In this study, an inexact mixed-integer fractional energy system planning (IMIF-EP) model is developed for supporting sustainable energy system management under uncertainty. Based on a hybrid of interval-parameter programming (IPP), fractional programming (FP) and mixed integer linear programming (MILP) techniques, IMIF-EP can systematically reflect various complexities in energy management systems. It not only handles imprecise uncertainties and dynamic features associated with power generation expansion planning, but also optimizes the system efficiency represented as output/input ratios. An interactive transform algorithm is proposed to solve the IMIF-EP model. For demonstrating effectiveness of the developed approach, IMIF-EP is applied to support long-term planning for an energy system. The results indicate that interval solutions obtained from IMIF-EP can provide flexible schemes of resource allocations and facility expansions towards sustainable energy management (SEM) under multiple complexities. A comparative economical energy management (EEM) system is also provided. Compared with least-cost models that optimize single criterion, IMIF-EP can better characterize practical energy management problems by optimizing a ratio between criteria of two magnitudes. In application, IMIF-EP is advantageous in balancing conflicting objectives and reflecting complicated relationships among multiple system factors. (C) 2013 Elsevier Ltd. All rights reserved.