The electrification of remote villages by autonomous renewable power systems is often more economical than the extension of a utility electrical grid. Accurate cost comparisons between the two alternatives, however, have historically been hindered by an inability to simulate a lowest cost autonomous system. In this article, a computational tool is presented which employs the techniques of combinatorial optimization to design a near-optimal autonomous power system for a given set of demand points. The optimum design of village electrification systems is approached as a two-level optimization problem. The upper level procedure attempts to design the optimum arrangement of transformers, which are connected to each other and to the electricity source with medium voltage wire. The lower level procedure attempts to design the optimum distribution grid for a specified transformer arrangement, with consideration of isolated sources. Optimization procedures based on the simulated annealing algorithm were developed for both the upper and lower level processes. An approximate lower level procedure based on the minimum spanning tree algorithm was also implemented in order to provide a reasonable starting point for the slower simulated annealing algorithm. Exhaustive enumeration algorithms for both the upper and lower level processes were developed in order to verify the accuracy of the other methods.