Many developing countries have emphasis on distributed generation (DG) technology for their generation expansion planning. The planning considerations and judicious choice of attributes are dictated by prevailing conditions. The attributes considered are capital costs, energy not served per annum, and profits from injecting power into the grid at peak load, all of which are important for a developing country. The uncertain futures considered are three possible loading conditions, which can be low, medium and high. Different scenarios (plans) are generated by various combinations of configurations. DGs can be configured as stand-alone mode, hybrid operation, or micro-grid formation with or without grid connection. With the increased complexities in DG planning options along with the multiple attributes to be accounted, more sophisticated techniques other than conventional economic analysis are needed to arrive at correct decisions by decision makers. The analytical hierarchy process (AHP) is used for obtaining relative weights in an objective way. Further, the statistical method like interval-based multi-attribute decision making with tradeoff analysis is used for shortlisting the feasible plans and identifying the most appropriate plan. It is proposed to use the weights obtained from AHP for finding the performance efficiencies in data envelopment analysis (DEA) for evaluating the plans. A new composite utility function is proposed to resolve cases where performance efficiency is insufficient for evaluation in DEA application. The sample system is derived with reference to a rural electrification scheme in India. The assessment of plans is presented and discussed. The comparative strengths and weaknesses of the methods are reported on the basis of the results obtained.