Research On Power System Alarm Processing And Fault Diagnosis Based On Centralized Control Center

Substations are important parts of power system transmission and distribution as they areresponsible for receiving and distributing electricity. In addition, there are many devicesinstalled in substations, which make them vulnerable to different kinds of faults. If any faultcould not be diagnosed and recovered accurately and duly, it would get devices damaged orpeople hurt, to make it worse, it would cause cascading outages, which might result in largeblackout. With the construction of un-maned substation, centralized control centers becomecenters for fault information collection and processing in recent years. Substationdriving-room technology, as a concrete implementation of smart grid technologies insubstations, provides easy, smart, reliable and "one-stop" services for operational monitoringand maintainance management. It also supplies full-view information for a smartemergency-alert, fault diagnose system built upon centralized control centers.With such a context, researches focusing on fault diagnose system based on centralizedcontrol center was taken in this thesis and can be summarized into the following three parts:1) the application of substation fault diagnose techniques in power systems at home andabroad are presented and their pros and cons are fully analyzed. Current model of operationmanagement and fault diagnose at control centers, their advantages and disadvantages, rangeof application are also analyzed. Hence, the overall architecture of emergency alert and faultdiagnose system at centralized control centers is proposed.2）A united naming approach for alert information is researched. Tow-dimension divisionapproach is applied to categorize alert information into different level vertically and intodifferent classes horizontally. Implementation technologies of using the logical relationshipsamong the emergency information to alert operators the happening of any fault and providethem the related information.3）Fault diagnose under the condition of complex faults and uncertainty of time-series is analyzed considering that SOE events are all timed with GPS and the time-series constrain ofalarm information. A diagnose model based on node credibility is proposed. Details about themapping rule of temporal constraint network, the calculation of node credibility and theevaluation of diagnose result are discussed. The proposed model is verified with a small testsystem with three substations. The test result showed that it could correctly diagnose the faultseven when the scenario involved multi-substations, uncertainty of time-series, missing orwrongly report of alarms.