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An inexact two-stage fractional energy systems planning model

Author

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  • Song, Tangnyu
  • Huang, Guohe
  • Zhou, Xiong
  • Wang, Xiuquan
Abstract
In this study, an inexact two-stage fractional energy systems planning model (ITF-ESP) is developed through an integration of interval-parameter programming (IPP), two-stage stochastic programming (TSP), fractional programming (FP), and mixed integer linear programming (MILP) methods. Since the proposed model could not be solved directly, it is converted into two interactive sub-models. In order to obtain more precise interval solutions, the sub-model corresponding to f−is solved first. The developed ITF-ESP model is considered as an efficient approach to address dual-objective optimization problems involving capacity expansion issues and policy scenario analysis, as well as uncertainties described as intervals and probability distributions. Effectiveness of the ITF-ESP model is demonstrated through a case study within a Chinese context. The results indicate that although the non-renewable technologies would still play a major role in electricity generation, the renewable technologies are becoming increasingly significant. Comparisons of the ITF-ESP model and the least-cost model are conducted to illustrate the advantages of the proposed ITF-ESP model in reflecting trade-offs between economic development and environmental protection. In addition, compared with the chance-constrained two-stage fractional optimization model (CTFO), interval solutions obtained from the ITF-ESP model can provide multiple alternative management plans in terms of electricity generation and capacity expansion.

Suggested Citation

  • Song, Tangnyu & Huang, Guohe & Zhou, Xiong & Wang, Xiuquan, 2018. "An inexact two-stage fractional energy systems planning model," Energy, Elsevier, vol. 160(C), pages 275-289.
    • Handle: RePEc:eee:energy:v:160:y:2018:i:c:p:275-289
    DOI: 10.1016/j.energy.2018.06.158
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    References listed on IDEAS

    as
    1. Shimazaki, Yoichi & Akisawa, Atsushi & Kashiwagi, Takao, 2000. "A model analysis of clean development mechanisms to reduce both CO2 and SO2 emissions between Japan and China," Applied Energy, Elsevier, vol. 66(4), pages 311-324, August.
    2. Mahbub, Md Shahriar & Cozzini, Marco & Østergaard, Poul Alberg & Alberti, Fabrizio, 2016. "Combining multi-objective evolutionary algorithms and descriptive analytical modelling in energy scenario design," Applied Energy, Elsevier, vol. 164(C), pages 140-151.
    3. Zhu, H. & Huang, W.W. & Huang, G.H., 2014. "Planning of regional energy systems: An inexact mixed-integer fractional programming model," Applied Energy, Elsevier, vol. 113(C), pages 500-514.
    4. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Lin, Q.G. & Tan, Q., 2009. "Community-scale renewable energy systems planning under uncertainty--An interval chance-constrained programming approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(4), pages 721-735, May.
    5. Ippolito, M.G. & Di Silvestre, M.L. & Riva Sanseverino, E. & Zizzo, G. & Graditi, G., 2014. "Multi-objective optimized management of electrical energy storage systems in an islanded network with renewable energy sources under different design scenarios," Energy, Elsevier, vol. 64(C), pages 648-662.
    6. Denholm, Paul & Margolis, Robert M., 2007. "Evaluating the limits of solar photovoltaics (PV) in electric power systems utilizing energy storage and other enabling technologies," Energy Policy, Elsevier, vol. 35(9), pages 4424-4433, September.
    7. Dincer, Ibrahim, 2000. "Renewable energy and sustainable development: a crucial review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 4(2), pages 157-175, June.
    8. Fadaee, M. & Radzi, M.A.M., 2012. "Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3364-3369.
    9. 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.
    10. Ahmadi, Pouria & Rosen, Marc A. & Dincer, Ibrahim, 2012. "Multi-objective exergy-based optimization of a polygeneration energy system using an evolutionary algorithm," Energy, Elsevier, vol. 46(1), pages 21-31.
    11. Greening, Lorna A. & Bernow, Steve, 2004. "Design of coordinated energy and environmental policies: use of multi-criteria decision-making," Energy Policy, Elsevier, vol. 32(6), pages 721-735, April.
    12. Turton, Hal & Barreto, Leonardo, 2006. "Long-term security of energy supply and climate change," Energy Policy, Elsevier, vol. 34(15), pages 2232-2250, October.
    13. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "Planning regional energy system in association with greenhouse gas mitigation under uncertainty," Applied Energy, Elsevier, vol. 88(3), pages 599-611, March.
    14. Mavrotas, George & Florios, Kostas & Vlachou, Dimitra, 2010. "Energy planning of a hospital using Mathematical Programming and Monte Carlo simulation for dealing with uncertainty in the economic parameters," MPRA Paper 105754, University Library of Munich, Germany.
    15. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    16. Zhang, X.Y. & Huang, G.H. & Zhu, H. & Li, Y.P., 2017. "A fuzzy-stochastic power system planning model: Reflection of dual objectives and dual uncertainties," Energy, Elsevier, vol. 123(C), pages 664-676.
    17. Shimoda, Yoshiyuki & Yamaguchi, Yukio & Okamura, Tomo & Taniguchi, Ayako & Yamaguchi, Yohei, 2010. "Prediction of greenhouse gas reduction potential in Japanese residential sector by residential energy end-use model," Applied Energy, Elsevier, vol. 87(6), pages 1944-1952, June.
    18. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    19. Keirstead, James & Jennings, Mark & Sivakumar, Aruna, 2012. "A review of urban energy system models: Approaches, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3847-3866.
    20. Hall, Peter J. & Bain, Euan J., 2008. "Energy-storage technologies and electricity generation," Energy Policy, Elsevier, vol. 36(12), pages 4352-4355, December.
    21. 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.
    22. Vahidinasab, Vahid, 2014. "Optimal distributed energy resources planning in a competitive electricity market: Multiobjective optimization and probabilistic design," Renewable Energy, Elsevier, vol. 66(C), pages 354-363.
    23. Chen, Fang & Huang, Guohe & Fan, Yurui, 2015. "A linearization and parameterization approach to tri-objective linear programming problems for power generation expansion planning," Energy, Elsevier, vol. 87(C), pages 240-250.
    24. Denholm, Paul & Margolis, Robert M., 2007. "Evaluating the limits of solar photovoltaics (PV) in traditional electric power systems," Energy Policy, Elsevier, vol. 35(5), pages 2852-2861, May.
    25. Zhou, Xiong & Huang, Guohe & Zhu, Hua & Chen, Jiapei & Xu, Jinliang, 2015. "Chance-constrained two-stage fractional optimization for planning regional energy systems in British Columbia, Canada," Applied Energy, Elsevier, vol. 154(C), pages 663-677.
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