Multiple dynamics and uncertainties are involved in regional energy and greenhouse gas management (REGM) system, confronting decision makers during plan/policy makings. In this study, a greenhouse gas (GHG)-mitigation oriented inexact dynamic energy system management model (IFMP-REGM) is developed for a REGM system. The IFMP-REGM is a hybrid methodology of interval mathematical programming, fuzzy linear programming and multi-stage stochastic programming. It can not only handle uncertainties presented as discrete intervals, fuzzy sets and probability distributions, but also reflect dynamic variations of system conditions, particularly for large-scale multistage problems with sequential structures. The uncertain information can be incorporated within a multi-layer scenario tree: revised decisions are permitted in each time period based on the realized values of the uncertain events. The developed IFMP-REGM model was then applied to a hypothetical regional energy and GHG management system. The results indicate that the IFMP-REGM can effectively address complexities of various system uncertainties as well as dealing with multi-stage stochastic decision problems within energy systems. (C) 2011 Elsevier Ltd. All rights reserved.