An interval fixed-mix stochastic programming method for greenhouse gas mitigation in energy systems under uncertainty

Y.L. Xie, Y.P. Li, G.H. Huang and Y.F. Li

Energy, 2010, vol. 35, issue 12, 4627-4644

Abstract: In this study, an interval fixed-mix stochastic programming (IFSP) model is developed for greenhouse gas (GHG) emissions reduction management under uncertainties. In the IFSP model, methods of interval-parameter programming (IPP) and fixed-mix stochastic programming (FSP) are introduced into an integer programming framework, such that the developed model can tackle uncertainties described in terms of interval values and probability distributions over a multi-stage context. Moreover, it can reflect dynamic decisions for facility-capacity expansion during the planning horizon. The developed model is applied to a case of planning GHG-emission mitigation, demonstrating that IFSP is applicable to reflecting complexities of multi-uncertainty, dynamic and interactive energy management systems, and capable of addressing the problem of GHG-emission reduction. A number of scenarios corresponding to different GHG-emission mitigation levels are examined; the results suggest that reasonable solutions have been generated. They can be used for generating plans for energy resource/electricity allocation and capacity expansion and help decision makers identify desired GHG mitigation policies under various economic costs and environmental requirements.

Keywords: Energy systems; Environment; Fixed-mix; Planning; Stochastic programming; GHG mitigation; Interval analysis; Uncertainty (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:35:y:2010:i:12:p:4627-4644

DOI: 10.1016/j.energy.2010.09.045

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