CN102509178A - Distribution network device status evaluating system - Google Patents
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Abstract
The invention discloses a distribution network device status evaluating system which comprises a device status information acquisition module, a device status information ETL module, an intelligent device status evaluation module, a device status management module, a repair schedule optimization module, a knowledge base module and a dynamic presentation module, wherein the device status information acquisition module uses a monitoring device to obtain various types of status information of a distribution network device; the device status information ETL module screens and processes device status information data to form data which can be used by the device status evaluation module; the intelligent device status evaluation module diagnoses the device status in accordance with the various types of status information of the distribution network device; the device status management module judges whether the distribution device needs to repaired in accordance with the information of the intelligent device status evaluation module; the repair schedule optimization module comprehensively optimizes a repair schedule based on repair time and load transfer paths; and the knowledge base module stores diagnosis algorithm configuration information and diagnosis results of the intelligent device status evaluation module. The distribution network device status evaluating system can provide the optimized device repair schedule, save the device repair cost and resources, and improve the operation and maintenance level and working efficiency of the distribution network system.
Description
Technical field
The present invention relates to a kind of model that is applied to the assessment of distribution net equipment condition intelligent; Based on the various states of power distribution network equipment, the method that adopts expert system to combine with the artificial neural network is analyzed data characteristics; Intelligence Selection diagnosis algorithm and diagnostic mode are diagnosed equipment state; According to the Device Diagnostic result, consider from economy, management etc. are many-sided, in conjunction with genetic algorithm, turnaround plan is carried out complex optimum based on repair time and load transfer path.
Background technology
Fast development along with electrical network; And the user is to the progressively raising of power supply reliability requirement; Traditional cycle maintenance pattern faces maintainer's shortage, power off time is long, power supply reliability is low, " accompanying examination to accompany inspection " great number of issues such as phenomenon is general, cost of overhaul height; Can not adapt to the requirement of power network development, repair based on condition of component is to solve the important means that traditional maintenance pattern faces problem.
The repair based on condition of component mode is a foundation with the current practical working situation of equipment; It is through advanced status monitoring and diagnostic means, reliability evaluation means and life prediction means; The state of judgment device, the early stage sign of identification fault is made judgement to trouble location itself and the order of severity, fault trend; And, drop to a certain degree or fault is initiatively implemented maintenance before will taking place in equipment performance according to the analyzing and diagnosing result.It is that electrical equipment safety, stable, long period, full performance, high-quality operation provide reliable technique and management to ensure.
At present, a lot of areas have begun the research and experiment of distribution net equipment repair based on condition of component, and have set up corresponding system.But owing to lack the standard or the standard of whole planning and design, construction and examination, also each is variant for the distribution of being faced reality level, and also not having at present can blanket equipment monitor, state estimation and maintenance decision technical scheme.
Summary of the invention
The technical matters that the present invention solved is based on the status information of equipment of monitoring equipment and related service system; Application intelligent equipment state assessment models and expert knowledge library; Real-time analysis equipment health status, and on this basis Plant maintenance plan is optimized, instruct the O&M personnel rationally to arrange service work; Reduce and repeat to have a power failure, reduce loss of outage.
For solving the problems of the technologies described above, the present invention takes following technical scheme to realize:
The present invention uses advanced technologies such as online acquisition, intelligent evaluation, machine learning, internet, database; With service distribution network systems O&M is fundamental purpose; The distribution various device is monitored in real time and assessed; According to assessment result, based on repair time and load transfer path turnaround plan is carried out complex optimum, for O&M personnel placement service work provides technical support.
Distribution net equipment status assessing system of the present invention is characterized in that, comprises following functional module:
Status information of equipment acquisition module: utilize monitoring equipment to obtain the status information of various distribution net equipments; The status information of equipment that will have now simultaneously in DMS, SCADA, fault repair reporting system, Outage Management Systems, Distributing Network GIS, the marketing system extracts, and forms the complete device status information data;
Status information of equipment ETL (Extract, Transformation, Loading; Data pick-up, conversion and loading) module: the status information of equipment data are screened and processed; Form unified data storehouse object; Set up general data model, the operable data of forming device state estimation module;
Smart machine state estimation module: according to the various status informations of power distribution network equipment, analyze data characteristics, equipment state is diagnosed;
Equipment state administration module:, judge whether controller switching equipment needs maintenance according to the information of smart machine state estimation module;
Maintenance Schedule Optimization module: turnaround plan is carried out complex optimum based on repair time and load transfer path;
Base module: preserve the diagnosis algorithm configuration information and the diagnostic result of smart machine state estimation module, and in the Device Diagnostic process, continue to optimize the diagnosis algorithm configuration information through study;
The Dynamic Display module: according to the equipment evaluation result, Real-time and Dynamic presentation device state on the page according to turnaround plan, is showed maintenance process with the mode that animation and text combine.
Aforesaid distribution net equipment status assessing system is characterized in that: in the status information of equipment acquisition module, described checkout equipment comprises infrared measurement of temperature equipment, shelf depreciation online detection instrument, leakage current checkout equipment etc.
Aforesaid distribution net equipment status assessing system is characterized in that: said smart machine state estimation module comprises workspace, pattern matcher, algorithmic dispatching, four modules of algorithm execution:
Workspace slave unit bus obtains device status data, and imports device status data into pattern matcher;
Pattern matcher: analytical equipment status data characteristic, in conjunction with knowledge base and algorithmic dispatching rule, mate diagnostic mode and diagnosis algorithm automatically;
Algorithmic dispatching: schedule informations such as the execution time of management assessment algorithm, cycle;
Algorithm execution module: treat the assessment apparatus execution algorithm by the scheduling requirement; Return execution result and give the workspace,, said return results is meant the state of current device; Comprise: outstanding, good, qualified, defective, return results imports in the equipment state administration module to be handled.
It is characterized in that: said smart machine state estimation module utilizes the executory diagnosis algorithm of algorithm that the controller switching equipment state is diagnosed, and said diagnosis algorithm comprises fuzzy cluster analysis algorithm, step analysis algorithm or genetic algorithm etc.
,These algorithms carry out state estimation to distinct device type and diagnostic mode to equipment respectively.
Aforesaid distribution net equipment status assessing system; It is characterized in that: said diagnostic mode comprises single diagnostic mode and comprehensive diagnos mode; Said single diagnostic mode detects data relatively with device status data and rules, historical maintenance and fault data, experimental data, same category of device; Set up the single diagnostic rule of power distribution network master status through knowledge base, and single diagnostic rule is kept in the rule base of expert system; Said comprehensive diagnos mode is that the utilization artificial neural network sets up mathematical model between failure symptom and abort situation; With the diagnostic characteristic data storage in the weights and threshold values of network; The failure symptom of input is exported after handling through mathematical model accurately, instructs localization of fault.
The equipment state administration module comprises state management module, state processing module, maintenance decision module three sub-module, and state management module is communicated by letter with base module, safeguards the status information of all devices; The state processing module judges whether the duration of abnormal conditions and abnormal conditions according to the status information of equipment that imports into, confirms to take place during threshold values unusual when reaching unusual duration; The maintenance decision module judges whether the needs maintenance according to the status information of equipment and the regulation of inspection and repair.
Aforesaid distribution net equipment status assessing system is characterized in that: said Maintenance Schedule Optimization module comprises repair time optimal module and load transfer path optimal module.Said repair time optimal module provides prioritization scheme based on genetic algorithm, and the selection strategy of genetic algorithm is that rotating disc type is selected, and calculates the average adaptive value of new population, and adaptive value is able to existence less than the individuality of average, and the individuality that is higher than average is survived with probability.Crossover Strategy adopts even Crossover Strategy.Said load transfer path optimal module based on the heuristic search algorithm of waiting to recover to set cutting and before push back for algorithm and provide prioritization scheme; Concrete thinking is: confirm node relationships according to the first end-node of circuit; Form hierarchical relationship through BFS repeatedly; Confirm node computation sequence, based on branch current calculate the node injection current push back calculate each branch current and before push away voltage, make Voltage unbalance be not more than convergence criterion through iteration at last.
Aforesaid distribution net equipment status assessing system; It is characterized in that: knowledge adopts production rule to represent in the described base module; Knowledge comprises compositions such as equipment state, detection method, monitoring result, expert judgments, status data, and extracts automatically and adjustment equipment failure sign and judgment device state rule through self study.
The beneficial effect that the present invention reached:
The present invention is directed to difficult points such as the extraction of distribution net equipment fault early sign, the foundation of equipment state assessment models, equipment state overhauling algorithm optimization; Designed equipment state assessment models based on expert system and artificial neural network; The distribution net equipment state is carried out real-time monitoring and evaluation, realize optimization turnaround plan through the method that the repair time is optimized and the optimization of load transfer path combines.Adopt technological means to realize at aspects such as data model extraction, the automatic renewals of knowledge base simultaneously.
(1) to a certain failure problems; Measurement data according to multiple monitoring equipment; Extract the early stage status data of one group of this fault through principal component analysis (PCA); In the algorithm execution module, adopt the K-means algorithm that these group data are carried out cluster analysis, provide the early sign and the eigenstate data of this failure problems.
(2) single diagnosis detects data relatively with device status data and rules, historical maintenance and fault data, experimental data, same category of device; And consider the operation conditions of current system; Set up the single diagnostic rule of power distribution network master status through expert system, and these knowledge are kept in the rule base of expert system.Comprehensive diagnos be the utilization artificial neural network between failure symptom and abort situation, set up mathematical model, with the comprehensive diagnos knowledge store in the weights and threshold values of network.Adopt the BP network to carry out modeling.The failure symptom of input is exported through after the processing of model accurately, instructs localization of fault.
(3) provide the repair time prioritization scheme based on genetic algorithm; Based on the heuristic search algorithm of waiting to recover to set cutting and before push back for algorithm and provide load transfer path prioritization scheme; Comprehensive on this basis two kinds of prioritization schemes; Provide optimum maintenance scheme, foundation is provided for the maintainer rationally arranges service work.
Description of drawings
Fig. 1 is the physics deployment diagram;
Fig. 2 is a software architecture diagram.
Embodiment
The present invention mainly comprises following each functional module:
Status information of equipment acquisition module: according to the kind of equipment; Adopt multiple monitoring equipment and method; The method that combines with sun power and accumulator guarantees the operate as normal of monitoring equipment; Extraction in conjunction with the status information of equipment in existing DMS, SCADA, fault repair reporting system, Outage Management Systems, Distributing Network GIS, the marketing system forms the round-the-clock by all kinds of means equipment state acquisition system of multimode;
Status information of equipment ETL module: device status data is carried out certain screening and processing, take out unified data storehouse object, work out general data model, the operable data of forming device state estimation module;
Smart machine state estimation module: according to the various status informations of power distribution network equipment, the method that adopts expert system to combine with the artificial neural network is analyzed data characteristics, and Intelligence Selection diagnosis algorithm and diagnostic mode are diagnosed equipment state;
Maintenance Schedule Optimization module: consider from economy, management etc. are many-sided,, turnaround plan is carried out complex optimum based on repair time and load transfer path in conjunction with genetic algorithm;
Base module: knowledge base is preserved diagnostic device assessment algorithm configuration information and diagnostic result, and in the Device Diagnostic process, continues to optimize algorithm configuration information through study;
Dynamic Display: according to the equipment evaluation result, Real-time and Dynamic presentation device state on the page according to turnaround plan, is showed maintenance process with the mode that animation and text combine.
Below in conjunction with accompanying drawing the present invention is done concrete introduction:
Fig. 1 is a physics deployment diagram of the present invention; Fig. 2 is a software architecture diagram of the present invention.
As shown in Figure 1, distribution net equipment assessment models of the present invention comprises data acquisition server, database server, evaluation of algorithm server, proof of algorithm server, application server.Data acquisition server is responsible for from the various status informations of other operation systems and monitoring equipment collection distribution net equipment, and data are cleaned, changed; Database server is responsible for memory device master data, device status data and knowledge base; The evaluation of algorithm server is responsible for the equipment state assessment, and deposits the equipment state assessment result in database server; The proof of algorithm server is verified, is optimized algorithm, deposits the result in database server; Using publisher server is that the equipment state displaying provides the platform support.
As shown in Figure 2, the smart machine state estimation comprises: workspace, pattern matcher, algorithmic dispatching, algorithm are carried out four modules.The state estimation program obtains device status data through the workspace; Into pattern matcher is imported device status data in the workspace, and pattern matcher is analyzed data characteristics, and in conjunction with knowledge base and algorithmic dispatching rule, automatic matching algorithm is also dispatched related algorithm and carried out; The algorithm execution module returns execution result and gives the workspace; The workspace returns to the equipment evaluation program with execution result.Return results is meant the state of current device, comprising: outstanding, good, general, unusual.The equipment state appraisal procedure imports above-mentioned return results in the equipment state administration module into to be handled.
The equipment state administration module comprises condition managing, state processing, maintenance decision three sub-module.State management module and database communication are safeguarded the status information of all devices; The state processing module judges whether the duration of abnormal conditions and abnormal conditions according to the status information of equipment that imports into, confirms to take place during threshold values unusual when reaching unusual duration; Maintenance decision judges whether the needs maintenance according to the status information of equipment and the regulation of inspection and repair.
The Maintenance Schedule Optimization module comprises that the repair time is optimized and the optimization of load transfer path; Repair time optimization provides prioritization scheme based on genetic algorithm; Load transfer path optimization based on the heuristic search algorithm of waiting to recover to set cutting and before push back for algorithm and provide prioritization scheme; Comprehensive on this basis two kinds of prioritization schemes return optimum prioritization scheme.
The present invention is in order to realize the assessment of distribution net equipment state and the optimization of turnaround plan; Adopt multiple mode and channel collecting device status information, extract the unified data object, built smart machine state estimation model and expert knowledge library; According to status information of equipment and knowledge base; The analyzing and diagnosing equipment state, and shift based on repair time and load path turnaround plan is optimized, can realize the complex optimum of overhaul of the equipments scheme; For the stable operation of distribution network systems provides technical support, improve the O&M level and the work efficiency of distribution network systems.
Below announce the present invention as above with preferred embodiment, so it is not in order to restriction the present invention, and all technical schemes that mode obtained of taking to be equal to replacement or equivalent transformation all drop in protection scope of the present invention.
Claims (8)
1. a distribution net equipment status assessing system is characterized in that, comprises following functional module:
Status information of equipment acquisition module: utilize monitoring equipment to obtain the status information of various distribution net equipments; The status information of equipment that will have now simultaneously in power information collection, SCADA, fault repair reporting system, Outage Management Systems, Distributing Network GIS, the marketing system extracts, and forms the complete device status information data;
Status information of equipment ETL module: the status information of equipment data are screened and processed, form unified data storehouse object, set up general data model, the operable data of forming device state estimation module;
Smart machine state estimation module: according to the various status informations of power distribution network equipment, analyze data characteristics, equipment state is diagnosed;
Equipment state administration module:, judge whether controller switching equipment needs maintenance according to the information of smart machine state estimation module;
Maintenance Schedule Optimization module: turnaround plan is carried out complex optimum based on repair time and load transfer path;
Base module: preserve the diagnosis algorithm configuration information and the diagnostic result of smart machine state estimation module, and in the Device Diagnostic process, continue to optimize the diagnosis algorithm configuration information through study;
The Dynamic Display module: according to the equipment evaluation result, Real-time and Dynamic presentation device state on the page according to turnaround plan, is showed maintenance process with the mode that animation and text combine.
2. distribution net equipment status assessing system according to claim 1 is characterized in that: in the status information of equipment acquisition module, said checkout equipment comprises infrared measurement of temperature equipment, shelf depreciation online detection instrument, leakage current checkout equipment etc.
3. distribution net equipment status assessing system according to claim 1 is characterized in that: said smart machine state estimation module comprises workspace, pattern matcher, algorithmic dispatching, four modules of algorithm execution:
Workspace slave unit bus obtains device status data, and imports device status data into pattern matcher;
Pattern matcher: analytical equipment status data characteristic, in conjunction with knowledge base and algorithmic dispatching rule, mate diagnostic mode and diagnosis algorithm automatically;
Algorithmic dispatching: the schedule information of management assessment algorithm comprises execution time and cycle;
Algorithm execution module: treat the assessment apparatus execution algorithm by the scheduling requirement; Return execution result and give the workspace; Said return results is meant the state of current device, comprising: outstanding, good, qualified, defective, return results imports in the equipment state administration module to be handled.
4. distribution net equipment status assessing system according to claim 3; It is characterized in that: said smart machine state estimation module utilizes the algorithm execution module that the controller switching equipment state is diagnosed; Said algorithm is carried out and is comprised fuzzy cluster analysis algorithm, step analysis algorithm or genetic algorithm, and algorithm carries out state estimation to distinct device type and diagnostic mode to equipment respectively.
5. distribution net equipment status assessing system according to claim 3; It is characterized in that: said diagnostic mode comprises single diagnostic mode and comprehensive diagnos mode; Said single diagnostic mode detects data relatively with device status data and rules, historical maintenance and fault data, experimental data, same category of device; Set up the single diagnostic rule of power distribution network master status through knowledge base, and single diagnostic rule is kept in the rule base of knowledge base; Said comprehensive diagnos mode is that the utilization artificial neural network sets up mathematical model between failure symptom and abort situation; With the diagnostic characteristic data storage in the weights and threshold values of network; The failure symptom of input is exported after handling through mathematical model accurately, instructs localization of fault.
6. distribution net equipment status assessing system according to claim 1; It is characterized in that: the equipment state administration module comprises state management module, state processing module, maintenance decision module three sub-module; State management module is communicated by letter with base module, safeguards the status information of all devices; The state processing module judges whether the duration of abnormal conditions and abnormal conditions according to the status information of equipment that imports into, confirms to take place during threshold values unusual when reaching unusual duration; The maintenance decision module judges whether the needs maintenance according to the status information of equipment and the regulation of inspection and repair.
7. distribution net equipment status assessing system according to claim 1; It is characterized in that: said Maintenance Schedule Optimization module comprises repair time optimal module and load transfer path optimal module, and said repair time optimal module provides prioritization scheme based on genetic algorithm, and the selection strategy of genetic algorithm is that rotating disc type is selected; Calculate the average adaptive value of new population; Adaptive value is able to existence less than the individuality of average, and the individuality that is higher than average is survived with probability, and Crossover Strategy adopts even Crossover Strategy; Said load transfer path optimal module based on the heuristic search algorithm of waiting to recover to set cutting and before push back for algorithm and provide prioritization scheme; Concrete grammar is: confirm node relationships according to the first end-node of circuit; Form hierarchical relationship through BFS repeatedly; Confirm node computation sequence, based on branch current calculate the node injection current push back calculate each branch current and before push away voltage, make Voltage unbalance be not more than convergence criterion through iteration at last.
8. distribution net equipment status assessing system according to claim 1; It is characterized in that: knowledge adopts production rule to represent in the described base module; Knowledge comprises equipment state, detection method, monitoring result, expert judgments and status data, and extracts automatically and adjustment equipment failure sign and judgment device state rule through self study.
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