CN117195055A - Classification method, device, equipment and medium for executing protection action strategy - Google Patents

Abstract

The invention discloses a classification method, a device, equipment and a medium for executing a protection action strategy, wherein a simulated power distribution network model in a virtual simulation space is constructed according to power distribution network data and power distribution network distribution data by acquiring the power distribution network data when a power distribution network fails; determining target data of a fault area section in the power distribution network, and loading the target data into the simulated power distribution network model; acquiring a plurality of protection executing action strategies, and performing periodic frequency test on the protection executing action strategies based on the simulated power distribution network model to acquire test data corresponding to the protection executing action strategies; and determining the security level of the execution protection action strategy based on the test data corresponding to the execution protection action strategy. The embodiment of the invention can rapidly divide the security level of executing the protection action strategy, solves the problem of lack of executing action security analysis on the fault recovery of the power distribution network, and reduces the risk of operation of the power distribution network after the fault recovery scheme is executed.

Description

Classification method, device, equipment and medium for executing protection action strategy

Technical Field

The invention relates to the technical field of power system dispatching automation and power grid simulation, in particular to a classification method, a device, equipment and a medium for executing a protection action strategy.

Background

With the continuous expansion construction of a power distribution network and the access of a large number of distributed power sources, the topology structure of the power distribution network is complex and is extremely easy to generate faults.

The existing power distribution network is generally only provided with a current sampling element, the protection principle adopts overcurrent protection, optical fiber longitudinal differential protection and the like, fault detection is carried out on a line, and a multistage backup protection scheme is established according to connection cascade of the line.

However, when the protection action strategy is executed for practical application during the fault of the current power distribution network, the hidden danger is buried for the safe operation of the power distribution network and the intangible economic loss is brought due to the fact that the working condition of the power distribution network after the recovery scheme is not determined.

Disclosure of Invention

The invention provides a classification method, a device, equipment and a medium for executing a protection action strategy, which are used for solving the problem of lack of safety analysis on the fault recovery execution action of a power distribution network, realizing rapid division of safety levels of the execution protection action strategy, guaranteeing the reliability of the protection execution action of the power distribution network and reducing the running risk of the power distribution network after the fault recovery scheme is executed.

According to an aspect of the present invention, there is provided a classification method for executing a protection action policy, including:

acquiring power distribution network data when a power distribution network fails, and constructing a simulated power distribution network model in a virtual simulation space according to the power distribution network data and the power distribution network distribution data;

determining target data of a fault area section in the power distribution network, and loading the target data into a simulated power distribution network model;

acquiring a plurality of protection executing action strategies, and performing periodic frequency test on the protection executing action strategies based on a simulated power distribution network model to obtain test data corresponding to the protection executing action strategies;

and determining the security level of the execution protection action strategy based on the test data corresponding to the execution protection action strategy.

According to another aspect of the present invention, there is provided a classification apparatus for executing a protection action policy, including:

the model construction module is used for acquiring power distribution network data when the power distribution network fails and constructing a simulated power distribution network model in a virtual simulation space according to the power distribution network data and the power distribution network distribution data;

the target data loading module is used for determining target data of a fault area section in the power distribution network and loading the target data into the simulated power distribution network model;

The test data acquisition module is used for acquiring a plurality of protection action executing strategies, and performing periodic frequency test on the protection action executing strategies based on the simulated power distribution network model to obtain test data corresponding to the protection action executing strategies;

the level determining module is used for determining the security level of executing the protection action strategy based on the test data corresponding to the execution protection action strategy.

According to another aspect of the present invention, there is provided an electronic apparatus including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the classification of the protection action policy of any of the embodiments of the invention.

According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement classification of an execution protection action policy of any of the embodiments of the present invention when executed.

According to the technical scheme, through obtaining the distribution network data when the distribution network fails, a simulated distribution network model in a virtual simulation space is constructed according to the distribution network data and the distribution network distribution data; determining target data of a fault area section in the power distribution network, and loading the target data into a simulated power distribution network model; acquiring a plurality of protection executing action strategies, and performing periodic frequency test on the protection executing action strategies based on a simulated power distribution network model to obtain test data corresponding to the protection executing action strategies; based on the test data corresponding to the execution protection action strategy, the safety level of the execution protection action strategy is determined, so that the classified safety level of the execution protection action strategy can be rapidly divided, the problem of lack of safety analysis on the fault recovery execution action of the power distribution network is solved, the reliability of the protection execution action of the power distribution network is ensured, and the running risk of the power distribution network after the fault recovery scheme is executed is reduced.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a classification method for executing a protection action policy according to a first embodiment of the present invention;

FIG. 2 is a flowchart of a classification method for executing a protection action policy according to a second embodiment of the present invention;

fig. 3 is a schematic structural diagram of a classification device for executing a protection action policy according to a third embodiment of the present invention;

fig. 4 is a schematic structural diagram of an electronic device implementing a classification method for executing a protection action policy according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a detailed description of embodiments of the present invention will be provided below, with reference to the accompanying drawings, wherein it is apparent that the described embodiments are only some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above-described drawings are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

Fig. 1 is a flowchart of a method for classifying a protection action policy according to an embodiment of the present invention, where the method may be performed by a classifying device for performing a protection action policy, and the classifying device for performing a protection action policy may be implemented in hardware and/or software, and the classifying device for performing a protection action policy may be configured in an electronic device such as a computer or a server. As shown in fig. 1, the method includes:

S110, acquiring power distribution network data when the power distribution network fails, and constructing a simulated power distribution network model in a virtual simulation space according to the power distribution network data and the power distribution network distribution data.

In this embodiment, when the power distribution network data is a power distribution network fault, current fault values of all positions of the power distribution network are obtained through fault detection of the power distribution network, wherein the current fault values can be voltage values and current values of a current power distribution network fault area section. The fault zone segment is a fault feeder segment where there is a fault between two switches. The distribution network distribution data comprise data of current and voltage transmission paths in the distribution network and a line arrangement division diagram of the distribution network. The simulated power distribution network model is a simulation model established according to power distribution network data and power distribution network distribution data. The power distribution network faults comprise, but are not limited to, various fault types such as single-phase grounding, interphase short circuit and the like, various fault addresses such as power supply side, network side, load side and the like, various fault depths such as high-resistance grounding faults, metallic grounding faults and the like, and various fault levels such as feeder level, equipment level, system level and the like.

Specifically, the data of the distribution network and the distribution network distribution data can be checked and collected by using the related data of the distribution network counted in the network-side database, one or more fault area sections are determined by a fault area section positioning technology (such as a matrix method and an artificial intelligence method), the voltage value and the current value in the fault area sections can be detected in real time by adopting a transformer, the collection of the current fault value of the distribution network is rapidly completed, and the fault type is determined. The method can adopt a wired or wireless mode to transmit the distribution network data and distribution network distribution data acquired in real time to electronic equipment such as a computer or a server, and establishes an anthropomorphic digital model based on the mapping of the actual physical area of the distribution network under different fault types in a virtual simulation space by utilizing a virtual reality technology and a digital twin technology.

The power distribution network is detected in real time, acquired power distribution network data and power distribution network distribution data are wirelessly transmitted to a classification device executing a protection action strategy, and a fault area section is determined to exist through a fault area section positioning technology based on a neural network. And detecting the fault area section in real time by using a transformer to obtain a corresponding current voltage value and a current value, and determining the fault type of the fault area section. The method comprises the steps of merging distribution network data acquired in real time with distribution network distribution data, establishing a digital twin body based on a virtual reality technology and a digital twin technology, obtaining an anthropomorphic digital model, visually displaying the distribution network data acquired in real time and the distribution network distribution data, and simulating the running state of the distribution network to obtain simulation data.

According to the technical scheme, the accuracy of the established operation data is ensured by checking the collected power distribution network data and the collected power distribution network distribution data, and test value errors caused by deviation data are reduced. By constructing the digital twin body, the dynamic reconfiguration of the power distribution network with high real-time performance is realized, the fault of the power distribution network can be rapidly detected, the reference basis of a maintenance period can be provided, and the reliability of an analysis result is improved.

And S120, determining target data of a fault area section in the power distribution network, and loading the target data into a simulated power distribution network model.

In this embodiment, the target data is a plurality of data, such as a voltage value and a current value, for analyzing a change of a fault area segment in the power distribution network after performing an operation corresponding to the relevant execution action protection policy.

Specifically, multiple items of data required by power distribution network fault analysis are determined as target data, a historical database is established, data related to the target data of fault area segments in the power distribution network are detected according to a certain frequency, the data are stored in the historical database, one or more items of target data are obtained through analysis and calculation, and the one or more items of target data are dynamically loaded into a simulated power distribution network model together with one or more items of target data obtained through real-time acquisition.

Optionally, the target data includes each switch position, a historical switch action frequency, a last switch action time, a current voltage value and a current value.

In this embodiment, the switch positions are positions of all switches in the fault area section in the simulated power distribution network model; the historical switching action frequency is calculated according to the switching operation times and the time length of the time period in each switching position in a time period before the current time point recorded in the historical target database; the last switching action time is the time of the last switching action of the current switching action occurrence time recorded in the historical target database; the current voltage value and the current value are respectively the voltage value and the current value of the fault area section detected by the transformer in real time.

According to the technical scheme, the working states of fault area segments in the power distribution network are accurately reflected by using the positions of the switches, the historical switching action frequency, the last switching action time, the current voltage value and the current value as target data, so that the analysis result is comprehensive and reliable.

S130, acquiring a plurality of protection executing action strategies, and performing periodic frequency test on the protection executing action strategies based on the simulated power distribution network model to obtain test data corresponding to the protection executing action strategies.

In this embodiment, the protection action executing policy is based on a reference fault execution action policy corresponding to each fault type pre-stored in the power distribution network fault type execution action database. The protection action executing strategy database is a pre-established database composed of reference fault execution action protection strategies corresponding to different fault types. The periodic frequency test is a simulation test of the frequency of faults occurring in the running process of the same duration of a plurality of execution protection action strategies in a simulated power distribution network model. The test data are a plurality of result data of periodic frequency tests of executing protection action strategies in the simulated power distribution network model.

Specifically, according to the fault type of the fault area section in the power distribution network, a plurality of corresponding protection action executing strategies are selected from the protection action executing strategy database, corresponding simulation operation is carried out in a simulated power distribution network model according to the protection action executing strategies, periodic frequency test is carried out on fault recovery operation of the power distribution network, continuous collection is carried out on operation data, and intelligent analysis, such as time sequence analysis and periodic analysis, is carried out on the collected data to obtain test data corresponding to the corresponding protection action executing strategies.

According to the technical scheme, the running data are continuously collected and intelligently analyzed, and periodic optimal prediction analysis is carried out, so that an optimal execution action point in the adopted protection execution action strategy can be predicted, a reference basis for a maintenance period can be provided, and the reliability of an analysis result is improved. And the same periodic frequency test is carried out on the plurality of execution protection action strategies, so that the consistency of the same periodic frequency is ensured, and the accuracy of an analysis result is ensured.

Optionally, the plurality of protection action executing policies include an application policy and a backup policy, and the protection action executing policies are obtained based on fault type matching of the power distribution network.

In this embodiment, the application policy is a current fault execution action protection policy corresponding to each fault type, and the backup policy is one or more alternative fault execution action protection policies corresponding to each fault type.

Specifically, for each fault type of the power distribution network, there may be one application policy and one or more backup policies in the protection action policy execution database that match the fault type.

Exemplary, application policies in executing the protection action policy include, but are not limited to: when the system is in fault or abnormal condition, the action of the circuit breaker is triggered by the circuit breaker, the fault part is isolated from the power grid, and other equipment and safe operation of the power grid are protected; sending an alarm signal, and informing an operator or a monitoring system in an alarm signal mode; and automatically operating the protection device, automatically judging the fault type according to a preset protection strategy and parameters, and executing corresponding protection actions. Alternative ones of the execution protection action policies include, but are not limited to: the power supply is switched, the fault part is isolated from the power grid by switching the power supply, and the power supply is switched to a standby power supply or other reliable power supplies for supplying power; trip protection, namely, the whole power distribution network or a partial area is powered off in a trip protection mode; isolation switch operation: by operating the isolating switch, the fault equipment or the fault area is isolated from the power grid, so that the fault diffusion and the influence on the normal operation of other equipment are prevented; remote control operation: through remote control operation, the on-off state of the equipment is remotely controlled, so that operations such as fault isolation, power supply recovery and the like are realized, and the convenience and safety of operation are improved; and (5) automatically restarting.

Optionally, the periodic frequency test is a periodic frequency test of executing a protection action strategy singly, and test data obtained by any one periodic frequency test includes a switching action frequency, a switching action frequency interval, and a voltage value and a current value of fault sections before and after each switching.

In this embodiment, the switching operation frequency is a switching operation frequency calculated by the switching element at each switching position in the target data according to the switching operation times and the duration of the time period in the periodic frequency test stage; the switching action frequency interval is a time interval between two adjacent switching actions in a periodic frequency test stage; the voltage value is the voltage value of a fault section in the simulated power distribution network model at the front and rear moments when the switching action occurs; the current value is the current value of the fault section in the simulated power distribution network model at the front and rear moments when the switching action occurs.

Specifically, each protection action strategy corresponding to each fault type in the protection action strategy execution database is tested for one time or multiple times in the simulated power distribution network model, and each periodic frequency test continuously collects and intelligently analyzes operation data to obtain test data comprising switching action frequency, switching action frequency interval, voltage values and current values of fault sections before and after each switching.

And S140, determining the security level of the execution protection action strategy based on the test data corresponding to the execution protection action strategy.

In this embodiment, the security level is a level division of the execution action according to the fault index of each execution protection action policy, where the fault index is one or more indexes of the execution protection action policy that fail in a future period of time obtained by analyzing and calculating the obtained test data when each execution protection action policy performs a periodic frequency test in the simulated power distribution network model.

Specifically, the security level of the protection action executing policy may be divided into a plurality of levels in advance, that is, a plurality of protection action executing policies corresponding to each fault type may be divided into a plurality of security level types, and the test data of the plurality of protection action executing policies may be analyzed and calculated by using a method of manual, deep learning or traditional machine learning, so as to classify the corresponding plurality of protection action executing policies, and each protection action executing policy corresponds to one security level type.

For example, the security level of the protection action policy may be classified into two major categories, high and low, according to the test data corresponding to the protection action policy, and the security level may be further classified into an optimal type in a category of low security level. The method based on the neural network can be adopted to classify according to the test data corresponding to each execution protection action strategy, so that the security classification of all execution protection action strategies is realized.

In order to more intuitively measure the fault degree of the power distribution network, a fault index can be used for reflecting the operation condition of the power distribution network after fault recovery by using an execution protection action strategy in a fault area section.

Optionally, determining a fault index of the protection action policy based on the test data corresponding to the protection action policy, where the fault index includes one or more of a fault rate, a fault number, fault point data, and repeated fault point data; and determining evaluation data for executing the protection action strategy based on the fault index for executing the protection action strategy, and determining the security level for executing the protection action strategy based on the evaluation data and the security level threshold.

In this embodiment, the failure rate is a percentage of the failure time of the period of performing the periodic frequency test in the simulated power distribution network model to the overall periodic frequency test time, that is, failure rate= [ (downtime+maintenance time)/planned use total time ] ×100%. The number of faults is the number of faults occurring in the periodic frequency test stage. And the fault point data or repeated fault point data are respectively the test data of each fault area section which appears or repeatedly appears when the simulated power distribution network model is subjected to periodic frequency test. The evaluation data are result data of comprehensive analysis of the fault index and are used for evaluating the safety of executing the protection action strategy. The security level threshold is a preset threshold of a security level classification standard for executing a protection action policy.

Specifically, test data obtained by periodically testing the execution protection action strategy in the simulated power distribution network model are analyzed and calculated, the repair protection action execution status, the route execution status and the action execution probability status of the fault type corresponding to the execution strategy are analyzed and represented by fault indexes, the fault frequency, the fault reason and the fault hazard degree of the power distribution network during the periodically testing are comprehensively and safely analyzed by the fault indexes, evaluation data of the execution protection action strategy are obtained, the evaluation data are compared with a preset safety grade threshold value, and the safety grade classification of the execution protection action strategy is realized, wherein the safety grade classification is the safety grade of the execution protection action strategy.

For example, assuming that the fault index includes a fault rate, a fault number, fault point data and repeated fault point data, the evaluation data is a comprehensive value obtained by analysis and calculation by using a neural network, and the security level threshold is a standard threshold for performing security level classification of a protection action policy obtained based on deep learning. The security level classification model is trained in advance, so that the security level classification model is input into test data obtained by periodically testing the protection action executing strategy in the simulated power distribution network model, a security level threshold value is determined according to the training data, evaluation data of the protection action executing strategy obtained through calculation is compared with the security level threshold value, and the security level type of the protection action executing strategy is output. Classifying the security level of the execution protection action strategy by using the trained security level classification model, and if the evaluation data is larger than the security level threshold value, considering that the security level of the execution protection action strategy is low, and classifying the execution protection action strategy into a type with low security level; if the evaluation data is smaller than the security level threshold, the security level of the execution protection action strategy is considered to be high, and the execution protection action strategy is classified into a type with high security level; if the evaluation data is smaller than the security level threshold and exceeds the 10% value, the security level of the execution protection action policy is considered to be optimal, and the execution protection action policy is further classified into a type with the optimal security level.

In order to more accurately determine the fault index of the protection action strategy, test data can be analyzed, so that the fault index meets the classification requirement of the protection action strategy, and is more reliable.

Optionally, fault identification is performed on test data obtained by performing multiple periodic frequency tests of the protection action strategy, and a fault index of the protection action strategy is determined according to a fault identification result of the test result of the multiple periodic frequency tests.

In this embodiment, the fault recognition is to recognize whether the simulated power distribution network model has a power distribution network fault according to a test result obtained during the periodic frequency test.

Specifically, the test results of multiple equal periodic frequency tests can be analyzed, and the test data of the simulated power distribution network model when the power distribution network fails can be identified and used as a failure identification result. And comprehensively analyzing one or more test data in the fault identification result to obtain the calculation relation between the test result and the fault index, and determining the fault index for executing the protection action strategy.

Illustratively, the comprehensive analysis of one or more items of test data in the failure recognition result may be performed using an artificial intelligence algorithm (e.g., machine learning) and/or a conventional mathematical model algorithm (e.g., factor analysis) to assign a respective weight to each item of test data.

According to the technical scheme, through obtaining the distribution network data when the distribution network fails, a simulated distribution network model in a virtual simulation space is constructed according to the distribution network data and the distribution network distribution data; determining target data of a fault area section in the power distribution network, and loading the target data into a simulated power distribution network model; acquiring a plurality of protection executing action strategies, and performing periodic frequency test on the protection executing action strategies based on a simulated power distribution network model to obtain test data corresponding to the protection executing action strategies; based on the test data corresponding to the execution protection action strategy, the safety level of the execution protection action strategy is determined, so that the safety level of the execution protection action strategy can be rapidly divided, the problem of lack of safety analysis on the fault recovery execution action of the power distribution network is solved, the reliability of the protection execution action of the power distribution network is ensured, and the running risk of the power distribution network after the fault recovery scheme is executed is reduced.

Example two

Fig. 2 is a flowchart of a classification method for executing a protection action policy according to a second embodiment of the present invention, where the technical solution of the embodiment of the present invention is further optimized based on any of the foregoing embodiments. As shown in fig. 2, the method includes:

S210, acquiring power distribution network data when a power distribution network fails, and constructing a simulated power distribution network model in a virtual simulation space according to the power distribution network data and the power distribution network distribution data.

S220, determining target data of fault area segments in the power distribution network, and loading the target data into a simulated power distribution network model.

S230, acquiring a plurality of execution protection action strategies.

S240, classifying the execution protection action policies to obtain at least two types of execution protection action policy groups.

In the present embodiment, the group of execution protection action policies is a group in which execution protection action policies are divided according to the degree of similarity between execution protection action policies.

Specifically, by classifying the execution protection action policies into two or more similarity categories according to the similarity between the execution protection action policies, each execution protection action policy is assigned to a corresponding execution protection action policy group according to the similarity category.

For example, a similarity threshold range may be set, and the execution protection action policies with similarity within the similarity threshold range are classified as optimal similar execution protection action policy groups, and the other execution protection action policies are classified as sub-selected similar execution protection action policy groups.

The classification processing of the protection action executing strategy can rely on subjective judgment of personnel, and can also set a similarity degree evaluation index to determine a classification standard.

Optionally, similarity data of the backup policy and the application policy is determined, and the backup policy is classified according to the similarity data and a classification threshold.

In this embodiment, the similarity data is distance data between the application policy and the backup policy, and is used to evaluate the similarity between the application policy and the backup policy.

Specifically, feature extraction can be performed on application policies and backup policies by using methods such as a text classification method, a statistical method, a machine learning method, a deep learning method and the like to obtain application policy features x and backup policy features y, similarity data d of the application policy features x and the backup policy features y can be obtained by using methods such as a manhattan distance, a chebyshev distance, a euclidean distance and the like, and each backup policy is classified and belongs to a corresponding execution protection action policy group according to a preset similarity threshold range and similarity data d of each backup policy and the application policy.

For example, the similarity data d of the application policy feature x and the backup policy feature y may be calculated by using the following formula:

The backup strategies of similarity data d E [0,1] are classified into optimal similar execution protection action strategy groups, and other backup strategies are classified into sub-selected similar execution protection action strategy groups.

According to the technical scheme, the protection execution action strategies with higher similarity are classified into the same protection execution action strategy group, and the protection execution action strategies of the same protection execution action strategy group are classified into the safety grades, so that the classification precision is improved, and the safety analysis result is more reliable.

S250, respectively performing periodic frequency test on a plurality of execution protection action strategies in the execution protection action strategy group in the same execution protection action strategy group to obtain test data corresponding to each execution protection action strategy.

Specifically, all the execution protection action policies in each execution protection action policy group can be respectively subjected to the same periodic frequency test, so as to obtain test data corresponding to each execution protection action policy in the execution protection action policy group.

Optionally, for the same execution protection action policy group, using a representative execution protection action policy to represent all execution protection action policies, and performing periodic frequency test on the representative execution protection action policy to obtain test data corresponding to the representative execution protection action policy.

Specifically, for each execution protection action policy group, any one execution protection action policy group in the execution protection action policy group may be used as a representative execution protection action policy of the execution protection action policy group, or a representative execution protection action policy may be generated by analyzing all execution protection action policies in the execution protection action policy group, which is not limited in this embodiment. And performing simulation test on the representative execution protection action strategy in the simulated power distribution network model only to obtain test data.

According to the technical scheme of the embodiment, the security level classification of the representative execution protection action strategy of the execution protection action strategy group is used as the security level classification of all the execution protection action strategies in the execution protection action strategy group, so that the computing resources are saved, the classification efficiency is improved, and the security analysis efficiency of the power distribution network work after the restoration scheme is executed is greatly improved.

S260, determining the security level of the execution protection action strategy based on the test data corresponding to the execution protection action strategy.

According to the technical scheme, through obtaining the distribution network data when the distribution network fails, a simulated distribution network model in a virtual simulation space is constructed according to the distribution network data and the distribution network distribution data; determining target data of a fault area section in the power distribution network, and loading the target data into a simulated power distribution network model; acquiring a plurality of execution protection action policies; classifying the execution protection action policies to obtain at least two types of execution protection action policy groups; for the same execution protection action strategy group, respectively performing periodic frequency test on a plurality of execution protection action strategies in the execution protection action strategy group to obtain test data corresponding to each execution protection action strategy; based on the test data corresponding to the execution protection action strategy, the security level of the execution protection action strategy is determined, finer division of the security level of the execution protection action strategy can be realized, the security analysis of the fault recovery execution action of the power distribution network is more comprehensive and reliable, and the risk of operation of the power distribution network after the fault recovery scheme is executed is further reduced.

Example III

Fig. 3 is a schematic structural diagram of a classification device for executing a protection action policy according to a third embodiment of the present invention. As shown in fig. 3, the apparatus includes:

the model construction module 310 is configured to obtain power distribution network data when a power distribution network fails, and construct a simulated power distribution network model in a virtual simulation space according to the power distribution network data and the power distribution network distribution data;

the target data loading module 320 is configured to determine target data of a fault area segment in the power distribution network, and load the target data into a simulated power distribution network model;

the test data obtaining module 330 is configured to obtain a plurality of protection execution action policies, and perform periodic frequency test on the protection execution action policies based on the simulated power distribution network model, so as to obtain test data corresponding to the protection execution action policies;

the level determining module 340 is configured to determine a security level of executing the protection action policy based on the test data corresponding to the execution protection action policy.

According to the technical scheme, through obtaining the distribution network data when the distribution network fails, a simulated distribution network model in a virtual simulation space is constructed according to the distribution network data and the distribution network distribution data; determining target data of a fault area section in the power distribution network, and loading the target data into a simulated power distribution network model; acquiring a plurality of protection executing action strategies, and performing periodic frequency test on the protection executing action strategies based on a simulated power distribution network model to obtain test data corresponding to the protection executing action strategies; based on the test data corresponding to the execution protection action strategy, the safety level of the execution protection action strategy is determined, so that the safety level of the execution protection action strategy can be rapidly divided, the problem of lack of safety analysis on the fault recovery execution action of the power distribution network is solved, the reliability of the protection execution action of the power distribution network is ensured, and the running risk of the power distribution network after the fault recovery scheme is executed is reduced.

On the basis of the above embodiment, optionally, the target data includes each switch position, a historical switch action frequency, a last switch action time, a current voltage value and a current value.

On the basis of the embodiment, optionally, the plurality of protection action executing strategies include an application strategy and a backup strategy, and the protection action executing strategies are obtained based on fault type matching of the power distribution network.

On the basis of the above embodiment, optionally, the periodic frequency test is a periodic frequency test for executing the protection action strategy singly, and the test data obtained by any one of the periodic frequency tests includes the switching action frequency, the switching action frequency interval, and the voltage value and the current value of the fault section before and after each switching.

Based on the above embodiment, the optional level determining module 340 specifically includes:

the fault index determining unit is used for determining a fault index for executing the protection action strategy based on the test data corresponding to the execution protection action strategy, wherein the fault index comprises one or more of a fault rate, a fault frequency, fault point data and repeated fault point data;

and the security level determining unit is used for determining evaluation data for executing the protection action strategy based on the fault index for executing the protection action strategy and determining the security level for executing the protection action strategy based on the evaluation data and the security level threshold value.

On the basis of the above embodiment, optionally, the fault indicator determining unit is specifically configured to: and carrying out fault identification on test data obtained by carrying out multiple periodic frequency tests of the protection action strategy, and determining fault indexes of the protection action strategy according to the fault identification results of the test results of the multiple periodic frequency tests.

Based on the above embodiment, optionally, the test data acquisition module 330 includes:

the strategy acquisition unit is used for acquiring a plurality of execution protection action strategies;

the policy classification unit is used for classifying the execution protection action policies to obtain at least two types of execution protection action policy groups;

the test data acquisition unit is used for respectively carrying out periodic frequency test on a plurality of execution protection action strategies in the execution protection action strategy group in the same execution protection action strategy group to obtain test data corresponding to each execution protection action strategy.

Based on the above embodiment, optionally, the policy classification unit is specifically configured to determine similarity data between the backup policy and the application policy, and perform type classification on the backup policy based on the similarity data and a type classification threshold.

The classifying device for executing the protection action strategy provided by the embodiment of the invention can execute the classifying method for executing the protection action strategy provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the executing method.

Example IV

Fig. 4 is a schematic structural diagram of an electronic device implementing a classification method for executing a protection action policy according to an embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic devices may also represent various forms of mobile equipment, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing equipment. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as performing classification of protection action policies.

In some embodiments, the classification of the protection action policy may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more of the steps of performing classification of protection action policies described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the classification of the protection action policy in any other suitable way (e.g., by means of firmware).

Various implementations of the systems and techniques described here above can be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

The computer program for implementing the classification of protection action policies of the invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

Example five

The fifth embodiment of the present invention further provides a computer readable storage medium, where computer instructions are stored, where the computer instructions are configured to cause a processor to execute a classification method for executing a protection action policy, where the method includes:

acquiring power distribution network data when a power distribution network fails, and constructing a simulated power distribution network model in a virtual simulation space according to the power distribution network data and the power distribution network distribution data; determining target data of a fault area section in the power distribution network, and loading the target data into a simulated power distribution network model; acquiring a plurality of protection executing action strategies, and performing periodic frequency test on the protection executing action strategies based on a simulated power distribution network model to obtain test data corresponding to the protection executing action strategies; and determining the security level of the execution protection action strategy based on the test data corresponding to the execution protection action strategy.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims (10)

1. A method of classifying an execution protection action policy, comprising:

acquiring power distribution network data when a power distribution network fails, and constructing a simulated power distribution network model in a virtual simulation space according to the power distribution network data and the power distribution network distribution data;

determining target data of a fault area section in the power distribution network, and loading the target data into the simulated power distribution network model;

acquiring a plurality of protection executing action strategies, and performing periodic frequency test on the protection executing action strategies based on the simulated power distribution network model to acquire test data corresponding to the protection executing action strategies;

and determining the security level of the execution protection action strategy based on the test data corresponding to the execution protection action strategy.

2. The method of claim 1, wherein the target data includes switch positions, historical switch operation frequencies, last switch operation time, current voltage values, and current values.

3. The method of claim 1, further comprising, after obtaining the plurality of execution protection action policies:

classifying the execution protection action policies to obtain at least two types of execution protection action policy groups;

Correspondingly, the periodic frequency test is performed on the protection action executing strategy based on the simulated power distribution network model to obtain test data corresponding to the protection action executing strategy, which comprises the following steps:

and respectively carrying out periodic frequency test on a plurality of execution protection action strategies in the execution protection action strategy group in the same execution protection action strategy group to obtain test data corresponding to each execution protection action strategy.

4. The method of claim 3, wherein the plurality of execution protection action policies includes an application policy and a backup policy, the execution protection action policies being derived based on a fault type match of the distribution network;

the classifying the protection action executing strategy comprises the following steps:

and determining similarity data of the backup strategy and the application strategy, and carrying out type classification on the backup strategy based on the similarity data and a type classification threshold value.

5. The method of claim 1, wherein determining the security level of the protection action policy based on the test data corresponding to the protection action policy comprises:

Determining a fault index of the execution protection action strategy based on the test data corresponding to the execution protection action strategy, wherein the fault index comprises one or more of a fault rate, a fault frequency, fault point data and repeated fault point data;

and determining evaluation data of the execution protection action strategy based on the fault index of the execution protection action strategy, and determining the security level of the execution protection action strategy based on the evaluation data and a security level threshold.

6. The method of claim 5, wherein determining the failure indicator of the protection action policy based on the test data corresponding to the protection action policy comprises:

and carrying out fault identification on the test data obtained by the multiple periodic frequency tests of executing the protection action strategy, and determining the fault index of the executing protection action strategy according to the fault identification result of the test result of the multiple periodic frequency tests.

7. The method according to claim 1 or 6, wherein the periodic frequency test is a periodic frequency test for executing a protection action strategy singly, and the test data obtained by any one of the periodic frequency tests comprises a switching action frequency, a switching action frequency interval, and a voltage value and a current value of fault sections before and after each switching.

8. A classification device for executing a protection action policy, comprising:

the model construction module is used for acquiring power distribution network data when the power distribution network fails and constructing a simulated power distribution network model in a virtual simulation space according to the power distribution network data and the power distribution network distribution data;

the target data loading module is used for determining target data of a fault area section in the power distribution network and loading the target data into the simulated power distribution network model;

the test data acquisition module is used for acquiring a plurality of protection action executing strategies, and carrying out periodic frequency test on the protection action executing strategies based on the simulated power distribution network model to acquire test data corresponding to the protection action executing strategies;

and the grade determining module is used for determining the security grade of the execution protection action strategy based on the test data corresponding to the execution protection action strategy.

9. An electronic device, the electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the classification method of performing a protection action policy of any of claims 1-7.

10. A computer readable storage medium storing computer instructions for causing a processor to implement the classification method of performing a protection action policy of any one of claims 1-7 when executed.