With the increase and expansion of environmental requirements and dwindling of fossil fuel resources, current environmental and energy systems have aroused wide public concern. In this dissertation research, several optimization modeling methodologies have been developed for energy and environmental systems planning. They include: (a) a hybrid dynamic dual interval model (DDIP) for irrigation water allocation; (b) a robust interactive interval fully fuzzy model (RIIFFLP) for environmental systems planning; (c) a robust interval type-2 fuzzy set model (R-IT2FSLP) to manage irrigation water resources, (d) a robust inexact joint-optimal α cut interval type-2 fuzzy boundary model (RIJ-IT2FBLP) for planning of energy systems, and (e) a pseudo-optimal stochastic dual interval T2 fuzzy sets model (PD-IT2FSLP) for environmental pollutant control and energy systems planning. The DDIP has been developed by integrating dynamic programming (DP) with the dual interval technique into a general optimal framework. It was applied to a hypothetical case of irrigation water allocation in western Canada. The RIIFFLP method has been developed to deal with fully fuzzy uncertainties by using the fuzzy ranking method to find a balance between the necessity of constraints and the objective function of a linear interval fuzzy sets programming as a technique for optimal decision-making. The R-IT2FSLP method has been developed through integrating the concept of type-2 fuzzy sets with an interval fuzzy boundary model to achieve maximum system profits with limited environmental resources under uncertainties. The solutions obtained clearly show that the type-2 fuzzy sets methodology can provide significantly improved results that are more accurate by comparison to formal optimization methods. The RIJ-IT2FBLP model has been developed by combining the join-optimal α cut method, the interval RTSM solution method and the interval type-2 fuzzy sets boundary method. The developed model was applied to issues concerning long-term energy sources. The PD-IT2FSLP energy model has been developed to support energy system planning and environmental pollutant control under multiple uncertainties for Xiamen City in China. The solutions of the PD-IT2FSLP model will help energy authorities improve current energy consumption patterns and ascertain an optimal pattern for energy utilization in Xiamen City.