CN117171366B - Knowledge graph construction method and system for power grid dispatching operation status - Google Patents
Knowledge graph construction method and system for power grid dispatching operation status Download PDFInfo
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Abstract
本发明公开了用于电网调度运行态势的知识图谱构建方法及系统，涉及电网调度知识图谱构建技术领域，包括数据采集模块、服务器、隐患感知模块、风险分析模块、比对分析模块以及提示模块。本发明通过对电网调度知识图谱构建系统进行图谱构建时的准确性进行评估，当图谱构建过程中存在准确性异常时，提示通知电力操作人员电网调度知识图谱构建系统进行图谱构建时可能存在较高的安全隐患风险，需要提前对电网调度知识图谱构建系统进行及时运维管理，有效地避免电力操作人员未能及时发现电网中潜在的安全风险，保障电网调度知识图谱构建系统对知识图谱进行高效地构建，进而保障电网调度知识图谱构建系统稳定高效地运行。
The invention discloses a knowledge graph construction method and system for power grid dispatching operation status, relates to the technical field of power grid dispatching knowledge graph construction, and includes a data collection module, a server, a hidden danger perception module, a risk analysis module, a comparison analysis module and a prompt module. The present invention evaluates the accuracy of the power grid dispatching knowledge graph construction system when constructing the graph. When there is an accuracy abnormality during the graph construction process, it prompts and informs the power operator that the power grid dispatching knowledge graph construction system may have higher accuracy when constructing the graph. It is necessary to carry out timely operation and maintenance management of the power grid dispatching knowledge graph construction system in advance to effectively prevent power operators from failing to discover potential safety risks in the power grid in time and ensure that the power grid dispatching knowledge graph construction system can efficiently implement the knowledge graph. Construction, thereby ensuring the stable and efficient operation of the power grid dispatching knowledge graph construction system.
Description
Technical Field
The invention relates to the technical field of power grid dispatching knowledge graph construction, in particular to a knowledge graph construction method and a system for power grid dispatching operation situations.
Background
The construction of a knowledge graph system for a grid dispatching operation situation is a complex task, and a large amount of power system data and knowledge are required to be integrated and presented in a graph form so as to support grid operators to monitor and manage the power system better.
The prior art has the following defects: the accuracy of the map construction is crucial to a power grid dispatching operation situation system, and if the accuracy is abnormal and not found in the map construction process, electric operators cannot timely find potential safety risks in the power grid, such as overload of equipment, instability or potential faults of the power grid, which can cause accidents and damage to the safety of the power grid and the equipment.
The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
The invention aims to provide a knowledge graph construction method and a knowledge graph construction system for a power grid dispatching operation situation, which are used for evaluating the accuracy of the power grid dispatching knowledge graph construction system in graph construction, and sending an early warning prompt through a prompt module when the accuracy is abnormal in the graph construction process, and informing an electric operator that higher potential safety hazard risks possibly exist in the process of carrying out graph construction through the prompt when the power grid dispatching knowledge graph construction system is informed, so that the power grid dispatching knowledge graph construction system needs to be managed in time and operation in advance, the situation that the electric operator cannot find potential safety risks in a power grid in time is effectively avoided, the power grid dispatching knowledge graph construction system is guaranteed to construct the knowledge graph efficiently, and the power grid dispatching knowledge graph construction system is guaranteed to operate stably and efficiently, so that the problems in the background technology are solved.
In order to achieve the above object, the present invention provides the following technical solutions: the knowledge graph construction system for the power grid dispatching operation situation comprises a data acquisition module, a server, a hidden danger sensing module, a risk analysis module, a comparison analysis module and a prompt module;
the data acquisition module acquires a plurality of data information, including measurement index information and performance information, when the power grid dispatching knowledge graph construction system performs graph construction, and after acquisition, the measurement index information and the performance information are uploaded to the server after being processed;
the server comprehensively analyzes the measurement index information and the performance information which are processed when the power grid dispatching knowledge graph construction system carries out graph construction, generates a hidden danger assessment index, and transmits the hidden danger assessment index to the hidden danger sensing module;
the hidden danger sensing module is used for comparing and analyzing hidden danger assessment indexes with a preset hidden danger assessment index reference threshold value when the power grid dispatching knowledge graph construction system carries out graph construction, generating a high hidden danger signal or a low hidden danger signal, and transmitting the signals to the risk analysis module;
the risk analysis module is used for comprehensively analyzing a plurality of hidden danger assessment indexes and hidden danger assessment index reference thresholds which are generated subsequently through the server after the high hidden danger signals generated when the power grid dispatching knowledge graph construction system performs graph construction are obtained, so as to generate risk indexes, and transmitting the risk indexes to the comparison analysis module;
The comparison analysis module is used for comparing the generated risk index with a preset risk index to generate a risk signal, transmitting the signal to the prompt module, and sending an early warning prompt through the prompt module.
Preferably, the measurement index information when the power grid dispatching knowledge graph construction system carries out graph construction comprises a performance statistics index abnormal variation coefficient and an average absolute error difference state hiding coefficient, the performance information when the power grid dispatching knowledge graph construction system carries out graph construction comprises a response time length abnormal hiding coefficient, and after acquisition, the data acquisition module respectively marks the performance statistics index abnormal variation coefficient and the average absolute error difference state hiding coefficient asAnd->The response time abnormal hiding coefficient is marked as +.>。
Preferably, the logic for obtaining the abnormal coefficient of variation of the performance statistics index is as follows:
s101, acquiring actual performance statistical indexes of different time periods in a T time when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual performance statistical indexes as，yThe number of the actual performance statistical indexes of different time periods in the T time when the power grid dispatching knowledge graph construction system performs graph construction is represented,y=1、2、3、4、……、q，qis a positive integer;
S102, acquiring an actual performance statistical index in a T time when carrying out map construction through a power grid dispatching knowledge map construction systemCalculating the standard deviation of the actual performance statistical index and the average value of the actual performance statistical index, and respectively calibrating the standard deviation of the actual performance statistical index and the average value of the actual performance statistical index as +.>And->Then:，/>；
s103, carrying out map construction through a power grid dispatching knowledge map construction system, wherein the map construction is carried out in real time within T timeStandard deviation of the statistical index of the marginal performanceAnd the mean value of the actual performance statistics +.>Calculating the actual performance statistical index variation coefficient, wherein the calculated expression is as follows: />；
S104, calculating abnormal variation coefficients of the performance statistical indexes, wherein the calculated expression is as follows:。
preferably, the logic for obtaining the average absolute error concealment coefficient is as follows:
s201, acquiring actual data and a data set of knowledge graph data when a power grid dispatching knowledge graph construction system performs graph construction;
s202, acquiring actual data and knowledge graph data of each data point at different moments in T time for each data point when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual data and the knowledge graph data as respectively And->，xThe actual data of each data point at different moments in the T time and the serial numbers of the knowledge graph data are represented when the power grid dispatching knowledge graph construction system performs graph construction,x=1、2、3、4、……、n，nis a positive integer;
s203, through knowledge graph dataAnd (3) the actual data->Calculate eachThe absolute error of the data point in the time T is calculated by the following formula: />；
S204, establishing a data set by using absolute errors of data points generated in the time T when the grid dispatching knowledge graph construction system performs graph construction, and calibrating the data set asMThen:，kthe number of the data point when the power grid dispatching knowledge graph construction system performs graph construction is represented,k=1、2、3、4、……、m，mis a positive integer;
s205, calculating an average absolute error difference state concealment coefficient, wherein the calculated expression is as follows:，mand the total number of data points when the grid dispatching knowledge graph construction system performs graph construction is represented.
Preferably, the logic for obtaining the response time abnormal concealment coefficient is as follows:
s301, acquiring an optimal response time length range when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the optimal response time length range as；
S302, acquiring a plurality of actual response time durations generated in a T time when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual response time durations as ，vThe number of the actual response time length generated in the time T when the power grid dispatching knowledge graph construction system performs graph construction is represented,v=1、2、3、4、……、u，uis a positive integer;
s303, calculating response time abnormal hiding coefficients, wherein the calculated expression is as follows:wherein->Representing +.A.A power grid dispatching knowledge graph construction system acquires a range which is not in the optimal response time length and is not in the optimal response time length in the time of graph construction>Number of actual response time between +.>，/>Is a positive integer>，uAnd the total number of the actual response time lengths acquired in the time T when the power grid dispatching knowledge graph construction system performs graph construction is represented.
Preferably, the server obtains the abnormal variation coefficient of the performance statistical indexMean absolute error state concealment coefficient +.>And response duration anomaly concealment coefficient +.>Afterwards, will->、/>And +.>Carrying out formulated analysis to generate hidden danger assessment index +.>The formula according to is: />Wherein->、/>、/>Respectively is the abnormal variation coefficient of the performance statistics index +.>Average absolute error state concealment coefficientAnd response duration anomaly concealment coefficient +.>Is a preset proportionality coefficient of>、/>、/>Are all greater than 0.
Preferably, the hidden danger sensing module compares the hidden danger assessment index generated when the power grid dispatching knowledge graph construction system performs graph construction with a preset hidden danger assessment index reference threshold value for analysis, and the analysis is as follows:
If the hidden danger assessment index is greater than or equal to the hidden danger assessment index reference threshold, generating a high hidden danger signal through the hidden danger sensing module, and transmitting the signal to the risk analysis module;
if the hidden danger assessment index is smaller than the hidden danger assessment index reference threshold, a low hidden danger signal is generated through the hidden danger sensing module, and the signal is transmitted to the risk analysis module.
Preferably, after the risk analysis module obtains the high hidden danger signal generated when the power grid dispatching knowledge graph construction system performs graph construction, a plurality of hidden danger assessment indexes and hidden danger assessment index reference thresholds which are generated subsequently through the server are comprehensively analyzed to generate a risk indexThe formula according to is: />In which, in the process,representing a risk assessment index that is subsequently generated by the server that is greater than or equal to a risk assessment index reference threshold,ba number indicating a hidden trouble evaluation index equal to or greater than a hidden trouble evaluation index reference threshold value which is subsequently generated by the server,b=1、2、3、4、……、s，sis a positive integer.
Preferably, the comparison and analysis module compares the generated risk index with a preset risk index, and the analysis is as follows:
if the risk index is greater than or equal to the risk index reference threshold, generating a high risk signal through the comparison analysis module, transmitting the signal to the prompt module, and sending out an early warning prompt through the prompt module;
If the risk index is smaller than the risk index reference threshold, a low risk signal is generated through the comparison analysis module, the signal is transmitted to the prompt module, and the early warning prompt is not sent out through the prompt module.
The knowledge graph construction method for the power grid dispatching operation situation comprises the following steps:
collecting multiple data information, including measurement index information and performance information, when the power grid dispatching knowledge graph construction system performs graph construction, and processing the measurement index information and the performance information when the power grid dispatching knowledge graph construction system performs graph construction after collecting the data information;
comprehensively analyzing the processed measurement index information and performance information when the power grid dispatching knowledge graph construction system performs graph construction, and generating hidden danger assessment indexes;
comparing and analyzing the hidden danger assessment index with a preset hidden danger assessment index reference threshold value when the power grid dispatching knowledge graph construction system performs graph construction, and generating a high hidden danger signal or a low hidden danger signal;
after a high hidden danger signal generated when the power grid dispatching knowledge graph construction system carries out graph construction is obtained, comprehensively analyzing a plurality of hidden danger assessment indexes and hidden danger assessment index reference thresholds which are generated subsequently through a server to generate risk indexes;
And comparing the generated risk index with a preset risk index, generating a risk signal, and sending an early warning prompt to the risk signal.
In the technical scheme, the invention has the technical effects and advantages that:
according to the invention, the accuracy of the grid dispatching knowledge graph construction system in graph construction is evaluated, when the accuracy is abnormal in the graph construction process, an early warning prompt is sent out through the prompt module, and the electric power operators are informed of the possible higher potential safety hazard risks in the process of graph construction through the prompt, so that the electric power dispatching knowledge graph construction system needs to be managed timely and in advance, the situation that the electric power operators cannot find the potential safety risks in the electric power in time is effectively avoided, the electric power dispatching knowledge graph construction system is ensured to construct the knowledge graph efficiently, and the stable and efficient operation of the electric power dispatching knowledge graph construction system is further ensured;
according to the method, when the abnormal hidden danger of accuracy occurs in the process of carrying out the map construction by the power grid dispatching knowledge map construction system, the operation state of the power grid dispatching knowledge map construction system is comprehensively analyzed, the abnormal hidden danger situation of the power grid dispatching knowledge map construction system is judged, the accuracy hidden danger risk of the power grid dispatching knowledge map construction system in the process of carrying out the map construction can be known through the generated risk index, the operation and maintenance manager can know the accuracy hidden danger risk situation of the power grid dispatching knowledge map construction system conveniently, and secondly, when the power grid dispatching knowledge map construction system generates a low risk signal in the process of carrying out the map construction, an early warning prompt is not sent out, so that the potential safety hidden danger of the power grid cannot be found in time by an electric operator in the process of carrying out the map construction by the power grid dispatching knowledge map construction system is small, the accidental tiny abnormal hidden danger can be possibly generated in the process of carrying out the map construction by the power grid dispatching knowledge map construction system, the accuracy in the process of the map construction can not be greatly influenced, the early warning situation caused by accidental abnormality is eliminated in the mode, and the power grid dispatching knowledge map construction system is ensured to be stably and efficiently operated.
Drawings
For a clearer description of embodiments of the present application or of the solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments described in the present invention, and that other drawings may be obtained according to these drawings for a person skilled in the art.
Fig. 1 is a schematic diagram of a knowledge graph construction method and system for a power grid dispatching operation situation.
Fig. 2 is a flow chart of a method and system for constructing a knowledge graph for a power grid dispatching operation situation.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art.
The invention provides a knowledge graph construction system for a power grid dispatching operation situation as shown in fig. 1, which comprises a data acquisition module, a server, a hidden danger sensing module, a risk analysis module, a comparison analysis module and a prompt module;
The data acquisition module acquires a plurality of data information, including measurement index information and performance information, when the power grid dispatching knowledge graph construction system performs graph construction, and after acquisition, the measurement index information and the performance information are uploaded to the server after being processed;
the measurement index information during the map construction by the power grid dispatching knowledge map construction system comprises a performance statistical index (F1 value) abnormal change coefficient and an average absolute error difference state hiding coefficient, and after the acquisition, the data acquisition module respectively marks the performance statistical index abnormal change coefficient and the average absolute error difference state hiding coefficient asAnd->；
In a knowledge graph construction system of a power grid dispatching operation situation, F1 value comprehensively considers accuracy (Precision) and Recall rate (Recall) for comprehensively evaluating the performance of a model, in power grid dispatching, anomaly detection is very important for ensuring stable and reliable operation of a power system, F1 value can be used for evaluating the performance of the knowledge graph construction system in anomaly detection, and if an anomaly event can be accurately identified and correlated with information in the knowledge graph, F1 value is helpful for evaluating the capability of the system;
The F1 value of the knowledge graph construction greatly fluctuates in different time periods, which may affect the accuracy of the knowledge graph construction system, so that electric operators cannot timely find potential safety risks in the power grid, because the fluctuation of the F1 value reflects the instability of the system performance, and the following effects and reasons may exist:
unstable data quality: the quality of the grid data may fluctuate in different time periods, including noise, missing data, outliers, etc., which may cause performance differences of the model in different time periods, making the F1 value fluctuate more;
model performance is unstable: classification or prediction models used by the knowledge graph construction system may be sensitive to changes in data, and particularly when data distribution is significantly changed, performance differences of the models in different time periods may cause fluctuation of the F1 value;
timeliness and real-time issues: the power grid dispatching operation situation needs to reflect the state and risk of the power grid timely and accurately, so that power operators can take necessary measures rapidly to maintain the stability of the power grid, if the F1 value fluctuates greatly in different periods, the performance of a model or a system is unstable, accurate information cannot be provided on a real-time or near-real-time basis, and the risk that the power operators cannot find the potential power grid safety risk timely is increased;
Risk missing report and false report: the fluctuation of the F1 value can cause problems of risk missing report and false report, the lower F1 value can cause that a model or a system cannot identify real problems in a power grid, so that the risk is not found, on the other hand, the higher F1 value can increase the risk of false report, so that an electric operator does not face false alarm, the attention of the electric operator to the real problems is reduced, and the real safety risks are difficult to distinguish;
data imbalance: faults or anomalies in the grid are typically relatively few, resulting in an imbalance between the positive and negative categories, when the data is unbalanced, the F1 value may be more susceptible to fluctuations of the small category, since the number of samples of the positive category is smaller;
therefore, the potential problem of abnormal variation of the performance statistical index can be found in time by analyzing the performance statistical index when the power grid dispatching knowledge graph construction system performs graph construction;
the logic for obtaining the abnormal variation coefficient of the performance statistical index is as follows:
s101, acquiring actual performance statistical indexes of different time periods (the time periods in the time period can be all equal or all unequal or a cross form of the time periods and the time periods in the time period are not specifically limited) in the T time when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual performance statistical indexes as follows ，yThe number of the actual performance statistical indexes of different time periods in the T time when the power grid dispatching knowledge graph construction system performs graph construction is represented,y=1、2、3、4、……、q，qis a positive integer;
it should be noted that the number of the substrates,in the formula, the accuracy refers to the proportion of the number of samples correctly predicted as positive category by the model to the number of samples correctly predicted as positive category, the accuracy of the model on the positive category is measured, the recall rate refers to the proportion of the number of samples correctly predicted as positive category by the model to the number of samples in all actual positive category, the coverage degree of the model on the samples of the positive category is measured, when the knowledge graph construction system constructs the knowledge graph, the system has an output result of the model, the output of the model contains the prediction probability or classification label of each sample, and the information can be used for determining which samples are correctly predicted as positive category, so as to determine the actual performance statistical indexes of the power grid dispatching knowledge graph construction system in different time periods when the graph construction is carried out;
s102, acquiring an actual performance statistical index in a T time when carrying out map construction through a power grid dispatching knowledge map construction systemCalculating the standard deviation of the actual performance statistical index and the average value of the actual performance statistical index, and respectively calibrating the standard deviation of the actual performance statistical index and the average value of the actual performance statistical index as +. >And->Then:，/>；
s103, carrying out map construction through a power grid dispatching knowledge map construction system, wherein the actual performance statistical index standard deviation is in T timeAnd the mean value of the actual performance statistics +.>Calculating the actual performance statistical index variation coefficient, wherein the calculated expression is as follows: />；
The actual performance statistical index variation coefficient can be known, the larger the expression value of the actual performance statistical index variation coefficient generated in the T time when the power grid dispatching knowledge graph construction system performs graph construction is, the worse the stability of the actual performance statistical index in different time periods in the T time when the power grid dispatching knowledge graph construction system performs graph construction is shown, and otherwise, the better the stability of the actual performance statistical index in different time periods in the T time is shown when the power grid dispatching knowledge graph construction system performs graph construction;
s104, calculating abnormal variation coefficients of the performance statistical indexes, wherein the calculated expression is as follows:；
the calculation expression of the abnormal variation coefficient of the performance statistical index shows that the larger the expression value of the abnormal variation coefficient of the performance statistical index generated in the time T when the power grid dispatching knowledge graph construction system carries out graph construction is, the lower the accuracy of the graph construction is, the greater the hidden danger that the electric power operators cannot timely find the potential safety risk in the power grid is, and on the contrary, the higher the accuracy of the graph construction is, the smaller the hidden danger that the electric power operators cannot timely find the potential safety risk in the power grid is;
The average absolute error in the knowledge graph construction is used for measuring the average error between the prediction or estimation of the model or the system and the actual observation value;
the accuracy of the power grid dispatching operation situation knowledge graph construction system can be affected due to the fact that the average absolute error of the knowledge graph construction is large, so that potential safety risks in a power grid cannot be found in time by electric operators, and the following detailed answers are given:
data accuracy is compromised: the fact that the average absolute error is large indicates that a large gap exists between data in the knowledge graph and the state of the real power grid, which is possibly caused by reasons of sensor errors, data collection problems, measurement inaccuracy and the like, if the data in the knowledge graph are inaccurate, an electric operator makes a decision based on incorrect information, so that the safety of the power grid is threatened;
misleading information: large average absolute errors may lead to information instability in the knowledge graph, which data is difficult for the power operator to determine, which may lead to misleading information, making it difficult for the power operator to distinguish between real problems and noise, which may distract the power operator, making it difficult for them to identify potential security risks;
Decision uncertainty: if the data constructed by the knowledge graph is inaccurate, the electric operator faces decision uncertainty and cannot determine the real state of the power grid, so that proper measures cannot be taken to cope with potential problems, which may lead to delay of reaction time and worsen the problems;
timeliness: the fact that the average absolute error is larger may mean that the data updating frequency of the knowledge graph is insufficient or not timely, the state of the power grid may change in a short time, and if the knowledge graph cannot accurately reflect the changes, an electric operator cannot know the actual condition of the power grid timely;
therefore, the average absolute error of the grid dispatching knowledge graph construction system during graph construction is analyzed, and the hidden danger problem that the average absolute error is abnormal can be found in time;
the logic for obtaining the average absolute error state hidden coefficient is as follows:
s201, acquiring actual data and a data set of knowledge graph data when a power grid dispatching knowledge graph construction system performs graph construction;
it should be noted that, the actual data may be power grid state data collected from the real world, and the knowledge graph data is a power grid knowledge graph constructed by the system;
S202, acquiring actual data and knowledge graph data of each data point at different moments in T time for each data point when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual data and the knowledge graph data as respectivelyAnd->，xThe actual data of each data point at different moments in the T time and the serial numbers of the knowledge graph data are represented when the power grid dispatching knowledge graph construction system performs graph construction,x=1、2、3、4、……、n，nis a positive integer;
it should be noted that, the actual data and the knowledge graph data when the power grid dispatching knowledge graph construction system performs graph construction should include the same data points so as to perform comparison, that is, the actual data and the corresponding subscripts of the knowledge graph data obtained at the same time are the same;
s203, through knowledge graph dataAnd (3) the actual data->Calculating the absolute error of each data point in the time T, wherein the calculation formula is as follows: />；
S204, establishing a data set by using absolute errors of data points generated in the time T when the grid dispatching knowledge graph construction system performs graph construction, and calibrating the data set asMThen:，kthe number of the data point when the power grid dispatching knowledge graph construction system performs graph construction is represented, k=1、2、3、4、……、m，mIs a positive integer;
s205, calculating an average absolute error difference state concealment coefficient, wherein the calculated expression is as follows:，mthe total number of data points when the power grid dispatching knowledge graph construction system performs graph construction is represented;
the calculation expression of the average absolute error state hidden coefficient can show that the larger the expression value of the average absolute error state hidden coefficient generated in the time T when the power grid dispatching knowledge graph construction system carries out graph construction is, the lower the accuracy of the graph construction is, the larger the hidden danger that potential safety risks in the power grid cannot be found in time by electric operators is, and otherwise, the higher the accuracy of the graph construction is, the smaller the hidden danger that potential safety risks in the power grid cannot be found in time by electric operators is;
the performance information of the power grid dispatching knowledge graph construction system during graph construction comprises response time abnormal hiding coefficients, and after acquisition, the data acquisition module marks the response time abnormal hiding coefficients as；
In the knowledge graph construction system of the power grid dispatching operation situation, the response time length in the construction of the knowledge graph refers to the time required from sending a request (such as a data updating request) to returning a response of the system, and the response time length can be used for measuring the performance and the efficiency of the system;
In the knowledge graph construction system of the power grid dispatching operation situation, the accuracy of the knowledge graph construction and the capability of power operators can be influenced to a certain extent due to the fact that the response time is long during the knowledge graph construction, and particularly in some specific cases, the following is a detailed answer:
delay causes information hysteresis: the high response time length during the construction of the knowledge graph can lead to the hysteresis of information, namely the constructed knowledge graph can not timely reflect the current state of the power grid, in the power grid dispatching, the instant data and the state information are critical to decision making, if the updating speed of the knowledge graph is low, the electric power operators can not timely acquire key information, and thus potential power grid safety risks can not be rapidly identified and responded;
data staleness: the data in the power grid can change rapidly along with time, including power load, power generation, voltage, current and the like, if the response time of the knowledge graph construction is high, the constructed knowledge graph can contain outdated or stale data, which can lead power operators to make decisions based on inaccurate data, and increase the running risk of the power grid;
abnormal condition detection: in a power grid, it is crucial to timely detect and respond to abnormal conditions, and a longer response time period may cause abnormal conditions to be not timely detected and reported, which may affect the perception and processing of power operators on power grid abnormalities, thereby increasing potential safety risks;
Decision support: the power grid dispatching operators need quick and accurate information to support decisions, including power load adjustment, equipment operation and emergency handling, if the response time of the knowledge graph construction is high, the power operators cannot obtain the required decision support in time, and the untimely or improper decisions may be caused;
therefore, the response time length of the power grid dispatching knowledge graph construction system in graph construction is analyzed, and the hidden danger problem that the response time length is abnormal can be timely found;
the logic for response duration anomaly concealment coefficient acquisition is as follows:
s301, acquiring an optimal response time length range when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the optimal response time length range as；
It should be noted that, firstly, the service requirement and the usage scenario of the power grid dispatching need to be known in depth, and cooperate with the power grid power operators and related stakeholders to understand the expected and required functions of the power grid power operators and the related stakeholders, secondly, performance test and load test are important ways of evaluating the response time of the system, and by simulating actual usage conditions, the response time of the system under different loads can be determined, and the test usually involves creating a load scenario, for example, simultaneously querying a plurality of data points or executing complex analysis tasks, and then measuring the response time of the system, so that the optimal response time range of the power grid dispatching knowledge graph construction system in performing graph construction is comprehensively determined in this way, and the optimal response time range of the power grid dispatching knowledge graph construction system in performing graph construction is not limited in detail and can be comprehensively adjusted according to the service requirement and actual usage scenario;
S302, acquiring a plurality of actual response time durations generated in a T time when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual response time durations as，vThe number of the actual response time length generated in the time T when the power grid dispatching knowledge graph construction system performs graph construction is represented,v=1、2、3、4、……、u，uis a positive integer;
it should be noted that, performance monitoring tools are used to monitor performance indexes of the system in real time, including response time, and these tools can provide detailed information about performance, including statistics of response time, and some common performance monitoring tools include Prometheus, grafana, new reli, etc.;
s303, calculating response time abnormal hiding coefficients, wherein the calculated expression is as follows:wherein->Representing +.A.A power grid dispatching knowledge graph construction system acquires a range which is not in the optimal response time length and is not in the optimal response time length in the time of graph construction>Number of actual response time between +.>，/>Is a positive integer>，uThe total number of actual response time lengths acquired in the time T when the power grid dispatching knowledge graph construction system performs graph construction is represented;
the calculation expression of the response time length abnormal hidden coefficient shows that the larger the expression value of the response time length abnormal hidden coefficient generated in the time T when the power grid dispatching knowledge graph construction system carries out graph construction is, the lower the accuracy of the graph construction is, the greater the hidden danger that potential safety risks in the power grid cannot be found in time by electric operators is, and otherwise, the higher the accuracy of the graph construction is, the smaller the hidden danger that potential safety risks in the power grid cannot be found in time by electric operators is;
The server comprehensively analyzes the measurement index information and the performance information which are processed when the power grid dispatching knowledge graph construction system carries out graph construction, generates a hidden danger assessment index, and transmits the hidden danger assessment index to the hidden danger sensing module;
the server obtains the abnormal variation coefficient of the performance statistical indexAverage absolute error state concealment coefficientAnd response duration anomaly concealment coefficient +.>Afterwards, will->、/>And +.>Carrying out formulated analysis to generate hidden danger assessment index +.>The formula according to is: />Wherein->、/>、/>Respectively is the abnormal variation coefficient of the performance statistics index +.>Average absolute error state concealment coefficientAnd response duration anomaly concealment coefficient +.>Is a preset proportionality coefficient of>、/>、/>Are all greater than 0;
the calculation formula shows that the larger the abnormal variation coefficient of the performance statistics index generated in the time T, the larger the average absolute error state hidden coefficient and the larger the response time abnormal hidden coefficient are generated when the power grid dispatching knowledge graph construction system carries out graph construction, namely the larger the performance value of the hidden danger assessment index generated in the time T is, the lower the accuracy of the graph construction is indicated, the greater the hidden danger of the potential safety risk in the power grid cannot be found in time by an electric operator, and the higher the accuracy of the graph construction is indicated, and the smaller the hidden danger of the potential safety risk in the power grid cannot be found in time by the electric operator is indicated;
It should be noted that, the selection of the time T is a time period with a short time, the time in the time period is not limited specifically herein, and can be set according to practical situations, so as to monitor the situation of the power grid dispatching knowledge graph construction system in the time T when the graph construction is performed, and thus monitor the running state situation of the power grid dispatching knowledge graph construction system in different time periods (in the time T) when the graph construction is performed;
the hidden danger sensing module is used for comparing and analyzing hidden danger assessment indexes with a preset hidden danger assessment index reference threshold value when the power grid dispatching knowledge graph construction system carries out graph construction, generating a high hidden danger signal or a low hidden danger signal, and transmitting the signals to the risk analysis module;
the hidden danger sensing module compares and analyzes hidden danger assessment indexes generated when the power grid dispatching knowledge graph construction system carries out graph construction with a preset hidden danger assessment index reference threshold value, and the hidden danger assessment indexes are analyzed as follows:
if the hidden danger assessment index is greater than or equal to the hidden danger assessment index reference threshold, generating a high hidden danger signal through the hidden danger sensing module, and transmitting the signal to the risk analysis module;
If the hidden danger assessment index is smaller than the hidden danger assessment index reference threshold, generating a low hidden danger signal through the hidden danger sensing module, and transmitting the signal to the risk analysis module;
the risk analysis module is used for comprehensively analyzing a plurality of hidden danger assessment indexes and hidden danger assessment index reference thresholds which are generated subsequently through the server after the high hidden danger signals generated when the power grid dispatching knowledge graph construction system performs graph construction are obtained, so as to generate risk indexes, and transmitting the risk indexes to the comparison analysis module;
after the risk analysis module acquires a high hidden danger signal generated when the power grid dispatching knowledge graph construction system carries out graph construction, comprehensively analyzing a plurality of hidden danger assessment indexes and hidden danger assessment index reference thresholds which are generated subsequently through a server to generate a risk indexThe formula according to is: />Wherein->Representing a risk assessment index that is subsequently generated by the server that is greater than or equal to a risk assessment index reference threshold,ba number indicating a hidden trouble evaluation index equal to or greater than a hidden trouble evaluation index reference threshold value which is subsequently generated by the server,b=1、2、3、4、……、s，sis a positive integer;
as can be seen from the calculation expression of the risk index, after the risk analysis module obtains the high hidden danger signal generated when the power grid dispatching knowledge graph construction system performs graph construction, the greater the risk index generated by the hidden danger assessment indexes and the hidden danger assessment index reference threshold value, the greater the hidden danger risk that the accuracy is poor when the power grid dispatching knowledge graph construction system performs graph construction, and otherwise, the smaller the hidden danger risk that the accuracy is poor when the power grid dispatching knowledge graph construction system performs graph construction;
The comparison analysis module is used for comparing the generated risk index with a preset risk index to generate a risk signal, transmitting the signal to the prompt module, and sending out an early warning prompt through the prompt module;
the comparison and analysis module compares the generated risk index with a preset risk index, and the analysis is as follows:
if the risk index is greater than or equal to the risk index reference threshold, a high-risk signal is generated through the comparison analysis module, the signal is transmitted to the prompt module, the prompt module sends an early warning prompt, and the prompt informs power operators that a high potential safety hazard risk possibly exists when the power grid dispatching knowledge graph construction system carries out graph construction, so that the power operators are required to carry out time-to-time operation and maintenance management on the power grid dispatching knowledge graph construction system in advance, the situation that potential safety risks in the power grid cannot be found in time is effectively avoided, the power grid dispatching knowledge graph construction system is guaranteed to construct the knowledge graph efficiently, and the power grid dispatching knowledge graph construction system is guaranteed to operate stably and efficiently;
if the risk index is smaller than the risk index reference threshold, a low-risk signal is generated through the comparison analysis module and is transmitted to the prompt module, and an early warning prompt is not sent through the prompt module, when the situation occurs, the condition shows that potential safety hazards in the power grid cannot be found in time by power operators when the power grid dispatching knowledge graph construction system performs graph construction, and the potential safety hazards are small, so that accidental tiny abnormal hidden hazards possibly occur when the power grid dispatching knowledge graph construction system performs graph construction, and the accuracy in graph construction cannot be greatly influenced;
According to the invention, the accuracy of the grid dispatching knowledge graph construction system in graph construction is evaluated, when the accuracy is abnormal in the graph construction process, an early warning prompt is sent out through the prompt module, and the electric power operators are informed of the possible higher potential safety hazard risks in the process of graph construction through the prompt, so that the electric power dispatching knowledge graph construction system needs to be managed timely and in advance, the situation that the electric power operators cannot find the potential safety risks in the electric power in time is effectively avoided, the electric power dispatching knowledge graph construction system is ensured to construct the knowledge graph efficiently, and the stable and efficient operation of the electric power dispatching knowledge graph construction system is further ensured;
according to the method, when the abnormal hidden danger of accuracy occurs in the process of carrying out the map construction by the power grid dispatching knowledge map construction system, the operation state of the power grid dispatching knowledge map construction system is comprehensively analyzed, the abnormal hidden danger situation of the power grid dispatching knowledge map construction system is judged, the accuracy hidden danger risk of the power grid dispatching knowledge map construction system in the process of carrying out the map construction can be known through the generated risk index, the operation and maintenance manager can know the accuracy hidden danger risk situation of the power grid dispatching knowledge map construction system conveniently, and secondly, when the power grid dispatching knowledge map construction system generates a low risk signal in the process of carrying out the map construction, an early warning prompt is not sent out, so that the potential safety hidden danger of the power grid cannot be found in time by an electric operator in the process of carrying out the map construction by the power grid dispatching knowledge map construction system is small, the accidental tiny abnormal hidden danger can be possibly generated in the process of carrying out the map construction by the power grid dispatching knowledge map construction system, the accuracy in the process of the map construction can not be greatly influenced, the early warning situation caused by accidental abnormality is eliminated in the mode, and the power grid dispatching knowledge map construction system is ensured to be stably and efficiently operated.
The invention provides a knowledge graph construction method for a power grid dispatching operation situation as shown in fig. 2, which comprises the following steps:
collecting multiple data information, including measurement index information and performance information, when the power grid dispatching knowledge graph construction system performs graph construction, and processing the measurement index information and the performance information when the power grid dispatching knowledge graph construction system performs graph construction after collecting the data information;
comprehensively analyzing the processed measurement index information and performance information when the power grid dispatching knowledge graph construction system performs graph construction, and generating hidden danger assessment indexes;
comparing and analyzing the hidden danger assessment index with a preset hidden danger assessment index reference threshold value when the power grid dispatching knowledge graph construction system performs graph construction, and generating a high hidden danger signal or a low hidden danger signal;
after a high hidden danger signal generated when the power grid dispatching knowledge graph construction system carries out graph construction is obtained, comprehensively analyzing a plurality of hidden danger assessment indexes and hidden danger assessment index reference thresholds which are generated subsequently through a server to generate risk indexes;
comparing and analyzing the generated risk index with a preset risk index, generating a risk signal, and sending an early warning prompt to the risk signal;
The knowledge graph construction method for the power grid dispatching operation situation is realized through the knowledge graph construction system for the power grid dispatching operation situation, and the specific method and the flow of the knowledge graph construction method for the power grid dispatching operation situation are detailed in the embodiment of the knowledge graph construction system for the power grid dispatching operation situation, and are not repeated herein.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present application are all or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired or wireless means (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
While certain exemplary embodiments of the present invention have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that modifications may be made to the described embodiments in various different ways without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive of the scope of the invention, which is defined by the appended claims.
Claims (9)
1. The knowledge graph construction system for the power grid dispatching operation situation is characterized by comprising a data acquisition module, a server, a hidden danger sensing module, a risk analysis module, a comparison analysis module and a prompt module;
the data acquisition module acquires a plurality of data information, including measurement index information and performance information, when the power grid dispatching knowledge graph construction system performs graph construction, and after acquisition, the measurement index information and the performance information are uploaded to the server after being processed;
the method comprises the steps that measurement index information during map construction by a power grid dispatching knowledge map construction system comprises a performance statistical index abnormal change coefficient and an average absolute error difference state hiding coefficient, performance information during map construction by the power grid dispatching knowledge map construction system comprises a response time abnormal hiding coefficient, and after collection, a data collection module respectively marks the performance statistical index abnormal change coefficient and the average absolute error difference state hiding coefficient as And->The response time abnormal hiding coefficient is marked as +.>；
The server comprehensively analyzes the measurement index information and the performance information which are processed when the power grid dispatching knowledge graph construction system carries out graph construction, generates a hidden danger assessment index, and transmits the hidden danger assessment index to the hidden danger sensing module;
the hidden danger sensing module is used for comparing and analyzing hidden danger assessment indexes with a preset hidden danger assessment index reference threshold value when the power grid dispatching knowledge graph construction system carries out graph construction, generating a high hidden danger signal or a low hidden danger signal, and transmitting the signals to the risk analysis module;
the risk analysis module is used for comprehensively analyzing a plurality of hidden danger assessment indexes and hidden danger assessment index reference thresholds which are generated subsequently through the server after the high hidden danger signals generated when the power grid dispatching knowledge graph construction system performs graph construction are obtained, so as to generate risk indexes, and transmitting the risk indexes to the comparison analysis module;
the comparison analysis module is used for comparing the generated risk index with a preset risk index to generate a risk signal, transmitting the signal to the prompt module, and sending an early warning prompt through the prompt module.
2. The knowledge graph construction system for power grid dispatching operation situation according to claim 1, wherein the logic for obtaining the abnormal variation coefficient of the performance statistical index is as follows:
s101, acquiring actual performance statistical indexes of different time periods in a T time when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual performance statistical indexes as，yThe number of the actual performance statistical indexes of different time periods in the T time when the power grid dispatching knowledge graph construction system performs graph construction is represented,y=1、2、3、4、……、q，qis a positive integer;
s102, acquiring an actual performance statistical index in a T time when carrying out map construction through a power grid dispatching knowledge map construction systemCalculating the standard deviation of the actual performance statistical index and the average value of the actual performance statistical index, and respectively calibrating the standard deviation of the actual performance statistical index and the average value of the actual performance statistical index as +.>And->Then:，/>；
s103, carrying out map construction through a power grid dispatching knowledge map construction system, wherein the actual performance statistical index standard deviation is in T timeAnd the mean value of the actual performance statistics +.>Calculating the actual performance statistical index variation coefficient, wherein the calculated expression is as follows: />；
S104, calculating abnormal variation coefficients of the performance statistical indexes, wherein the calculated expression is as follows: 。
3. The knowledge graph construction system for power grid dispatching operation situation according to claim 2, wherein the logic for obtaining the average absolute error state concealment coefficient is as follows:
s201, acquiring actual data and a data set of knowledge graph data when a power grid dispatching knowledge graph construction system performs graph construction;
s202, acquiring actual data and knowledge graph data of each data point at different moments in T time for each data point when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual data and the knowledge graph data as respectivelyAnd->，xThe actual data of each data point at different moments in the T time and the serial numbers of the knowledge graph data are represented when the power grid dispatching knowledge graph construction system performs graph construction,x=1、2、3、4、……、n，nis a positive integer;
s203, through knowledge graph dataAnd (3) the actual data->Calculating the absolute error of each data point in the time T, wherein the calculation formula is as follows: />；
S204, establishing a data set by using absolute errors of data points generated in the time T when the grid dispatching knowledge graph construction system performs graph construction, and calibrating the data set asMThen:，kthe number of the data point when the power grid dispatching knowledge graph construction system performs graph construction is represented, k=1、2、3、4、……、m，mIs a positive integer;
s205, calculating an average absolute error difference state concealment coefficient, wherein the calculated expression is as follows:，mand the total number of data points when the grid dispatching knowledge graph construction system performs graph construction is represented.
4. The knowledge graph construction system for power grid dispatching operation situation according to claim 3, wherein the logic for obtaining the response time abnormal hiding coefficient is as follows:
s301, acquiring an optimal response time length range when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the optimal response time length range as；
S302, acquiring a plurality of actual response time durations generated in a T time when the power grid dispatching knowledge graph construction system performs graph construction, and calibrating the actual response time durations as，vThe number of the actual response time length generated in the time T when the power grid dispatching knowledge graph construction system performs graph construction is represented,v=1、2、3、4、……、u，uis a positive integer;
s303, calculating response time abnormal hiding coefficients, wherein the calculated expression is as follows:wherein->Representing +.A.A power grid dispatching knowledge graph construction system acquires a range which is not in the optimal response time length and is not in the optimal response time length in the time of graph construction>Number of actual response time between +.>，/>Is a positive integer >，uAnd the total number of the actual response time lengths acquired in the time T when the power grid dispatching knowledge graph construction system performs graph construction is represented.
5. The knowledge graph construction system for power grid dispatching operation situation according to claim 4, wherein the server obtains abnormal variation coefficient of performance statistics indexMean absolute error state concealment coefficient +.>And response duration anomaly concealment coefficient +.>Afterwards, will->、/>And +.>Carrying out formulated analysis to generate hidden danger assessment index +.>The formula according to is: />Wherein->、/>、Respectively is the abnormal variation coefficient of the performance statistics index +.>Mean absolute error state concealment coefficient +.>And response duration anomaly concealment coefficient +.>Is a preset proportionality coefficient of>、/>、/>Are all greater than 0.
6. The knowledge graph construction system for the power grid dispatching operation situation according to claim 5, wherein the hidden danger sensing module compares a hidden danger evaluation index generated when the power grid dispatching knowledge graph construction system performs graph construction with a preset hidden danger evaluation index reference threshold value for analysis, and the analysis is as follows:
if the hidden danger assessment index is greater than or equal to the hidden danger assessment index reference threshold, generating a high hidden danger signal through the hidden danger sensing module, and transmitting the signal to the risk analysis module;
If the hidden danger assessment index is smaller than the hidden danger assessment index reference threshold, a low hidden danger signal is generated through the hidden danger sensing module, and the signal is transmitted to the risk analysis module.
7. The knowledge graph construction system for power grid dispatching operation situation according to claim 6, wherein after the risk analysis module obtains the high hidden danger signal generated during graph construction by the power grid dispatching knowledge graph construction system, a plurality of hidden danger evaluation indexes and hidden danger evaluation index reference thresholds which are subsequently generated by the server are comprehensively analyzed to generate a risk indexThe formula according to is: />Wherein->Representing a risk assessment index that is subsequently generated by the server that is greater than or equal to a risk assessment index reference threshold,brepresenting the hidden trouble greater than or equal to that generated later by the serverThe evaluation index refers to the number of the hidden danger evaluation index of the threshold value,b=1、2、3、4、……、s，sis a positive integer.
8. The knowledge graph construction system for the power grid dispatching operation situation according to claim 7, wherein the comparison analysis module compares the generated risk index with a preset risk index, and the analysis is as follows:
if the risk index is greater than or equal to the risk index reference threshold, generating a high risk signal through the comparison analysis module, transmitting the signal to the prompt module, and sending out an early warning prompt through the prompt module;
If the risk index is smaller than the risk index reference threshold, a low risk signal is generated through the comparison analysis module, the signal is transmitted to the prompt module, and the early warning prompt is not sent out through the prompt module.
9. The knowledge graph construction method for the power grid dispatching operation situation is realized by the knowledge graph construction system for the power grid dispatching operation situation according to any one of claims 1 to 8, and is characterized by comprising the following steps:
collecting multiple data information, including measurement index information and performance information, when the power grid dispatching knowledge graph construction system performs graph construction, and processing the measurement index information and the performance information when the power grid dispatching knowledge graph construction system performs graph construction after collecting the data information;
comprehensively analyzing the processed measurement index information and performance information when the power grid dispatching knowledge graph construction system performs graph construction, and generating hidden danger assessment indexes;
comparing and analyzing the hidden danger assessment index with a preset hidden danger assessment index reference threshold value when the power grid dispatching knowledge graph construction system performs graph construction, and generating a high hidden danger signal or a low hidden danger signal;
after a high hidden danger signal generated when the power grid dispatching knowledge graph construction system carries out graph construction is obtained, comprehensively analyzing a plurality of hidden danger assessment indexes and hidden danger assessment index reference thresholds which are generated subsequently through a server to generate risk indexes;
And comparing the generated risk index with a preset risk index, generating a risk signal, and sending an early warning prompt to the risk signal.
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