Inexact Optimization Methods And Its Application To Energy Planning

Energy planning plays a critically important role in sustainable socio-economic development. However, the uncertainties that are inherent in the planning process and the complex interactions among various uncertain parameters are challenging the capabilities of traditional determistic energy model. Therefore, the objective of this study is to apply inexact optimization methods to energy planning to deal with such complexities and uncertainties. In this study, a multistage interval-stochastic energy model (MIS-EM) is developed for supporting electric power and energy system planning under uncertainty, an inexact fuzzy-stochastic energy model (IFS-EM) is developed for planning energy and atmospheric environment system management under multiple uncertainties. Two cases study are provided respectively for demonstrating the applicability of the developed models. The results indicate that MIS-EM and IFS-EM could effectively reflect complexities and uncertainties of the study systems, and provide decision makers with scientific basis for decision making.