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Power distribution systems have been significantly affected by many fault causing events. Effective outage cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real- world data often degrades the outage cause identification performance. In this paper, artificial immune recognition system (AIRS), an immune-inspired algorithm for supervised classification task is applied to the Duke Energy outage data for outage cause identification using three major causes (tree, animal, and lightning) as prototypes. The performance of AIRS on these real-world imbalanced data is compared with an artificial neural network (ANN). The results show that AIRS can greatly improve the performance by as much as 163% when the data are imbalanced and achieve comparable performance with ANN for relatively balanced data. [ABSTRACT FROM AUTHOR]

This paper demonstrates the use of a slow-coherency-based generator grouping algorithm and a graph theoretic approach to form controlled islands as a last resort to prevent cascading outages following large disturbances. The proposed technique is applied to a 30 000-bus, 5000-generator, 2004 summer peak load, Eastern Interconnection data and demonstrated on the August 14, 2003 blackout scenario. Adaptive rate of frequency decline-based load shedding schemes are used in the load rich islands to control frequency. The simulation results presented show the advantage of the proposed method in containing the impact of the disturbance within the islands formed and in preventing the impact of the disturbance from propagating to the rest of the system. This is demonstrated by the significant reduction in line flows in the rest of the system and by improved voltage and relative angle characteristics. Based on the suggestion in the joint U.S.-Canadian task force final report on the blackout, load shedding without any islanding is also performed, and results obtained are compared with the proposed controlled islanding method. The islanding method outperforms the load shedding-only method in reducing the transmission line flows, but both methods have similar effects on voltage and relative angle behavior. [ABSTRACT FROM AUTHOR]

We investigate to find an efficient resource allocation algorithm among three proposed algorithms to improve the outage probability for multiple users in an indoor power-line communications system. The bit-error rate for users requiring different quality of service is considered to see whether the outage probability has improved. The suggested algorithms are shown to find the distribution of subchannels that improve the average outage probability when all users experience multipath fading time-varying channel characteristics. We compare the performance of the proposed algorithms with a conventional resource allocation algorithm and demonstrate its efficiency. Simulation results demonstrate that the performance of the greedy-algorithm-based algorithm is superior to that of the conventional algorithm in almost outage threshold ranges. [ABSTRACT FROM AUTHOR]

An algorithm is presented to evaluate substation reliability. This algorithm takes into account breaker failures, blocked breakers, and breaker backup protection to isolate faults in a substation. Passive and active outages are considered. Two evaluation criteria are used: substation fails if one point of load fails, and substation fails if all points of load fail. The cost of energy not supplied is used to evaluate and economically compare the substation reliability. [ABSTRACT FROM AUTHOR]