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IFTEM: An interval-fuzzy two-stage stochastic optimization model for regional energy systems planning under uncertainty

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  • Lin, Q.G.
  • Huang, G.H.
  • Bass, B.
  • Qin, X.S.

Abstract

The development of optimization models for energy systems planning has attracted considerable interest over the past decades. However, the uncertainties that are inherent in the planning process and the complex interactions among various uncertain parameters are challenging the capabilities of these developed tools. Therefore, the objective of this study is to develop a hybrid interval-fuzzy two-stage stochastic energy systems planning model (IFTEM) to deal with various uncertainties that can be expressed as fuzzy numbers, probability distributions and discrete intervals. The developed IFTEM is then applied to a hypothetical regional energy system. The results indicate that the IFTEM has advantages in reflecting complexities of various system uncertainties as well as dealing with two-stage stochastic decision problems within energy systems.

Suggested Citation

  • Lin, Q.G. & Huang, G.H. & Bass, B. & Qin, X.S., 2009. "IFTEM: An interval-fuzzy two-stage stochastic optimization model for regional energy systems planning under uncertainty," Energy Policy, Elsevier, vol. 37(3), pages 868-878, March.
    • Handle: RePEc:eee:enepol:v:37:y:2009:i:3:p:868-878
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    4. Dong, C. & Huang, G.H. & Cai, Y.P. & Liu, Y., 2012. "An inexact optimization modeling approach for supporting energy systems planning and air pollution mitigation in Beijing city," Energy, Elsevier, vol. 37(1), pages 673-688.
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    7. Gaiqiang Yang & Ping Guo & Mo Li & Shiqi Fang & Liudong Zhang, 2016. "An Improved Solving Approach for Interval-Parameter Programming and Application to an Optimal Allocation of Irrigation Water Problem," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 701-729, January.
    8. Zhou, Yang & Huang, Guo H. & Yang, Boting, 2013. "Water resources management under multi-parameter interactions: A factorial multi-stage stochastic programming approach," Omega, Elsevier, vol. 41(3), pages 559-573.
    9. Li, Y.F. & Li, Y.P. & Huang, G.H. & Chen, X., 2010. "Energy and environmental systems planning under uncertainty--An inexact fuzzy-stochastic programming approach," Applied Energy, Elsevier, vol. 87(10), pages 3189-3211, October.
    10. Wang, S. & Xie, Y.L. & Huang, G.H. & Yao, Y. & Wang, S.Y. & Li, Y.F., 2021. "A Structural Adjustment optimization model for electric-power system management under multiple Uncertainties—A case study of Urumqi city, China," Energy Policy, Elsevier, vol. 149(C).
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    12. Prasad, Ravita D. & Bansal, R.C. & Raturi, Atul, 2014. "Multi-faceted energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 686-699.
    13. Behrang, M.A. & Assareh, E. & Ghalambaz, M. & Assari, M.R. & Noghrehabadi, A.R., 2011. "Forecasting future oil demand in Iran using GSA (Gravitational Search Algorithm)," Energy, Elsevier, vol. 36(9), pages 5649-5654.
    14. Zhu, Y. & Huang, G.H. & Li, Y.P. & He, L. & Zhang, X.X., 2011. "An interval full-infinite mixed-integer programming method for planning municipal energy systems - A case study of Beijing," Applied Energy, Elsevier, vol. 88(8), pages 2846-2862, August.
    15. Lin, Q.G. & Huang, G.H., 2009. "A dynamic inexact energy systems planning model for supporting greenhouse-gas emission management and sustainable renewable energy development under uncertainty--A case study for the City of Waterloo,," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1836-1853, October.
    16. Lin, Q.G. & Huang, G.H., 2009. "Planning of energy system management and GHG-emission control in the Municipality of Beijing--An inexact-dynamic stochastic programming model," Energy Policy, Elsevier, vol. 37(11), pages 4463-4473, November.
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    18. Cao, M.F. & Huang, G.H. & Lin, Q.G., 2010. "Integer programming with random-boundary intervals for planning municipal power systems," Applied Energy, Elsevier, vol. 87(8), pages 2506-2516, August.

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