Development of an interval multi-stage stochastic programming model for regional energy systems planning and GHG emission control under uncertainty

Gongchen Li, Guohe Huang*, Qianguo Lin, Yanpeng Cai, Yumin Chen, Xiaodong Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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 (C) 2011 John Wiley & Sons, Ltd.

Original languageEnglish
Pages (from-to)1161-1174
Number of pages14
JournalInternational Journal of Energy Research
Volume36
Issue number12
DOIs
Publication statusPublished - Oct 2012

Keywords

  • greenhouse gas
  • mitigation
  • energy model
  • inexact
  • management
  • optimization
  • methodology
  • expansion

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