This oeportdescribesan enhanced testsystem ( W W ) f o r MW In bulk power system reliability evaluation studies. The value of the tost system is that it will permit comparative and benchmark studios to be perf0me-d on new and existing reliability evaluation techniques. The test system was developed by modifying and updating the original IEEE RTS (referred to as RTS79 hereafter) to reflect changes In evaluation methodologies and to overcome perceived deficiencies. -The first version of the IEEE Reliability Test System (RTS 79) was developed and published in 1979 [ l ] by the Application of Probability Methods (APM) Subcommittee of the Power System Englaeering Committee. It was developed to satisfy the need for a standardized data base to test and compare results from different power system reliability evaluation methodologies. As such, was designed to b@ a reference system that contains the core data and system parameters necessary for composite reliability evaluation methods. It was recognized at that time that enhancements to RTS It should be noted that In developing and adopting the various parameters for RTS-96, there was no Intention to develop a test system which was representative of any specific or typical power system. Forcing such a requirement on RTs-98 would result in a

Optimal placement of protection devices and distributed generators (DGs) in radial feeders is important to ensure power system reliability. Distributed generation is being adopted in distribution networks with one of the objectives being enhancement of system reliability. In this paper, an ant colony system algorithm is used to derive the optimal recloser and DG placement scheme for radial distribution networks. A composite reliability index is used as the objective function in the optimization procedure. Simulations are carried out based on two practical distribution systems to validate the effectiveness of the proposed method. Furthermore, comparative studies in relation to genetic algorithm are also conducted.Index Terms-Ant colony optimization (ACO), distributed generation (DG), optimum recloser placement, stochastic search and optimization.

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Short-term and medium-term reliability evaluation for power systems with high penetration of wind power