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Abstract: In order to enhance power system reliability and manage network congestions, many power utilities around the world have deployed various forms of system protection schemes (SPS) in their systems. In a deregulated environment, SPS could offer immediate solutions to network congestion that are beneficial to both utilities and customers. This paper presents a framework for quantitative risk and benefit assessments of SPS operations. The risk of SPS operations and its effect to the system security are evaluated by a probabilistic risk assessment approach. The benefits obtainable from power market and the customer interruption costs resulting from SPS operations are appraised. The proposed methodology can be used by power system operators and planners to assess the applications of SPS for system reliability enhancement and compare different alternatives for managing network congestion. Numerical results obtained from an actual event-based SPS example are presented. [ABSTRACT FROM AUTHOR]

Abstract: In a competitive electric energy market, service quality and reliability are two of the essential issues of the business. Distribution automation has been chosen by many utilities around the world as one of the most reliable measures for reducing outage time in their distribution networks. Considering network reliability data and the customer interruption costs, a value-based planning method is proposed in this paper to find the optimal numbers and locations of switches in feeder automation systems. The proposed method takes reliability costs, maintenance and investment costs into account to obtain a feeder automation plan that has a maximum benefit and a proper system reliability requirement. Three stages are involved in the search for optimal solution. Using minimum feeder data and assume equally distributed feeder loads, stage 1 gives initial estimates of reliability indices and costs, and benefit/cost ratios of different feeder automation options. To gain the maximum benefits from feeder automation with reasonable costs, results of stage 1 are used to select feeders with highest priorities for automations. Stage 2 determines the optimum locations of switches that minimize feeder outage costs, and in stage 3, the best locations for tie switches in the automated network are determined. Numerical processing procedure is described and the solution efficiency and results are compared with those obtained from a genetic algorithm. [Copyright &y& Elsevier]