Distribution system outage information processing using comprehensive data and intelligent techniques

In many distribution management systems, customer trouble calls have been used as the main data source for low level outage handling. Increased distribution SCADA (Supervisory Control And Data Acquisition) and recent developments in AMR (Automated Meter Reading) systems are providing more metering information about the distribution system below the feeder breaker. However the distribution system is so complex that no single data source can provide consistently errorless outage information for fast and accurate outage location determination. An intelligent outage data processing and outage-locating algorithm was designed and developed in this project.; In the first part of the algorithm, a data filter using fuzzy logic was developed to model the uncertainty of the outage information and to reconcile conflicting data. This filter provides more accurate outage information for the distribution outage management system by combining data from trouble call, wireless AMR and distribution SCADA.; In the second part of this project, an outage locating and confirmation knowledge-based system (KBS) was developed. The KBS uses the output of the fuzzy filter, which includes a reduced amount of accurate outage information. The traditional outage escalation method and the on-demand read feature of the wireless AMR system are integrated in the KBS to provide better outage location. The outage elements will be pinpointed by escalation and the locations will be confirmed by a meter-polling scheme. This algorithm can identify a single outage and multiple outages. The KBS will provide the outage location and the additional checking suggestions. An expert system shell G2 was used to implement the outage locating KBS. The system was tested on a distribution feeder with 250 customers. Totally fifteen cases were tested in different outage scenarios.