Research Of Assistant-decision System For Fault Diagnosis In Power System Based On ArcGIS Engine

The power grid is a network system, which has wide coverage, complexstructure, and is difficult to maintain and manage. At present, the power faultdiagnosis system cannot be managed effectively for the complex grid data(including spatial data and vector data), and cannot analysis and process a largeinflux of alarm information validly after failure. It is hard for the dispatcher toidentify the information to determine the fault location in a short time.Therefore, it is particularly important to build an intelligent decision-makingsystem in order to diagnose the abnormal information of the power gridaccurately.Under this background, this paper builds a network fault diagnosisanalytical model and an improved quantum particle swarm optimizationalgorithm to solve the model, which fully considers the related information offailure and the breaker protection in the power grid. Thus, it provides a certainreference value for the accurate fault location. Furthermore, this paperestablishes an assistant decision system platform for the power failurediagnosis, which adopts the object-oriented design methods and component-based design concepts and techniques. The specific contents are asfollows:(1) In order to manage and operate the power grid data effectively, thispaper establishes a spatial database, and then a property database. The databaseachieve the management of the property data and the spatial data, themanipulation of the graphics data, the layer divided of the CAD format data,the conversion between the vector and raster data and between the shp and txtdata, and other functions. As a result, it can provide a variety of needed data toassist the decision-making quickly when the grid fails.(2) In this paper, it uses a combination of C/S and B/S model to achievethe competence setting, which utilizes the effective data management andtransaction processing capabilities of C/S mode, as well as the advantages ofB/S mode in data query and information browsing, etc. It has differentoperating interface for different permissions, improving the security of datastorage and processing capability of the power grid.(3) As the current fault diagnosis analytical model does not consider theerror and refuses to move the protection and circuit breaker, the failureprotection of breaker and other issues, as well as the diagnosis results can notreflect the fault condition in detail, this paper presents an improved analyticalmodel method, and it achieves the optimal solution of the model, which isbased on the improved quantum particle swarm algorithm.(4) In order to let the repairing members to reach the fault site in the shortest time, it builds a K optimal path system for the city’s electricity repairsbased on the improved Dijkstra algorithm. The system fully take into accountthe hindered factors such as passage coefficient, road grade, traffic congestiondegree and road quality, etc, which shows an optimal repair path morereasonably and scientifically. Furthermore，it can provide an alternative path toselect in the event of exceptional circumstances.(5) Based on the system design, this paper sets up an assistant decisionsystem for the fault diagnosis in power grid. It achieves many functions such asuser management, layer operation, right-click menu, hawk eye view, bufferanalysis, map markers, mapping and printing, etc. At the same time, on thebasis of the improved quantum particle swarm algorithm, it conducts thenumerical examples analysis of the fault diagnosis model in the power grid,which provides a scientific basis for the accurate prediction of the faultdiagnosis.