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The need for distribution reliability enhancement in the age of smart grids requires reliable methods for locating faults on distribution systems leading to a faster service restoration and maintenance cost optimization. Given the numerous fault location methods, one faces the challenge of objectively evaluating and selecting the most proper method. In this paper, a two-step approach is proposed and discussed for ranking available fault location methods that takes into account application requirements and modeling limitations and uncertainties. The ranking method formulated as uncertainty analysis utilizes 2 n + 1 point estimation to calculate the statistical moments of the fault location estimation error. These moments plugged into the Chebyshev's inequality provide a basis for ranking the fault location method. The selected method may still suffer from multiple fault location estimations. To address this caveat, voltage sag characteristics reported by few intelligent electronic devices (IEDs) along the feeder are utilized. The number and location of these IEDs are determined through an optimal approach specifically formulated for this problem. The proposed two-step ranking methodology and the IED placement optimization approach were implemented on a simulated distribution system and their effectiveness was demonstrated through a few select scenarios and case studies.