CN115907542A - Substation secondary equipment digital evaluation method and system based on knowledge graph - Google Patents
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Abstract
A transformer substation secondary equipment digital evaluation method and system based on a knowledge graph comprises the steps of obtaining historical operation state data of transformer substation secondary equipment, and establishing a transformer substation secondary system state evaluation index set; acquiring operation data of secondary equipment of the transformer substation, and constructing a digital evaluation knowledge graph of the state of the secondary equipment of the transformer substation; and establishing a transformer substation secondary equipment state evaluation model by using a gray clustering method and an analytic hierarchy process according to the established power station secondary equipment state digital evaluation knowledge graph and the transformer substation secondary system state evaluation index set, and evaluating the operation state of the transformer substation secondary equipment according to the model value calculated by the transformer substation secondary equipment state evaluation model. The operation state of the secondary equipment of the transformer substation is evaluated according to the calculated value of the model, the operation quality of the secondary equipment of the transformer substation is evaluated according to the calculated value, the result is accurate and comprehensive, and a good reference basis is made for the maintenance of the equipment.
Description
Technical Field
The invention belongs to the technical field of urban power grid data analysis, and particularly relates to a transformer substation secondary equipment digital evaluation method and system based on a knowledge graph.
Background
For a long time, in the aspect of the state evaluation of the secondary equipment of the transformer substation, the traditional working method is low in efficiency, large in workload, short of comprehensive analysis of the state of the equipment, a standardized evaluation system is not formed, a normalized auxiliary tool is short, data and management information are transmitted mainly by means of telephones, paper, e-mails and the like, the state of the equipment is evaluated and the equipment maintenance is guided by means of an artificial statistical method too much, data acquisition is not standard, the difficulty of data arrangement and statistics is high, the problems that information transmission is not timely, the data utilization rate is low, the evaluation quality is uneven, the problem closed-loop effect is poor, expert experience cannot be shared in real time and the like exist, so that how to carry out the digitalized technical research on the state evaluation of the secondary equipment of the transformer substation is achieved, the closed-loop control capability of the whole process is improved, and the digitalized means for the state evaluation of the secondary equipment of the transformer substation is provided.
The overhaul of the secondary equipment of the transformer substation in China still takes periodic overhaul as the main part at present, and the state overhaul is assisted. Although the concept of condition maintenance was proposed earlier in the 80 s of the last century, the comprehensive automatic substation with good communication performance is gradually popularized, constructed and applied only after 2000 years, and the basic condition of condition maintenance is not provided in the early stage. Along with the construction of the intelligent transformer substation, research related to the digital state evaluation of the secondary equipment of the transformer substation is gradually and deeply developed.
Aiming at the problems that equipment failure mechanisms of secondary systems of intelligent substations are complex, uncertain and difficult to evaluate effectively, the conventional literature establishes an offline comprehensive evaluation method of the secondary systems by combining offline and online comprehensive information through a statistical model based on expert experience scoring and a mathematical model based on membership function calculation, and the method comprises the general steps of equipment state analysis, state factor extraction, state index establishment, state index membership degree matrix establishment, state index weight calculation, comprehensive evaluation model establishment and comprehensive state evaluation result calculation. However, due to different influence degrees of the state factors on the equipment, fuzzy state grading, different experience of experts, and the like, the state evaluation result obtained usually can only judge the state of the equipment and the state change trend thereof.
Although the research on the state evaluation method is relatively deep at home and abroad at present, the reference documents and achievements for performing state evaluation on the intelligent substation secondary system aiming at the characteristics of complexity, bulkiness and incompleteness of data information are few, on one hand, the offline state evaluation is standardized by no unified and sound standard in the industry, and on the other hand, the technology for performing online state diagnosis on equipment is difficult to realize due to the problem of state information acquisition.
In summary, the prior art mainly has the following defects;
1. most of the devices are limited to monitoring the state of the secondary equipment of the transformer substation, or on-line state evaluation of the secondary equipment of the transformer substation cannot be realized depending on historical data of the equipment;
2. a single device or loop is typically of interest, not being associated with the entire substation secondary equipment system;
3. the number of sensors installed in the protection equipment is limited, the secondary equipment state information which can be directly acquired is few, and sufficient data support is difficult to provide for state maintenance.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a transformer substation secondary equipment digital evaluation method and system based on a knowledge graph, which can comprehensively and accurately evaluate the operation state of the secondary equipment of a transformer substation through the numerical value calculated by a model.
In order to achieve the above purpose, the invention provides the following technical scheme:
a transformer substation secondary equipment digital evaluation method based on a knowledge graph comprises the following steps of;
acquiring historical operating state data of secondary equipment of the transformer substation, and establishing a state evaluation index set of a secondary system of the transformer substation;
acquiring operation data of secondary equipment of the transformer substation, and constructing a digital evaluation knowledge graph of the state of the secondary equipment of the transformer substation;
and establishing a transformer substation secondary equipment state evaluation model by using a gray clustering method and an analytic hierarchy process according to the established power station secondary equipment state digital evaluation knowledge graph and the transformer substation secondary system state evaluation index set, and evaluating the operation state of the transformer substation secondary equipment according to the model value calculated by the transformer substation secondary equipment state evaluation model.
Further, the historical operating state data of the equipment comprises operating temperature data of the secondary equipment, secondary circuit insulation data and differential flow data of the secondary equipment.
Further, the secondary equipment operation data includes pre-commissioning state quantity data, modified state quantity data, detection state quantity data, failure risk state quantity data, and reliability state quantity data of the secondary equipment.
Further, the state evaluation model of the secondary equipment of the transformer substation is F = (I × A) 1 ×M×A 2 ×P×A 3 ) X Q, wherein,
f is the secondary device body and the secondary loop evaluation value; i is a secondary equipment detection type state quantity; a. The 1 Is a first weighting factor; m is the reliability state quantity of the secondary equipment; a. The 2 Is a second weighting factor; p, secondary equipment failure risk state quantity; a. The 3 Is a third weightA factor; q is a secondary equipment improved state quantity.
Further, a first weighting factor A 1 And a third weighting factor A 3 Is 0.4.
Further, a second weighting factor A 2 Is 0.2.
Further, the state of the substation secondary equipment includes four levels of normal, attentive, abnormal and severe, wherein,
when the value calculated by the model is 86-100, the state of the secondary equipment of the transformer station is normal;
when the value calculated by the model is 71-85, the state of the secondary equipment of the transformer station is noticed;
when the value calculated by the model is 61-70, the state of the secondary equipment of the transformer station is abnormal;
and when the value calculated by the model is below 60, the state of the secondary equipment of the power station is serious.
Further, when the state of the secondary equipment of the transformer substation is calculated, and the historical operating state data of the secondary equipment of the transformer substation and the data in the operating data of the secondary equipment of the transformer substation have no corresponding state quantity, the corresponding state quantity does not participate in the calculation.
A digital evaluation system for secondary equipment of a transformer substation of a knowledge graph comprises
The state evaluation index set acquisition module is used for acquiring historical operation state data of the secondary equipment of the transformer substation and establishing a state evaluation index set of a secondary system of the transformer substation;
the digital evaluation knowledge map building module is used for obtaining the operation data of the secondary equipment of the transformer substation and building a digital evaluation knowledge map of the state of the secondary equipment of the transformer substation;
and the operation state evaluation module of the secondary equipment of the transformer substation is used for establishing a state evaluation model of the secondary equipment of the transformer substation by using a gray clustering method and an analytic hierarchy process according to the established state digital evaluation knowledge map of the secondary equipment of the power station and the state evaluation index set of the secondary system of the transformer substation, and evaluating the operation state of the secondary equipment of the transformer substation according to the value of the model value calculated by the state evaluation model of the secondary equipment of the transformer substation.
Compared with the prior art, the invention has the advantages that:
the invention relates to a substation secondary equipment digital evaluation method and a substation secondary equipment digital evaluation system based on a knowledge graph, wherein a unified secondary system state evaluation index set is established through analysis of structural features and functional effects of substation secondary system equipment, a substation secondary equipment state digital evaluation knowledge graph is established, a secondary system layered comprehensive state evaluation model is established by combining state evaluation methods such as a fuzzy comprehensive evaluation method, a gray clustering method and a hierarchical analysis method, then a relay protection measurement loop state diagnosis model is established through a hidden fault diagnosis method, the operation state of the substation secondary equipment is evaluated through the size of a calculated value of the model, the operation quality of the substation secondary equipment is evaluated through the calculated value, the result is accurate and comprehensive, and a good reference basis is made for equipment maintenance.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
In the drawings:
FIG. 1 is a knowledge graph-based substation secondary equipment digital evaluation method substation secondary equipment state evaluation knowledge graph research technology route diagram;
FIG. 2 is a node type and relationship diagram between key feature attributes and key feature attributes of a substation secondary equipment state according to the knowledge graph-based substation secondary equipment digital evaluation method;
FIG. 3 is a knowledge graph visualization flow chart of the digital evaluation method of the secondary equipment of the transformer substation based on the knowledge graph;
FIG. 4 is a diagram of a transformer substation secondary equipment state index evaluation process of a transformer substation secondary equipment digital evaluation method based on a knowledge graph of the invention;
FIG. 5 is a transformer substation secondary equipment knowledge base design flow chart of the transformer substation secondary equipment digital evaluation method based on knowledge graphs of the invention;
FIG. 6 is a transformer substation secondary equipment state digital evaluation flow chart of the transformer substation secondary equipment digital evaluation method based on the knowledge graph of the invention;
FIG. 7 is a technical route diagram of a substation secondary equipment state digital evaluation system developed by the substation secondary equipment digital evaluation method based on the knowledge graph of the invention;
FIG. 8 is a diagram of a digital evaluation system for the state of a secondary device of a transformer substation according to the digital evaluation method for a secondary device of a transformer substation based on a knowledge graph;
FIG. 9 is a topological diagram of a digital evaluation hardware system for the state of secondary equipment of a transformer substation based on a digital evaluation method for the secondary equipment of the transformer substation of the knowledge graph;
FIG. 10 is a functional architecture diagram of a substation secondary equipment state digital evaluation software system according to a knowledge-graph-based substation secondary equipment digital evaluation method of the present invention;
FIG. 11 is a functional module diagram of a substation secondary equipment state digital evaluation software website system according to a knowledge graph-based substation secondary equipment digital evaluation method;
fig. 12 is a home page view of a substation secondary equipment state digital evaluation software system based on a knowledge graph and the substation secondary equipment digital evaluation method of the invention.
Fig. 13 is a schematic flow diagram of a transformer substation secondary equipment digital evaluation method based on a knowledge graph.
Detailed Description
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings. It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The following detailed description is exemplary in nature and is intended to provide further explanation of the invention as claimed. Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention.
Example 1
A transformer substation secondary equipment digital evaluation method based on knowledge graph is shown in figure 13 and comprises the steps of
Acquiring historical operation state data of secondary equipment of the transformer substation, and establishing a state evaluation index set of a secondary system of the transformer substation;
acquiring operation data of secondary equipment of the transformer substation, and constructing a digital evaluation knowledge graph of the state of the secondary equipment of the transformer substation;
and establishing a transformer substation secondary equipment state evaluation model by using a gray clustering method and an analytic hierarchy process according to the established power station secondary equipment state digital evaluation knowledge graph and the transformer substation secondary system state evaluation index set, and evaluating the operation state of the transformer substation secondary equipment according to the model value calculated by the transformer substation secondary equipment state evaluation model.
Specifically, the equipment historical operating state data includes operating temperature data of the secondary equipment, secondary circuit insulation data and secondary equipment differential flow data.
Specifically, the secondary equipment operation data includes pre-commissioning secondary equipment state quantity data, modified state quantity data, detection type state quantity data, failure risk state quantity data, and reliability state quantity data.
Specifically, the transformer substation secondary equipment state evaluation knowledge graph is used for carrying out on-site investigation and data collection by taking a relay protection and automation device as an object and researching disposal measures of transformer substation secondary equipment state evaluation guide rules and historical defect faults in order to realize the evaluation of a transformer substation secondary equipment digital system; the method comprises the steps of researching and establishing a transformer substation secondary equipment state evaluation index system, establishing a grading model of each index according to the secondary equipment state evaluation index system, and then establishing an intelligent transformer substation secondary equipment state evaluation model on the basis of an intelligent transformer substation secondary equipment weight model. The method combines an evaluation model and a problem suggestion measure to construct a relay protection and automatic professional state evaluation knowledge map. The technical route is shown in fig. 1, and mainly comprises:
evaluation index system construction
The method scientifically and reasonably selects the state evaluation indexes of the secondary equipment of the transformer substation and establishes a corresponding index system, and is the basis for guaranteeing the reasonability and scientificity of the state evaluation of the secondary equipment. However, since the secondary equipment of the intelligent substation is complex and the factors affecting the operation state of the secondary equipment are many, it is difficult to take all the factors into consideration. Therefore, the mutual relationship of the influence factors of the secondary equipment of the transformer substation needs to be analyzed.
Secondary device status classification
The intelligent substation has the advantages that the types of secondary equipment are more, the state information of the equipment is complex, the data size is huge, and the performance influence factors in different aspects and different levels are many, so that the performance quality condition of the secondary equipment of the intelligent substation is reflected to different degrees. The state evaluation of the secondary equipment of the transformer substation takes the current regulation standard, the operation maintenance experience, the technical indexes of equipment manufacturers and the like as criteria, and the state of the equipment is quantitatively graded according to the comprehensive state information such as the actual operation condition of the equipment, various state detection data, sampling data, defect and abnormal information and the like, so that the real state of the evaluation equipment is judged and generally divided into three types: a normal state, an attentive state, and an abnormal state.
Quantitative analysis of secondary equipment state evaluation index
The secondary equipment of the transformer substation is divided into relay protection equipment, a secondary circuit, safety equipment, automation equipment, direct-current power supply equipment and communication network equipment. The evaluation of the relay protection device follows an objective and unified principle, the influence of human factors on an evaluation result is avoided, and the comprehensiveness, objectivity, accuracy and timeliness of evaluation data are ensured. The secondary equipment state of the transformer substation is influenced by hardware factors, software factors and human factors, and state information data corresponding to the factors are large and complex. Because the state maintenance work starting time of the secondary equipment of the transformer substation is late and is still in a searching stage, the current monitoring means and technology are not perfect enough, and a unified standard does not exist yet. In order to enable the state evaluation indexes to comprehensively and truly reflect the operation state of the secondary equipment of the transformer substation, the selection of the state evaluation indexes must follow the principle of combining scientificity, comprehensiveness, feasibility, safety, systematicness and hierarchy, so that on the basis of the state evaluation experience of the primary equipment, the practical situation and characteristics of the secondary equipment of the transformer substation are combined, the opinions and suggestions of multiple experts are referred to, and the following six aspects are summarized as the state evaluation indexes of the secondary equipment of the transformer substation:
state quantity before commissioning: the condition before commissioning directly determines the operation level of the substation secondary equipment in the future, and the method mainly comprises the aspects of design of construction drawings, relative quality of equipment, construction installation, commissioning acceptance and the like.
Improved state quantity: the improved state quantity of the secondary equipment of the transformer substation refers to the state quantity which is reduced in equipment performance and can be restored to a normal level after improvement and completion, and comprises accidental defects, familial defects and countermeasures.
Detection type state quantity: the substation secondary equipment detection type state quantity refers to state quantity representing equipment operation environment and operation conditions, and the state quantity can be obtained through direct observation, instrument detection or device self-detection.
Failure risk state quantity: the transformer substation secondary equipment failure risk state quantity refers to the state quantity representing the failure occurrence probability of the equipment after long-time operation. Without effective verification, the risk factor of failure of the equipment decreases after long-term operation. When the failure risk factor is reduced to a certain degree, the parts or the whole of the secondary equipment of the transformer substation need to be verified so as to improve the reliability of the secondary equipment.
Reliability state quantity: the reliability state quantity refers to the state quantity which represents the reliability of a certain type of equipment and the reliability of an individual of a manufacturer, and comprises an aging rate, a failure rate and the like. A low reliability factor score may indicate poor overall reliability of the device, or the presence of a degraded component, indicating that the device or a component thereof needs to be replaced.
Other factors: the operation period of the secondary equipment of the transformer substation is generally 10-12 years, and in addition, the operation state of the equipment can be influenced by manually changing the equipment.
And analyzing and combing the digital evaluation indexes of the state of the secondary equipment of the transformer substation according to the six aspects, and providing a data basis for the construction of the digital evaluation knowledge graph of the state of the secondary equipment of the transformer substation.
Evaluation method
The state evaluation of the secondary equipment of the transformer substation is carried out in a quantitative mode, the specific score is calculated according to the following formula, and the relationship between the score and the state is shown in the following table: f = (I × a) 1 ×M×A 2 ×P×A 3 ) XQ, wherein F is the secondary device body and the secondary loop evaluation value; i is a secondary equipment detection type state quantity; a. The 1 Is a first weighting factor; m is the reliability state quantity of the secondary equipment; a. The 2 Is a second weighting factor; p secondary equipment failure risk state quantity; a. The 3 Is a third weighting factor; q is a secondary equipment improved state quantity.
Preferably, the first weighting factor A 1 And a third weighting factor A 3 Is 0.4.
Preferably, the second weighting factor A 2 Is 0.2.
Specifically, according to the calculation result, the state of the secondary equipment of the substation includes four levels of normal, attention, abnormality, and severity, wherein,
when the value calculated by the model is 86-100, the state of the secondary equipment of the transformer station is normal;
when the value calculated by the model is 71-85, the state of the secondary equipment of the transformer station is noticed;
when the value calculated by the model is 61-70, the state of the secondary equipment of the transformer station is abnormal;
and when the value calculated by the model is below 60, the state of the secondary equipment of the power station is serious.
Specifically, when the state of the secondary equipment of the transformer substation is calculated, and data in the historical operating state data of the secondary equipment of the transformer substation and the CPU operating data of the secondary equipment of the transformer substation have no corresponding state quantity, the corresponding state quantity does not participate in the calculation.
Substation secondary equipment state evaluation knowledge graph construction
And establishing a knowledge graph of the state of the secondary equipment of the transformer substation, and acquiring the related knowledge of the state of the secondary equipment. The method is characterized in that relevant policies, regulations and standards of the power industry such as a relay protection device state evaluation guide, a power equipment preventive test regulation and the like are referred, and research results of a plurality of experts and scholars are referred, so that attributes of the state of the secondary equipment of the transformer substation are collected, and key characteristic quantities of the state of the secondary equipment of the transformer substation are used as key attributes of the state of the equipment.
The transformer substation secondary equipment state evaluation knowledge graph is composed of a mode layer and a data layer. The model layer is the core of the knowledge graph, basic theories, entity concepts, relational logics and the like are displayed, refined knowledge, principles, data and the like are stored, and the purpose is to constrain the data layer entities of the knowledge graph by means of the logics and formulas of the model layer.
Entity identification is a one-to-one set partitioning of a given set of entities and a set of categories. For example, apples correspond to fruits and carrots correspond to vegetables. In short, entity identification can be considered a classification problem. To implement this division, we need to label a word sequence with various characteristics of the entity, such as context characteristics. After the entity attribute of the equipment is determined, relationship reasoning can be carried out on the basis of entity extraction, the extraction of the relationship is converted into a classification problem, and the extraction of the triples is completed. And selecting a semantic network representation method to construct triples such as entity/concept-relation-entity/concept or entity/concept-relation-attribute.
In addition, the relevance between the key characteristic attribute and the non-key characteristic attribute of the state of the secondary equipment of the substation, the relevance relationship between the characteristic attribute and the fault attribute and the like also need to be considered. The node type and relationship graph between the key characteristic attribute and the key characteristic attribute of the substation secondary equipment state is shown in fig. 2.
Entity: a main transformer protection device index, a converter transformer protection device index and a direct current protection device index of 82303082
Characteristic attributes are as follows: CPU (device) temperature, CPU load factor, working voltage, internal crystal oscillator deviation (8230)
And (3) fault attribute: abnormal operation, abnormal temperature and wrong equipment parameters \8230
The relationship is as follows: belong to, contain, strongly correlate, weakly correlate 8230
Graph databases are typical storage manners based on graph structures, and data models of graph databases are mainly embodied by nodes and relations (edges), and support operations such as querying, adding, deleting and updating the graph structures. Compared with the traditional relational database, the query speed is high, the operation is simple, and more abundant relation showing modes can be provided. In order to complete the map architecture of the state of the secondary equipment of the transformer substation, a knowledge map visualization flow chart is shown in fig. 3, firstly, relevant data preparation is performed, secondary equipment ledger data and relevant regulations are utilized, and meanwhile, a secondary equipment state relevant knowledge text is obtained by combining expert experience. And after the data preparation is finished, carrying out entity recognition on the acquired knowledge by extracting the entities in the text. The relationships between the matching entities are then analyzed by relevance. And finally obtaining all the entities and the relations.
State digitization custom construction and storage method
On the basis of state evaluation indexes of substation secondary equipment, unified evaluation content, an evaluation method, an evaluation process and a grading standard of secondary equipment state evaluation are researched and constructed on the basis of fully combing the existing working system, the existing evaluation standard and the existing implementation detailed rule, a relay protection and automation equipment state evaluation process automation technology is researched and constructed, a state evaluation standard database, an evaluation record database and a hidden danger problem database which can be customized and expanded are formed, problem grading is carried out on the basis of data analysis, a typical case expert knowledge base is built, experience feedback is realized, an informatization, knowledgeable and typical hidden danger problem common fault database is constructed, a universal secondary equipment problem analysis and processing model is researched and provided, and the process, standardization and normalization of the basis of state evaluation work are supported.
Automatic analysis of state evaluation index
The method comprises the steps of performing correlation analysis on monitoring data of the secondary equipment of the transformer substation, analyzing correlation characteristic quantities of a plurality of monitoring points based on special characteristic analysis of a single monitoring point, constructing a state evaluation model of the secondary equipment of the transformer substation, formulating working condition evaluation standards and state prediction standards of the secondary equipment, specifying running conditions of the equipment and evaluation standards of the equipment by researching state evaluation of the secondary equipment, performing analysis and evaluation on data of each index item reflecting the state of the secondary equipment, and finally obtaining overall state grades of the equipment, namely four grades of normal, attention, abnormity and severity. After a relevant service auditing process, a secondary equipment state evaluation report is formed to guide the development of equipment maintenance work; and provides decision basis for equipment maintenance fault prediction. The evaluation process diagram of the substation secondary equipment state index is shown in fig. 4.
Knowledge base construction
And (4) grading problems on the basis of data analysis, establishing a typical case knowledge base, realizing experience feedback, and constructing an informatization, knowledge and typical hidden danger problem common-fault database. The organization of knowledge base content depends on the logical representation of the knowledge. To some extent, different knowledge representation methods should require different organizational forms of the knowledge base. The knowledge base of the system is organized and constructed by using the composition method of the fact table and the rule table, and a transformer substation secondary equipment knowledge base design flow chart shown in fig. 5 can be obtained.
The knowledge graph technology mainly comprises seven aspects of knowledge acquisition, knowledge representation, knowledge storage, knowledge fusion, knowledge modeling, knowledge understanding, knowledge operation and maintenance and the like, and provides support for applications in different fields.
Acquiring knowledge: knowledge is generally derived from structured, semi-structured, or unstructured data resources, and computer-understandable and computable structured data is extracted from these various structures and types of data by knowledge extraction techniques for further analysis and utilization. Such as policy standards related to power industry, such as "state evaluation guide of relay protection device" and "preventive test regulations of power equipment", and information such as basic parameters, operation data, defect data, and evaluation reports of equipment, which are acquired on site in real time.
Establishing a fault tree: identifying the state of secondary equipment according to various monitoring data and other diagnostic information such as tests and examinations, analyzing and diagnosing common faults, giving fault reasons and fault positions, predicting fault development trends, proposing suggested measures for fault treatment, and taking effective measures in time to achieve the purpose of preventing the faults in the bud; on the basis of ensuring the safe operation of secondary equipment, reasonable maintenance is carried out.
For the fault with a definite analysis and diagnosis model, the system adopts a fault tree-based fault diagnosis method, a model base of fault characteristics is established → a fault tree model is established → a knowledge base of a fault processing method is established, the holographic data is combined to analyze and diagnose the fault, a healthy sample is formed by excavating parameter intervals when the equipment normally operates through big data, and intelligent diagnosis of the equipment fault is realized when the parameters deviate from the normal operation intervals, and sudden change or long-time one-way change occurs. After fault intelligent diagnosis and manual confirmation, a fault sample can be generated to form a fault tree, so that subsequent fault diagnosis is facilitated, and the fault tree is automatically benchmarked.
Knowledge representation: the knowledge representation is a data structure for converting knowledge existing in the real world into contents recognizable and processable by a computer and describing the knowledge.
And (3) knowledge fusion: the knowledge fusion refers to a process of fusing information such as basic parameters, operation data, defect data and evaluation reports of various transformer substation secondary devices from different sources.
And (3) knowledge storage: the knowledge storage is to design a bottom storage mode according to a knowledge representation form of a knowledge map so as to complete storage of various kinds of substation secondary equipment knowledge acquired in different ways and realize management and calculation of large-scale data.
Knowledge modeling: knowledge modeling refers to the step of expressing and establishing a data model of a substation secondary equipment state evaluation knowledge graph in a manual modeling mode or a semi-automatic modeling mode.
Finally, a complete substation secondary equipment typical expert knowledge base is formed, and the knowledge base can be subsequently expanded, modified, maintained and the like.
Problem analysis processing model construction
Providing a general secondary equipment problem analysis and processing model according to a secondary equipment state grading result, determining subsequent auxiliary maintenance decision-making work content of the fault equipment, and supporting the flow, standardization and normalization of a state evaluation work basis, wherein the flow, standardization and normalization are shown in the following table;
the digital evaluation system for the state of the secondary equipment of the transformer substation aims at different state quantities, and a detection type state quantity grading table of the digital evaluation system is shown as the following table and is a detection type state quantity grading table of a conventional transformer substation
Intelligent substation state scoring table
The general transformer substation detection type state quantity comprehensive grading method is characterized in that the grading of any one state quantity of the device body, the secondary circuit and the auxiliary device is less than 60% of the full value of the corresponding state quantity, and the total grading value of the detection type state quantity of the corresponding evaluation unit is obtained; otherwise, the average value of the total score of the device body and the total score of the secondary circuit and the auxiliary device is taken.
Specifically, the establishment of the substation secondary system state evaluation index set refers to the summary and classification of historical operating state data of the substation secondary equipment, namely historical paper data in the two tables, into electronic data, and the summarized electronic data can realize functions of retrieval, classification, screening and the like.
The method for constructing the transformer substation secondary equipment state digital evaluation knowledge graph is to make the acquired data into a visual graph through echarts.
The comprehensive grading method for the detection type state quantities of the intelligent substation is characterized in that the grading value of any state quantity of the device body, the secondary circuit, the auxiliary device, the merging unit, the intelligent terminal and the process layer switch is less than 60% of the full value of the corresponding state quantity, and then the total grading value of the detection type state quantities of the corresponding evaluation unit is obtained; otherwise, the average value of the total scores of the device body, the secondary circuit, the merging unit, the intelligent terminal and the process layer switch is taken.
The index item of the defect or the index item of the state quantity which is seriously reduced due to the defect is not eliminated except the index calculation of the project, and the index item is also added into an improved state quantity evaluation link.
When part of evaluation objects do not have corresponding state quantity, the state quantity does not participate in evaluation, and other state quantity scores X i Converting the total score of the state quantities of the object into 100 points according to a proportion, and particularly converting the method into a formula;
x i the score of the state quantity after the conversion is carried out; x' i The score of the state quantity when no conversion is performed is obtained.
Transformer substation secondary equipment state digital evaluation process
The digitalized evaluation process of the state of the secondary equipment of the transformer substation is divided into two parts, namely a manager module and an executive module. The manager module realizes formulation, audit and release of evaluation tasks; the executive module realizes the evaluation work of tasks, and a digital evaluation flow chart of the state of the secondary equipment of the transformer substation is shown in fig. 6. Task formulation: when a manager (a task chief responsible person) determines an evaluation task, the manager selects a power station to be evaluated, devices (a device body, a secondary circuit and auxiliary device, a merging unit, an intelligent terminal and a process layer switch) to be evaluated, specifies a time period for completing the evaluation task, and selects a responsible person and an executive person of the evaluation task; and (4) approval: after the task is formulated, a project auditor audits the task list; and (3) task release: issuing the task after confirming that the formulated task list is correct; and (3) query task: after the tasks are released, the executive personnel can inquire tasks to be dealt with at the mobile terminal and the website terminal; and (3) task downloading: the executive personnel downloads the inquired tasks to be dealt with at the mobile terminal and the website terminal; and (3) task execution: the executive personnel evaluates the state of the device according to the downloaded evaluation task list; and (4) evaluation report: after the evaluation work is finished, the executive personnel uploads the evaluation result to the mobile terminal and the website terminal; reporting and auditing: the project responsible person audits the uploaded evaluation report, and issues the evaluation result after confirming that the evaluation result is correct; problem tracking: and after the auditing is finished, the power station personnel track defect problems and risk items found in the evaluating process according to the evaluating result.
Development of digital evaluation system for state of secondary equipment of transformer substation
On the basis of a transformer substation secondary equipment state evaluation model and an evaluation business process, a transformer substation secondary equipment state digital evaluation system is designed and developed by using a computer information technology, and then a test point application is carried out. The method is used for researching the construction implementation scheme of the integrated, visual and intelligent substation secondary equipment state digital evaluation system based on the 'big cloud object movement' technology, researching standard dynamic management, field evaluation and conversion of a problem analysis model and a platform application component, and completing platform architecture function design and development application. Through the research, the intelligent decision and informatization management and control of the state evaluation management and analysis service of the secondary equipment of the transformer substation are realized, the working efficiency and the benefit are improved, and the technical support is further provided for the efficient, stable and reliable operation of the secondary equipment of the transformer substation. In order to construct a digital evaluation system for the state of the secondary equipment of the transformer substation, realize an integrated design concept of intelligence, high efficiency and safety and ensure that the digital evaluation system has good requirements on expansibility, reliability, openness, economy and practicability, a technical route diagram for developing the digital evaluation system for the state of the secondary equipment of the transformer substation is adopted on the basis of fully investigating the service flow of the digital evaluation system for the state of the secondary equipment of the transformer substation and is shown in figure 7. The method comprises the steps of building a multi-technology fusion and support substation secondary equipment state digital evaluation system based on a substation secondary equipment state evaluation knowledge graph and a substation secondary equipment state evaluation digital custom building and storing method, achieving intelligent management of substation secondary equipment state evaluation and selecting a typical application scene to develop test point application.
System components
The transformer substation secondary equipment state digital evaluation system consists of an upper computer system and a lower computer system, and the system is structured as follows:
lower computer system
The lower computer system collects real-time data of the secondary equipment of the transformer substation in a data collection mode, the lower computer data collection box is used as core equipment for data collection, a modular structure is adopted, multiple fault-tolerant and anti-interference technologies are achieved, and advanced hardware design and manufacturing processes are adopted. The intelligent data acquisition system comprises various data sensors, data acquisition boxes, an industrial all-in-one machine and lower computer software, wherein each module in the intelligent data acquisition box can work independently, and the fault of one channel or one module cannot influence the normal work of other channels or other modules. The device has the characteristics of convenience in installation, maintenance and replacement and good reliability.
Upper computer system
The upper computer comprises an upper computer server and digital evaluation software: the method can meet the requirements of query processing management and online evaluation of large-scale data. The Database interface adopts an ODBC (Open Database Connectivity) interface, and has good expansibility and compatibility. Meanwhile, the digital evaluation software is an application program which not only has the functions of evaluating data display, reading and storing, data analysis, document management, safety evaluation and the like, but also has high-level functions of fault diagnosis and the like. The architecture diagram of the substation secondary equipment state digital evaluation system is shown in fig. 8.
System hardware platform
The digital evaluation system for the state of the secondary equipment of the transformer substation mainly comprises an upper computer system and a lower computer system, wherein a data acquisition box serving as data acquisition core equipment in the lower computer system is arranged near the secondary equipment of the transformer substation; the acquisition box acquires state parameters of the corresponding substation secondary equipment measuring point sensor and transmits the state parameters to a server of an upper computer system, and relevant monitoring data and historical data can be checked at a terminal through an algorithm model of the upper computer server. The topological diagram of the digital evaluation hardware system for the state of the secondary equipment of the transformer substation is shown in fig. 9.
System software platform
The digital substation secondary equipment state evaluation software system is composed of a mobile terminal and a website terminal, wherein the data at the bottommost layer are stored in a classified mode, visual application services are provided for the mobile terminal and the website terminal through data processing, and standardized and intelligent substation secondary equipment state evaluation is finally achieved through cooperation of the site and the website terminal. The functional architecture diagram of the digital evaluation software system of the state of the secondary equipment of the transformer substation is shown in fig. 10; fig. 11 shows a functional block diagram of a website system of the digital evaluation software for the state of the secondary equipment of the transformer substation. The system mainly comprises 9 functional modules which are respectively project management, task management, report management, problem management, statistical analysis, evaluation criteria, data management, basic information and system management. The home page displays tables and curves after partial statistical analysis, managers can see all information of evaluation contents, and task executors can intelligently see relevant information participating in evaluation tasks.
System function
The system home page shows the state evaluation problem rectification situation data and the task list to be handled, the rectification summary of each company and each power station is shown, the overall rectification situation is shown by using a histogram, and the digital evaluation software system home page map of the state of the secondary equipment of the transformer substation is shown in fig. 12. The method specifically comprises the following steps:
project management: the project management module mainly comprises four functional modules, namely a new project, an edited project, project issuing and project inquiring, and the functional modules can sequentially realize operations of adding, editing, issuing, inquiring and the like on the project. The newly-built project can be used for realizing basic operation management of the project; editing the project, and only allowing the project in a state to be issued (the project is not issued) to be edited; the project issuing module is used for issuing the established project by a general responsible person, selecting a state project to be issued on a project issuing list interface, after the project issuing operation of the project is successfully issued, the project state is changed into an issued state, a corresponding unit can automatically receive an evaluation project, and an evaluation group leader is a responsible person of the evaluation project; the item query module can check all relevant detailed information and operation records of the items, the item list is arranged according to time, and the list page has a condition query function.
Task management: the task management module comprises three modules of task allocation, task auditing and task issuing. The task allocation module is used for task allocation and task executive personnel allocation of the received evaluation items by task responsible personnel; the task auditing module is used for auditing and confirming the received evaluation task and the modified evaluation task; the task issuing module is used for the task responsible person to issue the checked and correct project to the task executive person, and the corresponding executive person can check the task to be handled.
Report management: this functional module includes report queries and report audits. The report query module is used for checking an initial report after a certain evaluation task is completed, task executors can download and check the initial report, and meanwhile, if the report is found to be wrong, the initial report can be modified and regenerated; the report auditing module is used for downloading and checking the formal report by managers, and can re-upload the formal report if the auditing is wrong.
Problem management: the problem management module mainly comprises four modules of problem reporting, problem auditing, problem tracking and problem counting. The problem filling is that task executive personnel fills the problems found in the evaluation process into the system; the problem auditing module is used for auditing and confirming the problems filled by the task executive personnel by the manager, confirming the problems, subsequently tracking the problems, checking the problem tracking progress in real time and finally summarizing and counting the problems.
Statistical analysis: the statistical analysis module comprises two sub-modules of data analysis and a knowledge graph. The data analysis module can visually display the comparative analysis result of each inspection data. The knowledge graph shows a state evaluation standard index system of the relay protection and automation device in the digital evaluation of the state of the secondary equipment of the transformer substation.
Evaluation criteria: and three submodules are arranged below the evaluation standard module and are respectively used for evaluation guide rules, standard upgrading and formula management. The evaluation guide module mainly realizes the check of each evaluation standard information; the standard upgrading module is used for updating and upgrading the evaluation standard of the new version; the formula management module manages the scoring formula related in the evaluation guide.
Data management: the data management module mainly realizes that the standard contents of the check items of each evaluation device are provided with related data support, and can upload and download related data; the data viewing module is used for viewing the standard related data of the inspection items of each evaluation device.
Basic information: the basic information comprises submodules of company management, power station management, device category, personnel management, job title management, version management, equipment management and the like. The company management module is used for realizing the functional operations of creating, deleting and the like of the main company and the subsidiary companies thereof; the power station management module is used for realizing functional operations such as addition, deletion and the like of a power station under a certain company; the device type module is used for adding and deleting device types; the personnel management module is used for realizing functional operations such as addition, deletion and the like of the digital evaluation personnel of the state of the secondary equipment of the transformer substation; the title management module is used for realizing functional operations such as adding and deleting titles of the user; the version management module is used for realizing functional operations such as addition and modification of the mobile terminal APP version; the equipment management module is used for managing the equipment in the power station.
And (3) system management: the system management comprises menu management, role management, user management and log management. The menu management module is used for enabling a user with the authority of the functional module in the system to perform operations such as adding, modifying and deleting the functions of the main modules. And the role management module realizes the functions of role authority division and role information management. Different roles have different system operation authorities, and only an administrator has the authority to create the roles; the user management module is used for realizing the maintenance of the user information and the management of the corresponding authority, and a system administrator can maintain and modify the user information, forbid the user information which does not need to access the system any more and forbid the login and use of the system. After the user logs in the system, the user can modify the personal information, the password and other information of the user. In order to guarantee the system security and reflect the functions and responsibilities of users with different roles, the user can carry out related operations only after the user establishes an account and logs in an individual account by a super administrator; the menu management function is provided, and a user with the authority of the functional module can add, modify, delete and the like the functions of each main module;
the log management is used for recording the login situation of the user, and recording the login attribute in a form of a table, and the log list comprises a user name, a real name, a login module, detailed information, operation time, a result and a login IP, which is the guarantee of system security. The system provides the information for inquiring the login of a specific user in a screening mode of user name, login module, result, starting time and ending time. The log management interface is shown in the figure. The user can select the result meeting the query condition in the query area of the interface by inputting the conditions of the user name, the login module, the starting time, the ending time, the result and the like, the result is displayed in the lower log list area, and all log information can be exported by one key.
According to the invention, a substation secondary equipment state evaluation system is built by closely combining new-generation information communication technologies such as big data and the Internet of things, a digitalized state evaluation flow is closely combined with the Internet technology, the existing working mode is changed, field real-time data is acquired through a data acquisition system and a mobile intelligent terminal, state evaluation data multidimensional analysis and evaluation problem real-time tracking are carried out, effective sharing of industry specifications is realized, and safety, reliability, accuracy and high efficiency of an equipment state evaluation process are ensured.
Example 2
A transformer substation secondary equipment digital evaluation system based on knowledge graph comprises
The state evaluation index set acquisition module is used for acquiring historical operating state data of the secondary equipment of the transformer substation and establishing a state evaluation index set of a secondary system of the transformer substation;
the digital evaluation knowledge graph establishing module is used for acquiring the operation data of the secondary equipment of the transformer substation and establishing a digital evaluation knowledge graph of the state of the secondary equipment of the transformer substation;
and the operation state evaluation module of the secondary equipment of the transformer substation is used for establishing a state evaluation model of the secondary equipment of the transformer substation by using a gray clustering method and an analytic hierarchy process according to the established state digital evaluation knowledge map of the secondary equipment of the power station and the state evaluation index set of the secondary system of the transformer substation, and evaluating the operation state of the secondary equipment of the transformer substation according to the value of the model value calculated by the state evaluation model of the secondary equipment of the transformer substation.
It will be appreciated by those skilled in the art that the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The embodiments disclosed above are therefore to be considered in all respects as illustrative and not restrictive. All changes which come within the scope of or equivalence to the invention are intended to be embraced therein.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (9)
1. A transformer substation secondary equipment digital evaluation method based on a knowledge graph is characterized by comprising the following steps of;
acquiring historical operation state data of secondary equipment of the transformer substation, and establishing a state evaluation index set of a secondary system of the transformer substation;
acquiring operation data of secondary equipment of the transformer substation, and constructing a digital evaluation knowledge map of the state of the secondary equipment of the transformer substation;
and establishing a transformer substation secondary equipment state evaluation model by using a gray clustering method and an analytic hierarchy process according to the established power station secondary equipment state digital evaluation knowledge graph and the transformer substation secondary system state evaluation index set, and evaluating the operation state of the transformer substation secondary equipment according to the model value calculated by the transformer substation secondary equipment state evaluation model.
2. The substation secondary equipment digital evaluation method based on the knowledge graph of claim 1, wherein the secondary equipment historical operating state data comprises operating temperature data, secondary circuit insulation data and secondary equipment differential flow data of the secondary equipment.
3. The substation secondary equipment digital evaluation method based on the knowledge graph of claim 1, wherein the secondary equipment operation data comprises secondary equipment pre-commissioning state quantity data, improved state quantity data, detection state quantity data, failure risk state quantity data and reliability state quantity data.
4. The method for digitally evaluating substation secondary equipment based on knowledge graph according to claim 1, wherein the substation secondary equipment state evaluation model is F = (ixa) 1 ×M×A 2 ×P×A 3 )×Q；
F is the secondary device body and the secondary loop grading value; i is a secondary equipment detection type state quantity; a. The 1 Is a first weighting factor; m is the reliability state quantity of the secondary equipment; a. The 2 Is a second weighting factor; p secondary equipment failure risk state quantity; a. The 3 Is a third weighting factor; q is a secondary equipment improved state quantity.
5. The knowledge graph-based substation secondary equipment digital evaluation method according to claim 4, characterized in that the first weighting factor A 1 And a third weighting factor A 3 Is 0.4.
6. The knowledge-graph-based substation secondary equipment digital evaluation method according to claim 4, characterized in that the second weighting factor A 2 Is 0.2.
7. The knowledge-graph-based substation secondary equipment digital evaluation method according to claim 1, wherein the states of the substation secondary equipment comprise four levels of normal, attention, abnormal and severe;
when the value calculated by the model is 86-100, the state of the secondary equipment of the transformer station is normal;
when the value calculated by the model is 71-85, the state of the secondary equipment of the transformer station is noticed;
when the value calculated by the model is 61-70, the state of the secondary equipment of the transformer station is abnormal;
when the value of the score calculated by the model is below 60, the state of the secondary equipment of the power station is serious.
8. The substation secondary equipment digital evaluation method based on the knowledge graph of claim 1, wherein when the state of the substation secondary equipment is calculated, and when data in the historical operating state data of the substation secondary equipment and the operating data of the substation secondary equipment has no corresponding state quantity, the corresponding state quantity does not participate in calculation.
9. A transformer substation secondary equipment digital evaluation system based on a knowledge graph is characterized by comprising a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring a data set;
the state evaluation index set acquisition module is used for acquiring historical operating state data of the secondary equipment of the transformer substation and establishing a state evaluation index set of a secondary system of the transformer substation;
the digital evaluation knowledge graph establishing module is used for acquiring the operation data of the secondary equipment of the transformer substation and establishing a digital evaluation knowledge graph of the state of the secondary equipment of the transformer substation;
and the operation state evaluation module of the secondary equipment of the transformer substation is used for establishing a state evaluation model of the secondary equipment of the transformer substation by using a gray clustering method and an analytic hierarchy process according to the established state digital evaluation knowledge map of the secondary equipment of the power station and the state evaluation index set of the secondary system of the transformer substation, and evaluating the operation state of the secondary equipment of the transformer substation according to the value of the model value calculated by the state evaluation model of the secondary equipment of the transformer substation.
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