CN102509178B - 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 being applied to the assessment of distribution net equipment condition intelligent, based on the various states of Distribution Network Equipment, adopt the method that expert system is combined with artificial neural network, analyze data characteristics, intelligent selection diagnosis algorithm and diagnostic mode, diagnose equipment state; According to device Diagnostic result, consider from the many-side such as economy, management, in conjunction with genetic algorithm, based on repair time and load transfer plan path, complex optimum is carried out to turnaround plan.
Background technology
Along with the fast development of electrical network, and the progressively raising that user requires power supply reliability, traditional cycle maintenance model 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, the cost of overhaul is high, can not adapt to the requirement of power network development, repair based on condition of component is the important means solving traditional maintenance model Problems.
Mode of condition-oriented overhaul with the current practical working situation of equipment for foundation, it is by advanced status monitoring and diagnostic means, reliability evaluation means and life prediction means, the state of judgment device, identify the early stage sign of fault, trouble location itself and the order of severity, fault trend are judged, and according to analyzing and diagnosing result, before equipment performance drops to a certain degree or fault will occur, initiatively implement maintenance.It is electrical equipment safety, stable, long period, full performance, high-quality are run and provided reliable technology and management ensures.
At present, a lot of areas have started the research and experiment of distribution net equipment repair based on condition of component, and establish corresponding system.But owing to lacking overall planning and design, the standard of construction and examination or specification, the real level of the distribution faced by institute is also each variant, and also not having at present can blanket equipment monitor, state estimation and maintenance decision technical scheme.
Summary of the invention
Technical matters solved by the invention is the status information of equipment based on monitoring equipment and related service system, application smart machine state estimation model and expert knowledge library, real-time analysis equipment health status, and on this basis Plant maintenance plan is optimized, instruct the service work of operation maintenance personnel reasonable arrangement, 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 online acquisition, intelligent evaluation, machine learning, internet, database advanced technology, to serve distribution network systems O&M for fundamental purpose, Real-Time Monitoring and assessment are carried out to the various equipment of distribution, according to assessment result, based on repair time and load transfer plan path, complex optimum is carried out to turnaround plan, for operation maintenance personnel arranges service work to provide technical support.
Distribution network device status evaluating system of the present invention, is characterized in that, comprises following functions module:
Status information of equipment acquisition module: utilize monitoring equipment to obtain the status information of various distribution net equipment, status information of equipment in existing DMS, SCADA, troublshooting system, Outage Management Systems, Distributing Network GIS, marketing system is extracted simultaneously, form complete status information of equipment data;
Status information of equipment ETL(Extract, Transformation, Loading, data pick-up, conversion and loading) module: status information of equipment data are carried out screening and processing, form unified database 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 Distribution Network Equipment, analyzes data characteristics, diagnoses equipment state;
Equipment state administration module: according to the information of smart machine state estimation module, judges that controller switching equipment is the need of maintenance;
Maintenance Schedule Optimization module: complex optimum is carried out to turnaround plan based on repair time and load transfer plan path;
Base module: diagnosis algorithm configuration information and the diagnostic result of preserving smart machine state estimation module, and in device Diagnostic process, continue to optimize diagnosis algorithm configuration information by study;
Dynamic Display module: according to equipment evaluation result, real-time Dynamic Display equipment state on the page, according to turnaround plan, shows maintenance process in the mode that animation and text combine.
Aforesaid distribution network device status evaluating system, is characterized in that: in status information of equipment acquisition module, and described checkout equipment comprises infrared measurement of temperature equipment, shelf depreciation online detection instrument, leakage current checkout equipment etc.
Aforesaid distribution network device status evaluating system, is characterized in that: described smart machine state estimation module comprises workspace, pattern matcher, algorithmic dispatching, algorithm perform four modules:
Into pattern matcher from device bus equipment status data, and is imported device status data in workspace;
Pattern matcher: analytical equipment status data feature, in conjunction with knowledge base and algorithmic dispatching rule, Auto-matching diagnostic mode and diagnosis algorithm;
Algorithmic dispatching: the schedule information such as execution time, cycle of management assessment algorithm;
Algorithm execution module: treat assessment apparatus execution algorithm by scheduling requirement, return execution result to workspace, described in return results the state referring to current device, comprise: outstanding, good, qualified, defective, return results to import in equipment state administration module and process.
It is characterized in that: described smart machine state estimation module utilizes the executory diagnosis algorithm of algorithm to diagnose controller switching equipment state, and described 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 network device status evaluating system, it is characterized in that: described diagnostic mode comprises single diagnostic mode and comprehensive diagnos mode, described single diagnostic mode by device status data and code, history is overhauled and fault data, experimental data, same category of device detect data and compare, set up the single diagnostic rule of power distribution network master status by knowledge base, and single diagnostic rule is kept in the rule base of expert system; Described comprehensive diagnos mode uses artificial neural network to set up mathematical model between failure symptom and abort situation, diagnostic characteristic data are stored in the weights and bias of network, the failure symptom of input is exported accurately after mathematical model process, instructs localization of fault.
Equipment state administration module comprises state management module, status processing module, maintenance decision module three submodules, and state management module communicates with base module, safeguards the status information of all devices; Status processing module, according to the status information of equipment imported into, judges whether the duration of abnormal conditions and abnormal conditions, confirms to occur extremely when reaching Abnormal lasting threshold values; Maintenance decision module judges whether to need maintenance according to status information of equipment and the regulation of inspection and repair.
Aforesaid distribution network device status evaluating system, is characterized in that: described Maintenance Schedule Optimization module comprises repair time optimization module and load transfer plan path optimization module.The described repair time is optimized module and provides prioritization scheme based on genetic algorithm, and the selection strategy of genetic algorithm is that rotating disc type is selected, and calculate the average adaptive value of new population, adaptive value is less than the individual existence of average, and the individuality higher than average is survived with probability.Crossover Strategy adopts uniform crossover strategy.The heuristic search algorithm that described load transfer plan path optimization module is cut based on candidate restoring tree and Forward and backward substitution method provide prioritization scheme, concrete thought is: according to circuit first and last node determination node relationships, hierarchical relationship is formed through repeatedly BFS (Breadth First Search), determine node calculate order, based on branch current calculate node Injection Current push back calculate each branch current and before push away voltage, make Voltage unbalance be not more than convergence criterion finally by iteration.
Aforesaid distribution network device status evaluating system, it is characterized in that: in described base module, knowledge adopts production rule to represent, knowledge comprises the compositions such as equipment state, detection method, monitoring result, expert judgments, status data, and is automatically extracted and adjusted equipment failure sign and judgment device state rule by self study.
The beneficial effect that the present invention reaches:
The present invention is directed to the 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, devise the equipment state assessment models based on expert system and artificial neural network, Real-Time Monitoring assessment is carried out to distribution net equipment state, realizes the optimization to turnaround plan by the method that the repair time is optimized and load transfer plan path optimization combines.Extract at data model simultaneously, adopt technological means to realize in knowledge base upgrades automatically etc.
(1) for a certain failure problems, according to the measurement data of multiple monitoring equipment, the early stage status data of one group of this fault is extracted by principal component analysis (PCA), in algorithm execution module, adopt K-means algorithm to carry out cluster analysis to these group data, provide early sign and the eigenstate data of this failure problems.
(2) single diagnosis by device status data and code, history is overhauled and fault data, experimental data, same category of device detect data and compare, and consider the operation conditions of current system, set up the single diagnostic rule of power distribution network master status by expert system, and these knowledge are kept in the rule base of expert system.Comprehensive diagnos uses artificial neural network between failure symptom and abort situation, to set up mathematical model, by comprehensive diagnos knowledge store in the weights and bias of network.BP network is adopted to carry out modeling.The failure symptom of input is exported accurately after the process of model, instructs localization of fault.
(3) repair time prioritization scheme is provided based on genetic algorithm, the heuristic search algorithm of cutting based on candidate restoring tree and Forward and backward substitution method provide load transfer plan path optimization scheme, comprehensive two kinds of prioritization schemes on this basis, provide optimum maintenance solution, for the service work of maintainer's reasonable arrangement provides foundation.
Accompanying drawing explanation
Fig. 1 is physics deployment diagram;
Fig. 2 is software architecture diagram.
Embodiment
The present invention mainly comprises following functional module:
Status information of equipment acquisition module: according to the kind of equipment, adopt multiple monitoring equipment and method, the method combined with sun power and accumulator ensures the normal work of monitoring equipment, in conjunction with the extraction of the status information of equipment in existing DMS, SCADA, troublshooting system, Outage Management Systems, Distributing Network GIS, marketing system, form multimode round-the-clock equipment state acquisition system by all kinds of means;
Status information of equipment ETL module: device status data is carried out certain screening and processing, takes out unified database object, works 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 Distribution Network Equipment, adopts the method that expert system is combined with artificial neural network, and analyze data characteristics, intelligent selection diagnosis algorithm and diagnostic mode, diagnose equipment state;
Maintenance Schedule Optimization module: consider from the many-side such as economy, management, in conjunction with genetic algorithm, based on repair time and load transfer plan path, complex optimum is carried out to turnaround plan;
Base module: knowledge base preserves diagnostic device assessment algorithm configuration information and diagnostic result, and in device Diagnostic process, continue to optimize algorithm configuration information by study;
Dynamic Display: according to equipment evaluation result, real-time Dynamic Display equipment state on the page, according to turnaround plan, shows maintenance process in the mode that animation and text combine.
Below in conjunction with accompanying drawing, concrete introduction is done to the present invention:
Fig. 1 is physics deployment diagram of the present invention; Fig. 2 is 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, algorithm evaluation server, proof of algorithm server, application server.Data acquisition server is responsible for the various status informations gathering distribution net equipment from other operation systems and monitoring equipment, and cleans data, changes; Database server is responsible for memory device master data, device status data and knowledge base; Algorithm evaluation network in charge equipment state is assessed, and by equipment state assessment result stored in database server; Proof of algorithm server is verified algorithm, is optimized, by result stored in database server; Application publisher server is shown for equipment state provides platform support.
As shown in Figure 2, smart machine state estimation comprises: workspace, pattern matcher, algorithmic dispatching, algorithm perform four modules.State estimation program is by workspace equipment status data; Into pattern matcher is imported device status data in workspace, and pattern matcher analyzes data characteristics, and in conjunction with knowledge base and algorithmic dispatching rule, Auto-matching algorithm also dispatches related algorithm execution; Algorithm execution module returns execution result to workspace; Execution result is returned to equipment evaluation program by workspace.Return results the state referring to current device, comprising: be outstanding, good, general, abnormal.Equipment state appraisal procedure by above-mentioned return results to import in equipment state administration module process.
Equipment state administration module comprises condition managing, state processing, maintenance decision three submodules.State management module and database communication, safeguard the status information of all devices; Status processing module, according to the status information of equipment imported into, judges whether the duration of abnormal conditions and abnormal conditions, confirms to occur extremely when reaching Abnormal lasting threshold values; Maintenance decision judges whether to need maintenance according to status information of equipment and the regulation of inspection and repair.
Maintenance Schedule Optimization module comprises repair time optimization and load transfer plan path optimization, repair time optimization provides prioritization scheme based on genetic algorithm, the heuristic search algorithm that load transfer plan path optimization cuts based on candidate restoring tree and Forward and backward substitution method provide prioritization scheme, comprehensive two kinds of prioritization schemes on this basis, return optimum prioritization scheme.
The present invention is in order to realize the optimization of assessment to distribution net equipment state and turnaround plan, adopt various ways and channel collecting device status information, extract unified data object, smart machine state estimation model and expert knowledge library are built, according to status information of equipment and knowledge base, analyzing and diagnosing equipment state, and based on repair time and load path transfer, turnaround plan is optimized, the complex optimum of overhaul of the equipments scheme can be realized, for the stable operation of distribution network systems provides technical support, improve 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 intended to limiting the invention, and all technical schemes taking the mode of equivalent replacement or equivalent transformation to obtain, all drop in protection scope of the present invention.
Claims (7)
1. a distribution network device status evaluating system, is characterized in that, comprises following functions module:
Status information of equipment acquisition module: utilize monitoring equipment to obtain the status information of various distribution net equipment, status information of equipment in existing power information collection, SCADA, troublshooting system, Outage Management Systems, Distributing Network GIS, marketing system is extracted simultaneously, form complete status information of equipment data;
Status information of equipment ETL module: status information of equipment data are carried out screening and processing, forms unified database 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 Distribution Network Equipment, analyzes data characteristics, diagnoses equipment state; Described smart machine state estimation module comprises workspace, pattern matcher, algorithmic dispatching, algorithm perform four modules:
Into pattern matcher from device bus equipment status data, and is imported device status data in workspace;
Pattern matcher: analytical equipment status data feature, in conjunction with knowledge base and algorithmic dispatching rule, Auto-matching diagnostic mode and diagnosis algorithm;
Algorithmic dispatching: the schedule information of management assessment algorithm, comprises execution time and cycle;
Algorithm execution module: treat assessment apparatus execution algorithm by scheduling requirement, return execution result to workspace, describedly return results the state referring to current device, comprising: outstanding, good, qualified, defective, return results to import in equipment state administration module and process;
Equipment state administration module: according to the information of smart machine state estimation module, judges that controller switching equipment is the need of maintenance;
Maintenance Schedule Optimization module: complex optimum is carried out to turnaround plan based on repair time and load transfer plan path;
Base module: diagnosis algorithm configuration information and the diagnostic result of preserving smart machine state estimation module, and in device Diagnostic process, continue to optimize diagnosis algorithm configuration information by study;
Dynamic Display module: according to equipment evaluation result, real-time Dynamic Display equipment state on the page, according to turnaround plan, shows maintenance process in the mode that animation and text combine.
2. distribution network device status evaluating system according to claim 1, is characterized in that: in status information of equipment acquisition module, and described monitoring equipment comprises infrared measurement of temperature equipment, shelf depreciation online detection instrument, leakage current checkout equipment.
3. distribution network device status evaluating system according to claim 1, it is characterized in that: described smart machine state estimation module utilizes algorithm execution module to diagnose controller switching equipment state, described algorithm performs and comprises 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.
4. distribution network device status evaluating system according to claim 1, it is characterized in that: described diagnostic mode comprises single diagnostic mode and comprehensive diagnos mode, described single diagnostic mode by device status data and code, history is overhauled and fault data, experimental data, same category of device detect data and compare, set up the single diagnostic rule of power distribution network master status by knowledge base, and single diagnostic rule is kept in the rule base of knowledge base; Described comprehensive diagnos mode uses artificial neural network to set up mathematical model between failure symptom and abort situation, diagnostic characteristic data are stored in the weights and bias of network, the failure symptom of input is exported accurately after mathematical model process, instructs localization of fault.
5. distribution network device status evaluating system according to claim 1, it is characterized in that: equipment state administration module comprises state management module, status processing module, maintenance decision module three submodules, state management module communicates with base module, safeguards the status information of all devices; Status processing module, according to the status information of equipment imported into, judges whether the duration of abnormal conditions and abnormal conditions, confirms to occur extremely when reaching Abnormal lasting threshold values; Maintenance decision module judges whether to need maintenance according to status information of equipment and the regulation of inspection and repair.
6. distribution network device status evaluating system according to claim 1, it is characterized in that: described Maintenance Schedule Optimization module comprises repair time optimization module and load transfer plan path optimization module, the described repair time is optimized module and provides prioritization scheme based on genetic algorithm, the selection strategy of genetic algorithm is that rotating disc type is selected, calculate the average adaptive value of new population, adaptive value is less than the individual existence of average, and the individuality higher than average is survived with probability, and Crossover Strategy adopts uniform crossover strategy; The heuristic search algorithm that described load transfer plan path optimization module is cut based on candidate restoring tree and Forward and backward substitution method provide prioritization scheme, concrete grammar is: according to circuit first and last node determination node relationships, hierarchical relationship is formed through repeatedly BFS (Breadth First Search), determine node calculate order, based on branch current calculate node Injection Current push back calculate each branch current and before push away voltage, make Voltage unbalance be not more than convergence criterion finally by iteration.
7. distribution network device status evaluating system according to claim 1, it is characterized in that: in described base module, knowledge adopts production rule to represent, knowledge comprises equipment state, detection method, monitoring result and expert judgments, and is automatically extracted and adjusted equipment failure sign and judgment device state rule by self study.
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| CN117435964B (en) * | 2023-12-21 | 2024-03-15 | 江苏赫奕科技有限公司 | Equipment state evaluation method and system based on data diagnostic instrument |
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