested to obtain the desired electrical performance parameters thereof. Again, the component is actually tested according to the desired electrical performance parameters to verify the accuracy of the virtual test results. And if the actual measurement result passes, confirming the rationality of the pre-installed bit number design scheme of the element, otherwise, returning to redesign. And finally, repeating the process, and finally, confirming the preassembled bit numbers of all the elements to complete the comprehensive test and verification of the power installation design scheme.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Embodiment one: as shown in fig. 1, an embodiment of the present application provides a power installation test method, which includes:
step S1000: acquiring a power installation plan, wherein the power installation plan comprises a circuit topological structure and a component preassembly bit number;
specifically, referring to a structural layout of the power system, the structural layout is marked with installation positions of each element in space, and the installation positions are element preassembly position numbers. Then, the connection relationship between the elements is determined in combination with the structural layout and the power system installation principle, thereby obtaining the circuit topology. The circuit topology structure refers to a connection relation among all electric elements in the power system, and comprises a connection sequence and a connection mode of all the elements, such as series connection, parallel connection and the like, and is used for determining paths and related parameters in a circuit; the component preassembly position number refers to preset installation positions of each electrical component in the power system, and the preset installation positions are determined in the design stage of the power system so as to guide the subsequent actual installation.
By acquiring the circuit topology structure and the pre-installed position numbers of the elements, the structure of the power system and the pre-installed positions of the elements are defined, and necessary information is provided for subsequent digital twin circuit simulation and element installation test.
Step S2000: performing circuit simulation according to the circuit topology structure and the element pre-installation bit number to construct a simulated digital twin circuit;
specifically, after the circuit topology structure and the element pre-installation bit number are acquired, corresponding element parameters, such as rated voltage, rated current, impedance parameters and the like, are acquired according to the element pre-installation bit number, and an element digital twin model is constructed, wherein the model comprises the static characteristics and the mathematical model of the element. Next, in the circuit simulation software, a simulated circuit model identical to the actual circuit topology is constructed from the circuit topology. The constructed element digital twin model is then imported onto the corresponding element location. Then, initialization parameters of the simulation circuit model, such as power values, power factors and the like, are set, a simulation time range is set, and simulation solving is started. And then, checking simulation results, such as waveforms and values of voltage, current, power and the like, and judging whether the results are consistent with the actual circuit. If the simulation circuit model is not matched, parameters in the simulation model, such as impedance values and voltage values, are adjusted, and the simulation circuit model is repeatedly set until the results are matched. When the simulation circuit model and the parameter verification pass, the simulation circuit model and the parameter are simulation digital twin circuits matched with the actual circuit.
By constructing a simulation model equivalent to an actual circuit based on a circuit topology structure and element parameters, continuously adjusting the model to enable an output result of the model to be consistent with the actual circuit, and finally forming a simulation digital twin circuit matched with the actual circuit, a foundation is laid for automatic electric power installation test.
Step S3000: performing data mining based on the electric power installation scene to obtain an electric performance test case;
specifically, the power installation scenario refers to a scenario feature of an actual application environment and an operation condition of the power system. The electrical performance test case is a set of input conditions and expected output results for testing relevant electrical performance indicators in a power system under a certain specific power installation scenario.
First, a power installation scenario is determined, for example, the power production scale of a power plant is determined according to the unit capacity of the power plant, and then a power use scenario, for example, residential power consumption, industrial power consumption and the like, is determined according to the power production scale. Historical operational record data, such as power, voltage, current, power factor, etc., of the genset is then collected in the power installation scenario, and these data constitute a dataset. Checking the data discrete degree of each electrical performance index in the data set, if the data discrete degree of a certain index is high, indicating that the data set has obvious outliers, wherein the data range of the outliers is the test case. Meanwhile, the obtained preliminary test cases are evaluated, and whether the range of the preliminary test cases accords with the allowable range of an actual power system is judged. If the test case is out of the allowable range, the test case is not valid and needs to be removed. And then, optimizing and sorting the evaluated test cases, and integrating the test cases to cover all key states by considering different possible running states of the power system in the power installation scene to form a final electrical performance test case which comprises an electrical performance index name, a test input value and an expected output result.
The historical operation data is collected based on the power installation scene, and the electrical performance test cases matched with the scene are extracted through means of data analysis, evaluation and the like, so that the extracted test cases can cover key operation states possibly encountered by the power system, and necessary test basis is provided for power installation verification.
Step S4000: based on the electrical performance test case, performing virtual test on the simulated digital twin circuit to obtain a primary test result;
specifically, in order to verify the performance of the power circuit, based on the acquired electrical performance test cases, virtual testing is performed on the simulated digital twin circuit, and a primary test result is acquired. The virtual test is to perform a virtual test on the obtained analog digital twin circuit to verify whether the electrical performance of the analog digital twin circuit meets the requirement. The primary test result is a global test result of the circuit, and if the test is passed, the performance of the power circuit is indicated to meet the requirement; if not, the circuit needs to be modified.
Firstly, selecting an electrical performance test case matched with a current simulation digital twin circuit, and loading the electrical performance test case into circuit simulation software. Then, the test input conditions in the test case are loaded onto the element model simulating the corresponding position of the digital twin circuit, for example, the voltage values of the test inputs are loaded onto the primary sides of all the transformer models. Then, running simulation software, starting to solve a simulation digital twin circuit model, and obtaining output results of all elements, such as waveforms of current, voltage, power and the like. The output results of the elements are then compared with the expected outputs in the test case. If the results are matched, the position test is passed; if not, this position test is indicated as not passing. If the results of all the positions are consistent with the expected output, the final test is passed, and the simulation digital twin circuit and parameters which are passed by the test are recorded; if a certain position is not matched, the position information is recorded, the use case test is returned to be carried out again, the element model of the position is corrected, and the execution is repeated until the test passes. The output results of all the positions need to be verified, the whole test cannot pass due to the fact that the output results of any position cannot pass, and the final test passes only when the output results of all the positions meet expected output.
And verifying the electrical performance of each position of the simulated digital twin circuit one by one through the steps of loading a test case, running simulation, comparing and outputting, correcting a model and the like, ensuring that the output result meets the test case requirement, and finally obtaining a simulation model passing the test through the integral test, thereby providing a basis for actual measurement of subsequent equipment.
Step S5000: when the primary test result is that the test passes, acquiring an ith element preassembly bit number of the element preassembly bit number, and matching the ith element distribution position from the circuit topological structure;
specifically, after the result of the first-level test is obtained, in order to further verify the performance of each element, the pre-installation bit number of each element is obtained, and the element distribution positions are matched from the circuit topology structure.
Firstly, in a simulated digital twin circuit passing the primary test, element pre-installation bit numbers are traversed, element pre-installation bit numbers of all elements are obtained one by one, the element pre-installation bit numbers are recorded as i element pre-installation bit numbers according to the traversing sequence, i is the traversed number of the element, for example, the 1 st traversed element is the 1 st element pre-installation bit number, the 2 nd traversed element is the 2 nd element pre-installation bit number and the like. And then searching the traversed element preassembly bit number information in the circuit topology structure information to determine the distribution position of the selected element, recording the preassembly bit number of the selected element and the distribution position thereof, and using the preassembly bit number of the selected element as information of a follow-up element local test, thereby laying a foundation for realizing automatic test and preassembly verification, realizing feasibility verification and further improving the stability of electric power installation.
Step S6000: in the simulation digital twin circuit, updating the electrical performance of the circuit topology structure except for the distribution position of the ith element into a test passing state, and performing virtual test on the simulation digital twin circuit based on the electrical performance test case to obtain an expected value of the electrical performance of the ith element with the preset bit number of the ith element;
specifically, first, the electrical parameters of all elements except the ith element in the analog digital twin circuit are locked to the parameter values that pass the first-order test. Then, loading an electrical performance test case matched with the current power installation scene in simulation software, and loading the test input condition into the i-th element. Then, simulation software is operated to carry out simulation solution, and output results of the ith element, such as voltage, current waveforms, values and the like, are obtained, and the output results form expected electrical performance values of the ith element.
And then, correlating the expected value of the electrical performance of the ith element with the preassembled bit number of the ith element, and using the expected value of the electrical performance of the ith element and the preassembled bit number of the ith element as input of a subsequent secondary test to guide the selection and verification of the ith element. Since the electrical parameters of all elements except the ith element are test passing values, only the output of the ith element in the simulation results will change. The output of other elements keeps the state that the test passes, so that the obtained expected value of the electrical performance of the ith element is not influenced by the other elements, and the performance characteristics of the ith element in the power installation scene are accurately represented. Meanwhile, according to the different types of the ith element, the expected value of the electrical performance can be different output results, such as the secondary side voltage of the transformer can be obtained by the transformer, the opening and closing time of the circuit breaker can be obtained by the circuit breaker.
The method for locking the output of other elements in the specified power installation scene is adopted, and the expected value of the electrical performance of the ith element is obtained through virtual test, so that basis and reference are provided for secondary test and actual equipment selection.
Step S7000: and according to the electrical performance expected value, actually measuring an ith element to obtain a secondary test result, and when the secondary test result is passed, carrying out license installation identification on the preassembled bit number of the ith element.
Specifically, first, according to the technical parameter manual and the usage standard of the ith element, the allowable tolerance range or performance requirement of the element is determined, and the actual measurement threshold is formed. Meanwhile, a plurality of devices which are matched with the requirement of the ith element are selected as candidate devices for actual measurement, and test input which is the same as the expected value is required to be applied during actual measurement. Then, the measured output results, such as voltage, current, power, etc., of each candidate device are obtained and compared with the measured threshold. If the measured value is larger than the measured threshold value, the measured value does not pass; if the measured threshold value is smaller than or equal to the measured threshold value, the measured value passes. And if the actual measurement results of all the devices do not pass, returning to reselect other devices as candidate devices for testing. If the measured result of a device passes, the device is allowed to be mounted on the pre-mounted position of the i-th element. And then, recording the installation permission equipment information and the information thereof on the preassembled position as the basis of subsequent maintenance. And simultaneously, carrying out license installation identification on the preassembly bit number to guide the actual installation work. The license installation identification is associated with the preassembly bit number and the equipment information and is recorded in a design file of the power system and the information management system, and equipment and positions which are allowed to be installed can be directly confirmed according to the identification during actual installation.
The equipment meets the performance requirement through actual measurement, the allowable installation position is identified, and the feasibility verification of the electrical equipment is realized. And the verification efficiency and accuracy are greatly improved by combining with a digital twin technology, a foundation is laid for the installation of the power system, and the power installation stability is further improved.
Further, as shown in fig. 2, the embodiment of the present application further includes:
step S3100: the power installation scenario includes a power production type and a power production scale;
step S3200: taking the power generation type and the power generation scale as constraint scenes, and acquiring power generation record data based on big data;
step S3300: and according to the power production record data, performing data mining on the electrical performance index to obtain an electrical performance test case.
Specifically, the power installation scenario includes a power production type and a power production scale, which together determine the actual working environment and operating conditions that a certain power system faces. Wherein, the electric power production type is characterized by binary code, for example, the residential electricity consumption is 00, the chemical production electricity consumption is 01, and the commercial electricity consumption is-10. The power production scale is also represented by binary codes, such as 0-500 user being 00, 501-5000 user being 01, 5001-50000 user being 10, more than 50001 user being 11. The combination of the two codes forms a characteristic code representing an installation scene, so that a certain power system can be accurately positioned. And then, constructing a database query statement according to the determined binary codes of the power production type and the scale, and searching record data matching the current scene in a historical operation record database. And executing the constructed database query statement to obtain a search result set, wherein the result set contains all recorded data matched with the current scene and is used for subsequent data mining analysis.
Then, corresponding electrical performance indicators, such as rated voltage, current, active power, reactive power, inductance, ac amplification, dissipated power, etc., are determined for the different electrical components. And then, analyzing data related to the electrical performance indexes in the big data set according to the selected electrical performance indexes, extracting modes and rules in the data, and obtaining an electrical performance test case which is used for verifying the key operation state of the power system in the power installation scene and providing necessary basis for automatic test.
By utilizing the electric power installation scene to locate the range of the data set and adopting big data and data mining technology to analyze historical operation data, the electric performance test case matched with the scene is obtained, and a test basis and a verification benchmark are provided for an automatic test method.
Further, the embodiment of the application further includes:
step S3310: acquiring ith electrical performance index record data according to the power production record data;
step S3320: traversing the ith electrical performance index record data to perform discrete coefficient analysis, and obtaining a discrete coefficient calibration result;
step S3330: cleaning the ith electrical performance index record data with the discrete coefficient calibration result being greater than or equal to a discrete coefficient threshold value, and obtaining an ith electrical performance record data cleaning result;
Step S3340: and carrying out extremum evaluation on the cleaning result of the ith electrical performance record data to obtain the electrical performance test case.
Specifically, first, the specified electrical performance index is traversed to obtain the i-th electrical performance index, partial data corresponding to the i-th electrical performance index is extracted from the total record data set, and the i-th electrical performance index record data is obtained as an analysis target. The recorded data corresponding to the ith electrical performance index reflects the actual change condition of the index under different conditions. Then, the degree of dispersion between the recorded data is judged by discrete analysis means such as calculating the difference coefficient between the recorded data. If the degree of dispersion is larger, the data set is indicated to have more outliers, and the data range of the outliers is suitable to be used as a test case. Subsequently, a discrete coefficient threshold is set and the recorded dataset is filtered. The filtering basis is a discrete coefficient calibration result, and recorded data with the discrete degree smaller than a threshold value are removed. The filtered data set only contains data with larger discrete degree, which is beneficial to the generation of subsequent test cases.
Then, according to the maximum value and the minimum value evaluation, extracting the maximum/minimum recorded data range in the recorded data cleaning result; and evaluating the extracted data range to judge whether the extracted data range accords with the situation possibly happening in practice. If not, this range is indicated as unsuitable for use as a test case. If it is practical, it is indicated that it can constitute the input range of the test case. Then, the time range of the recorded data set is used as a test requirement, such as summer, heavy load period and the like, and the selected input range is expanded to be still effective under different conditions. And then integrating and optimizing the input ranges, ensuring the normalization and the integrity of the test cases, deleting redundant test cases, and avoiding repetition. The test case includes information such as an index name, a test input range, expected output, a test requirement and the like, and the expected output is determined according to the allowable range of the ith electrical performance index.
Further, as shown in fig. 3, the embodiment of the present application further includes:
step S3321: traversing the ith electrical performance index record data to perform deviation calculation according to the kth record data of the ith electrical performance index record data to obtain a kth deviation distance set;
step S3322: based on the kth record data, m record data are screened from the kth offset distance set from near to far, and m is constructed k A neighborhood;
step S3323: screening m j The neighborhood contains n record data of the kth record data, and n is constructed k A neighborhood, wherein the n k Neighborhood and the m k Recording data in a neighborhood without intersection;
step S3324: traversing the n based on the kth record data k Neighborhood and the m k A neighborhood, calculating the average value of the sum of the reciprocal of the distance, and obtaining the distribution density of the kth recorded data;
step S3325: and obtaining the distribution density average value of the ith electrical performance index recorded data, comparing the distribution density average value with the distribution density of the kth recorded data, and obtaining the discrete coefficient calibration result.
Specifically, the kth recorded data in the ith electrical performance index recorded data is used as a reference, deviation between the kth recorded data and other recorded data is calculated, a group of deviation values is obtained, a kth deviation distance set is formed, and the degree of change of the kth recorded data and the other recorded data is reflected. Then, from the kth offset distance set, m pieces of record data having smaller offset values from the kth record data are selected, and m pieces of record data are formed together with the kth record data k A neighborhood representing a dataset that is closer to the kth recorded data.
The other recorded data except the kth recorded data corresponding to the ith electrical performance index also has a corresponding offset distance set to form m j Neighborhood each containing a distance of departure from the kth recorded data. From m j Screening out n smaller distance data with the k record data deviation distance from the neighborhood to form n k A neighborhood. Wherein n is k The neighborhood is from other set of offset distances, m k The neighborhood is from the kth offset distance set, and no intersection between two neighbors records data.
Subsequently, the kth recorded data and m are calculated k Neighborhood and n k And calculating the average value of the sum of reciprocal distances among all the recorded data in the adjacent domains to obtain the distribution density of the kth recorded data. The larger the distribution density is, the more elements in the data set are in the vicinity of the kth recorded data. Calculating the ith electrical performance index pair according to the distribution density calculation modeAnd calculating the average value of all the distribution densities of all the recorded data, and comparing the average value with the distribution density of the kth recorded data to obtain a discrete coefficient calibration result of the kth recorded data. The larger the discrete coefficient calibration result of the kth recorded data is, the smaller the distribution density is compared with the average distribution density, so that the less elements around the kth recorded data are indicated, and the recorded data are outliers.
By constructing m of recorded data k Neighborhood and n k And (3) the neighborhood, calculating the distribution density of each recorded data, and finally obtaining the discrete coefficient calibration result of the kth recorded data. The larger discrete coefficient calibration result shows that an outlier exists, and a reference is provided for the test case generation.
Further, the embodiment of the application further includes:
step S3341: performing hierarchical clustering analysis on the i-th electrical performance record data cleaning result according to the i-th electrical performance preset deviation to obtain a record data clustering result, wherein the record data clustering result has an intra-class characteristic value and an intra-class support degree, the intra-class characteristic value represents record data, and the intra-class support degree refers to the number of record data gathered in a class;
step S3342: acquiring an ith electrical performance index extreme value convergence direction, wherein the ith electrical performance index extreme value convergence direction comprises a maximum value direction and a minimum value direction;
step S3343: when the convergence direction of the ith electrical performance index extreme value is the maximum value direction, extracting the intra-class characteristic value with the intra-class support degree larger than or equal to the intra-class support degree threshold value, and carrying out maximum value screening to construct the electrical performance test case;
Step S3344: and when the convergence direction of the ith electrical performance index extreme value is the minimum value direction, extracting the intra-class characteristic value with the intra-class support degree larger than or equal to the intra-class support degree threshold value, and carrying out minimum value screening to construct the electrical performance test case.
Specifically, firstly, setting preset deviation according to the data type of the ith electrical performance index, and analyzing and classifying the cleaning result of the recorded data by using a hierarchical clustering method to obtain a clustering result of the recorded data. The clustering result includes intra-class feature values, which represent the cluster centers, and intra-class support, which represent the recorded data amounts contained in the clusters. Then, judging the convergence direction of the extreme value according to the property of the ith electrical performance index, and if the index value is larger, the convergence direction of the extreme value is the maximum value direction; if the index value is smaller, the value is more strict, and the extreme value convergence direction is the minimum value direction. The convergence direction is judged to provide a direction for subsequent extremum screening.
And if the extreme value convergence direction is the maximum value direction, selecting the record data with the support degree in the class being greater than or equal to the threshold value as a clustering center, and taking the corresponding data range as the input range of the test case. The higher support degree in the class indicates that more record data is gathered near the classification center, and the record data is more representative and more suitable to be used as a test case. And if the extreme value convergence direction is the minimum value direction, selecting the record data with the support degree in the class being greater than or equal to the threshold value as a clustering center, and taking the corresponding data range as the input range of the test case.
The method comprises the steps of classifying recorded data cleaning results by adopting a hierarchical clustering method, selecting corresponding clustering centers and data ranges thereof as test case input ranges according to extreme value convergence directions, and selecting a classification center with stronger representativeness, so that the obtained test cases are more accurate and reliable.
Further, the embodiment of the application further includes:
step S33411: when the extreme value convergence direction of the ith electrical performance index is the maximum value direction, a first hierarchical clustering formula is constructed:
，
，
，
wherein,characterizing a certain cluster of the q-th generation,>all elements in a certain cluster characterizing passage q,/->Characterizing an i-th electrical performance preset deviation, < >>Characterization of the maximum screening function,/->Intra-class feature value characterizing a certain cluster of the q-th generation,>characterizing the support degree in the class;
step S33412: when the convergence direction of the ith electrical performance index extreme value is the minimum value direction, a second hierarchical clustering formula is constructed:
，
，
，
wherein,characterizing a certain cluster of the q-th generation,>all elements in a certain cluster characterizing passage q,/->Characterizing an i-th electrical performance preset deviation, < >>Characterization of the minimum screening function->Intra-class feature value characterizing a certain cluster of the q-th generation, >Characterizing the support degree in the class;
step S33413: and performing hierarchical clustering analysis on the i-th electrical performance record data cleaning result according to the first hierarchical clustering formula or the second hierarchical clustering formula to obtain the record data clustering result.
Specifically, through analysis of the obtained cleaning result of the ith electrical performance record data, two kinds of cluster analysis formulas are constructed according to the difference of the convergence directions of the extremum of the ith electrical performance index.
When the convergence direction of the ith electrical performance index extreme value is the maximum value direction, a first hierarchical clustering formula is constructed as follows:
，
，
，
wherein,a certain cluster characterizing passage q, consisting of a set of elements +.>Composition of these elementsThe difference between the elements does not exceed a preset deviation +.>；/>Representing the ith electrical performance preset deviation; />The intra-class feature value of a certain cluster characterizing the q-th generation is the element +.>Is filtered by a maximum filter function>Acquisition (I)>Characterization of support within class, element +.>By->And (5) function acquisition.
When the convergence direction of the ith electrical performance index extreme value is the minimum value direction, the worker constructs a second hierarchical clustering formula as follows:
，
，
，
wherein,a certain cluster of the q-th generation is characterized, Is made up of a group of elements->Composition is prepared. The difference between these elements does not exceed a predetermined deviation +.>；/>Representing the ith electrical performance preset deviation; />The intra-class feature value of a certain cluster characterizing the q-th generation is the element +.>Is filtered by a minimum value filter function>Acquiring; />Characterization of support within class, element +.>By->And (5) function acquisition.
And then, carrying out cluster analysis on the cleaning result of the ith electrical performance record data according to the constructed first hierarchical clustering formula or second hierarchical clustering formula to obtain a record data clustering result, and gathering the record data with high similarity in the same cluster to effectively distinguish different operation modes and working states, thereby obtaining more accurate test cases.
Further, the embodiment of the application further includes:
step S2100: acquiring rated electrical parameters and functional parameters of the element according to the element preassembly position number;
step S2200: constructing an element digital twin model according to the element rated electrical parameters and the element functional parameters;
step S2300: and virtually connecting the element digital twin model according to the circuit topological structure to obtain the simulation digital twin circuit.
Specifically, firstly, corresponding rated electrical parameters of the element, such as voltage level, current rated value, impedance value and the like, and element function parameters, such as action time of a switching element, steady state error and the like, are obtained according to the element pre-installation bit number. And then, constructing a corresponding element digital twin model by adopting a digital twin technology according to the acquired element rated electrical parameters and element functional parameters. The constructed element digital twin model should have the same electrical and dynamic response characteristics as the physical element.
And finally, according to the circuit topology structure to be simulated, logically connecting the digital twin models of all the elements, for example, connecting the elements at two ends through wires or buses, controlling the switching element to be influenced by other elements, and the like, so as to obtain the final simulated digital twin circuit. The simulated digital twin circuit is formed by combining a plurality of element digital twin models through virtual connection, and has the same static and dynamic electrical characteristics as a physical circuit.
By constructing the element digital twin model and the simulated digital twin circuit, effective virtual support and pre-test are carried out on the physical circuit, the possible problems of the physical circuit are predicted, reference and support are provided for the physical test, and the improvement of the electrical installation test precision is facilitated, so that the stability of the electrical installation is improved.
In summary, the power installation test method provided by the embodiment of the application has the following technical effects:
acquiring a power installation plan, wherein the power installation plan comprises a circuit topological structure and a component preassembly bit number, and providing a data base for constructing twin power by acquiring required power installation design information; performing circuit simulation according to the circuit topology structure and the element preassembly bit number, constructing a simulated digital twin circuit, and providing a platform for virtual test and simulation optimization; data mining is carried out based on an electric power installation scene, an electric performance test case is obtained, and a universal representative test working condition and index are extracted according to the actual electric power installation operation condition, so that a basis is provided for virtual test; based on an electrical performance test case, performing virtual test on the simulated digital twin circuit to obtain a primary test result, and performing preliminary comprehensive inspection on a design scheme by using a virtual test environment to find potential problems or verify design rationality;
when the primary test result is that the test passes, the i-th element preassembly bit number of the element preassembly bit number is obtained, the i-th element distribution position is matched from the circuit topology structure, and the element with the greatest influence on the system performance is locked in the design scheme and used as the object of subsequent actual measurement; in the simulation digital twin circuit, the electrical performance of a circuit topology structure except for the distribution position of the ith element is updated to be in a test passing state, virtual test is carried out on the simulation digital twin circuit based on an electrical performance test case, an expected value of the electrical performance of the ith element with a preassembled bit number of the ith element is obtained, an ideal working state of a key element is predicted through the virtual test, and a reference is provided for judging an actual measurement result; according to the expected value of the electrical performance, the ith element is actually measured, a secondary test result is obtained, when the secondary test result is passed, the preassembled position number of the ith element is subjected to permission installation identification, and the accuracy of the virtual test is verified through a real object, so that the test precision is improved, and the electric power installation stability is further improved.
Embodiment two: based on the same inventive concept as one of the power installation test methods in the foregoing embodiments, as shown in fig. 4, an embodiment of the present application provides a power installation test system, including:
a mounting plan obtaining module 11, configured to obtain a power mounting plan, where the power mounting plan includes a circuit topology and a component preassembly bit number;
the power circuit simulation module 12 is used for performing circuit simulation according to the circuit topology structure and the component preassembly bit number to construct a simulated digital twin circuit;
the scene data mining module 13 is used for carrying out data mining based on the power installation scene to acquire an electrical performance test case;
the circuit virtual test module 14 is used for carrying out virtual test on the simulated digital twin circuit based on the electrical performance test case to obtain a primary test result;
the element distribution matching module 15 is configured to obtain an i element preassembly bit number of the element preassembly bit number when the primary test result is that the test passes, and match the i element distribution position from the circuit topology structure;
an element performance expectation module 16, configured to update, in the analog digital twin circuit, an electrical performance of the circuit topology structure except for the i-th element distribution position to a test passing state, and perform a virtual test on the analog digital twin circuit based on the electrical performance test case, to obtain an i-th element electrical performance expectation value of the i-th element preassembly bit number;
And the license installation identification module 17 is used for carrying out actual measurement on the ith element according to the electrical performance expected value, obtaining a secondary test result, and carrying out license installation identification on the preassembled bit number of the ith element when the secondary test result is passed.
Further, the scene data mining module 13 includes the following execution steps:
the power installation scenario includes a power production type and a power production scale;
taking the power generation type and the power generation scale as constraint scenes, and acquiring power generation record data based on big data;
and according to the power production record data, performing data mining on the electrical performance index to obtain an electrical performance test case.
Further, the scene data mining module 13 further comprises the following execution steps:
acquiring ith electrical performance index record data according to the power production record data;
traversing the ith electrical performance index record data to perform discrete coefficient analysis, and obtaining a discrete coefficient calibration result;
cleaning the ith electrical performance index record data with the discrete coefficient calibration result being greater than or equal to a discrete coefficient threshold value, and obtaining an ith electrical performance record data cleaning result;
And carrying out extremum evaluation on the cleaning result of the ith electrical performance record data to obtain the electrical performance test case.
Further, the scene data mining module 13 further comprises the following execution steps:
traversing the ith electrical performance index record data to perform deviation calculation according to the kth record data of the ith electrical performance index record data to obtain a kth deviation distance set;
based on the kth record data, m record data are screened from the kth offset distance set from near to far, and m is constructed k A neighborhood;
screening m j The neighborhood contains n record data of the kth record data, and n is constructed k A neighborhood, wherein the n k Neighborhood and the m k Recording data in a neighborhood without intersection;
traversing the n based on the kth record data k Neighborhood and the m k A neighborhood, calculating the average value of the sum of the reciprocal of the distance, and obtaining the distribution density of the kth recorded data;
and obtaining the distribution density average value of the ith electrical performance index recorded data, comparing the distribution density average value with the distribution density of the kth recorded data, and obtaining the discrete coefficient calibration result.
Further, the scene data mining module 13 further comprises the following execution steps:
performing hierarchical clustering analysis on the i-th electrical performance record data cleaning result according to the i-th electrical performance preset deviation to obtain a record data clustering result, wherein the record data clustering result has an intra-class characteristic value and an intra-class support degree, the intra-class characteristic value represents record data, and the intra-class support degree refers to the number of record data gathered in a class;
Acquiring an ith electrical performance index extreme value convergence direction, wherein the ith electrical performance index extreme value convergence direction comprises a maximum value direction and a minimum value direction;
when the convergence direction of the ith electrical performance index extreme value is the maximum value direction, extracting the intra-class characteristic value with the intra-class support degree larger than or equal to the intra-class support degree threshold value, and carrying out maximum value screening to construct the electrical performance test case;
and when the convergence direction of the ith electrical performance index extreme value is the minimum value direction, extracting the intra-class characteristic value with the intra-class support degree larger than or equal to the intra-class support degree threshold value, and carrying out minimum value screening to construct the electrical performance test case.
Further, the scene data mining module 13 further comprises the following execution steps:
when the extreme value convergence direction of the ith electrical performance index is the maximum value direction, a first hierarchical clustering formula is constructed:
，
，
，
wherein,characterizing a certain cluster of the q-th generation,>all elements in a certain cluster characterizing passage q,/->Characterizing an i-th electrical performance preset deviation, < >>Characterization of the maximum screening function,/->Characterizing a certain generation qIntra-class feature values of clusters,/->Characterizing the support degree in the class;
When the convergence direction of the ith electrical performance index extreme value is the minimum value direction, a second hierarchical clustering formula is constructed:
，
，
，
wherein,characterizing a certain cluster of the q-th generation,>all elements in a certain cluster characterizing passage q,/->Characterizing an i-th electrical performance preset deviation, < >>Characterization of the minimum screening function->Intra-class feature value characterizing a certain cluster of the q-th generation,>characterizing the support degree in the class;
and performing hierarchical clustering analysis on the i-th electrical performance record data cleaning result according to the first hierarchical clustering formula or the second hierarchical clustering formula to obtain the record data clustering result.
Further, the circuit virtual test module 14 includes the following steps:
acquiring rated electrical parameters and functional parameters of the element according to the element preassembly position number;
constructing an element digital twin model according to the element rated electrical parameters and the element functional parameters;
and virtually connecting the element digital twin model according to the circuit topological structure to obtain the simulation digital twin circuit.
Any of the steps of the methods described above may be stored as computer instructions or programs in a non-limiting computer memory and may be called by a non-limiting computer processor to identify any of the methods to implement embodiments of the present application, without unnecessary limitations.
Further, the first or second element may not only represent a sequential relationship, but may also represent a particular concept, and/or may be selected individually or in whole among a plurality of elements. It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (8)
1. A power installation test method, comprising:
acquiring a power installation plan, wherein the power installation plan comprises a circuit topological structure and a component preassembly bit number;
performing circuit simulation according to the circuit topology structure and the element pre-installation bit number to construct a simulated digital twin circuit;
performing data mining based on the electric power installation scene to obtain an electric performance test case;
based on the electrical performance test case, performing virtual test on the simulated digital twin circuit to obtain a primary test result;
when the primary test result is that the test passes, acquiring an ith element preassembly bit number of the element preassembly bit number, and matching the ith element distribution position from the circuit topological structure;
In the simulation digital twin circuit, updating the electrical performance of the circuit topology structure except for the distribution position of the ith element into a test passing state, and performing virtual test on the simulation digital twin circuit based on the electrical performance test case to obtain an expected value of the electrical performance of the ith element with the preset bit number of the ith element;
and according to the electrical performance expected value, actually measuring an ith element to obtain a secondary test result, and when the secondary test result is passed, carrying out license installation identification on the preassembled bit number of the ith element.
2. The power installation test method according to claim 1, wherein the data mining based on the power installation scene to obtain the electrical performance test cases comprises:
the power installation scenario includes a power production type and a power production scale;
taking the power generation type and the power generation scale as constraint scenes, and acquiring power generation record data based on big data;
and according to the power production record data, performing data mining on the electrical performance index to obtain an electrical performance test case.
3. The power installation test method according to claim 2, wherein the step of performing data mining on the electrical performance index according to the power production record data to obtain an electrical performance test case comprises the steps of:
Acquiring ith electrical performance index record data according to the power production record data;
traversing the ith electrical performance index record data to perform discrete coefficient analysis, and obtaining a discrete coefficient calibration result;
cleaning the ith electrical performance index record data with the discrete coefficient calibration result being greater than or equal to a discrete coefficient threshold value, and obtaining an ith electrical performance record data cleaning result;
and carrying out extremum evaluation on the cleaning result of the ith electrical performance record data to obtain the electrical performance test case.
4. A method of power installation testing as claimed in claim 3, wherein traversing the ith electrical performance index record data for discrete coefficient analysis to obtain a discrete coefficient calibration result comprises:
traversing the ith electrical performance index record data to perform deviation calculation according to the kth record data of the ith electrical performance index record data to obtain a kth deviation distance set;
based on the kth record data, m record data are screened from the kth offset distance set from near to far, and m is constructed k A neighborhood;
screening m j The neighborhood contains n record data of the kth record data, and n is constructed k A neighborhood, wherein the n k Neighborhood and the m k Recording data in a neighborhood without intersection;
traversing the n based on the kth record data k Neighborhood and the m k A neighborhood, calculating the average value of the sum of the reciprocal of the distance, and obtaining the distribution density of the kth recorded data;
and obtaining the distribution density average value of the ith electrical performance index recorded data, comparing the distribution density average value with the distribution density of the kth recorded data, and obtaining the discrete coefficient calibration result.
5. A power installation test method according to claim 3, wherein performing extremum evaluation on the cleaning result of the ith electrical performance record data to obtain the electrical performance test case comprises:
performing hierarchical clustering analysis on the i-th electrical performance record data cleaning result according to the i-th electrical performance preset deviation to obtain a record data clustering result, wherein the record data clustering result has an intra-class characteristic value and an intra-class support degree, the intra-class characteristic value represents record data, and the intra-class support degree refers to the number of record data gathered in a class;
acquiring an ith electrical performance index extreme value convergence direction, wherein the ith electrical performance index extreme value convergence direction comprises a maximum value direction and a minimum value direction;
When the convergence direction of the ith electrical performance index extreme value is the maximum value direction, extracting the intra-class characteristic value with the intra-class support degree larger than or equal to the intra-class support degree threshold value, and carrying out maximum value screening to construct the electrical performance test case;
and when the convergence direction of the ith electrical performance index extreme value is the minimum value direction, extracting the intra-class characteristic value with the intra-class support degree larger than or equal to the intra-class support degree threshold value, and carrying out minimum value screening to construct the electrical performance test case.
6. The power installation test method according to claim 5, wherein hierarchical clustering analysis is performed on the i-th electrical performance record data cleaning result according to the i-th electrical performance preset deviation to obtain a record data clustering result, wherein the record data clustering result has an intra-class feature value and an intra-class support degree, the intra-class feature value refers to representative record data, and the intra-class support degree refers to the number of record data pieces aggregated in a class, and the method comprises:
when the extreme value convergence direction of the ith electrical performance index is the maximum value direction, a first hierarchical clustering formula is constructed:
，
，
，
wherein,characterizing a certain cluster of the q-th generation, >All elements in a certain cluster characterizing passage q,/->Characterizing an i-th electrical performance preset deviation, < >>Characterization of the maximum screening function,/->Intra-class feature value characterizing a certain cluster of the q-th generation,>characterizing the support degree in the class;
when the convergence direction of the ith electrical performance index extreme value is the minimum value direction, a second hierarchical clustering formula is constructed:
，
，
，
wherein,characterizing a certain cluster of the q-th generation,>characterizing all of a cluster of the q-th generationElement(s)>Characterizing an i-th electrical performance preset deviation, < >>Characterization of the minimum screening function->Intra-class feature value characterizing a certain cluster of the q-th generation,>characterizing the support degree in the class;
and performing hierarchical clustering analysis on the i-th electrical performance record data cleaning result according to the first hierarchical clustering formula or the second hierarchical clustering formula to obtain the record data clustering result.
7. The power installation test method of claim 1, wherein performing circuit simulation based on the circuit topology and the component pre-load bit number to construct a simulated digital twin circuit comprises:
acquiring rated electrical parameters and functional parameters of the element according to the element preassembly position number;
Constructing an element digital twin model according to the element rated electrical parameters and the element functional parameters;
and virtually connecting the element digital twin model according to the circuit topological structure to obtain the simulation digital twin circuit.
8. A power installation testing system for implementing a power installation testing method as claimed in any one of claims 1 to 7, comprising:
the device comprises a mounting plan acquisition module, a power management module and a power management module, wherein the mounting plan acquisition module is used for acquiring a power mounting plan, and the power mounting plan comprises a circuit topological structure and a component preassembly bit number;
the power circuit simulation module is used for carrying out circuit simulation according to the circuit topological structure and the element preassembling bit number to construct a simulated digital twin circuit;
the scene data mining module is used for carrying out data mining based on the power installation scene to acquire an electrical performance test case;
the circuit virtual test module is used for carrying out virtual test on the simulated digital twin circuit based on the electrical performance test case to obtain a primary test result;
The element distribution matching module is used for acquiring an ith element preassembly bit number of the element preassembly bit number when the primary test result is that the test passes, and matching the ith element distribution position from the circuit topological structure;
the element performance expected module is used for updating the electrical performance of the circuit topological structure except for the i-th element distribution position into a test passing state in the simulated digital twin circuit, and performing virtual test on the simulated digital twin circuit based on the electrical performance test case to obtain an i-th element electrical performance expected value of the i-th element preassembly bit number;
and the license installation identification module is used for carrying out actual measurement on the ith element according to the expected value of the electrical performance to obtain a secondary test result, and carrying out license installation identification on the preassembled bit number of the ith element when the secondary test result is passed.
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