Development of an interval multi‐stage stochastic programming model for regional energy systems planning and GHG emission control under uncertainty |
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| Authors: | Gongchen Li Guohe Huang Qianguo Lin Yanpeng Cai Yumin Chen Xiaodong Zhang |
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| Affiliation: | 1. Faculty of Engineering and Applied Science, University of Regina, , Regina, Saskatchewan, S4S 0A2 Canada;2. Center for Studies of Energy and Environment, University of Regina, , Regina, Saskatchewan, S4S 7J7 Canada;3. Faculty of Engineering, Dalhousie University, , Halifax, Nova Scotia, B3J 1Z1 Canada |
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| Abstract: | A regional energy system consists of diverse forms of energy. Energy‐related issues such as utilization of renewable energy and reduction of greenhouse 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 (IMSP‐REM) was developed to support regional energy systems management and GHG control under uncertainty. The IMSP‐REM is a hybrid methodology of inexact optimization and multi‐stage stochastic programming. Not only can it handle uncertainties presented as intervals and probability density functions but also reflect dynamics of system conditions over multiple planning stages. The developed IMSP‐REM 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 system planning framework. In addition, the model has advantages in incorporating multiple uncertainties and dynamics within energy management systems. Copyright © 2011 John Wiley & Sons, Ltd. |
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| Keywords: | greenhouse gas mitigation energy model inexact |
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