An Inexact Programming Model for Regional Energy Systems Planning and GHG-Emission Control

Abstract

A regional energy system consists of diverse forms of energy. Energy-related issues such as utilization of renewable energy and reduction of green house gas (GHG) emission are confronting decision makers. Meanwhile, various uncertainties and dynamics of the energy system are posing difficulties for the energy system planning, especially for those under multiple stages. In this study, an interval multi-stage stochastic programming regional energy systems planning model (IMSPREM) was developed for supporting regional energy systems management and green house gas control under uncertainty. The IMSP-REM is a hybrid methodology of inexact optimization and multi-stage stochastic programming. It can not only handle uncertainties presented as intervals and probability density functions, but also reflect dynamics of system conditions over multiple planning stages. The developed IMSPREM was applied to a hypothetical regional energy system. The results indicate that the IMSP-REM can effectively reflect issues of GHG reduction and renewable energy utilization within an energy systems planning framework. In addition, the model has advantages in incorporating multiple uncertainties and dynamics within energy management systems.