IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v36y2011i9p5677-5689.html
   My bibliography  Save this article

An interval-fuzzy two-stage stochastic programming model for planning carbon dioxide trading under uncertainty

Author

Listed:
  • Li, M.W.
  • Li, Y.P.
  • Huang, G.H.

Abstract

In this study, an IFTSP (interval-fuzzy two-stage stochastic programming) method is developed for planning carbon dioxide (CO2) emission trading under uncertainty. The developed IFTSP incorporates techniques of interval fuzzy linear programming and two-stage stochastic programming within a general optimization framework, which can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions and discrete intervals. The IFTSP cannot only tackle uncertainties expressed as probabilistic distributions and discrete intervals, but also provide an effective linkage between the pre-regulated CO2 mitigation policies and the associated economic implications. The developed model is applied to a case study of CO2-emission trading planning of industry systems under uncertainty, where three trading schemes are considered based on different trading participants. The results indicate that reasonable solutions have been generated. They are help for supporting: (a) formulation of desired GHG (greenhouse gas) mitigation policies under various economic and system-reliability constraints, (b) selection of the desired CO2-emission trading pattern, and (c) in-depth analysis of tradeoffs among system benefit, satisfaction degree, and CO2 mitigation under multiple uncertainties.

Suggested Citation

  • Li, M.W. & Li, Y.P. & Huang, G.H., 2011. "An interval-fuzzy two-stage stochastic programming model for planning carbon dioxide trading under uncertainty," Energy, Elsevier, vol. 36(9), pages 5677-5689.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:9:p:5677-5689
    DOI: 10.1016/j.energy.2011.06.058
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544211004440
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2011.06.058?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Iwata, Hiroki & Okada, Keisuke, 2010. "Greenhouse gas emissions and the role of the Kyoto Protocol," MPRA Paper 22299, University Library of Munich, Germany.
    2. Rehdanz, Katrin & Tol, Richard S.J., 2005. "Unilateral regulation of bilateral trade in greenhouse gas emission permits," Ecological Economics, Elsevier, vol. 54(4), pages 397-416, September.
    3. Huang, Guo H. & Baetz, Brian W. & Patry, Gilles G., 1995. "Grey integer programming: An application to waste management planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 83(3), pages 594-620, June.
    4. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "An interval-valued minimax-regret analysis approach for the identification of optimal greenhouse-gas abatement strategies under uncertainty," Energy Policy, Elsevier, vol. 39(7), pages 4313-4324, July.
    5. Ellerman,A. Denny & Buchner,Barbara K. & Carraro,Carlo (ed.), 2007. "Allocation in the European Emissions Trading Scheme," Cambridge Books, Cambridge University Press, number 9780521875684, October.
    6. Lin, Q.G. & Huang, G.H., 2010. "An inexact two-stage stochastic energy systems planning model for managing greenhouse gas emission at a municipal level," Energy, Elsevier, vol. 35(5), pages 2270-2280.
    7. Kuik, Onno & Mulder, Machiel, 2004. "Emissions trading and competitiveness: pros and cons of relative and absolute schemes," Energy Policy, Elsevier, vol. 32(6), pages 737-745, April.
    8. Copeland, Brian R. & Taylor, M. Scott, 2005. "Free trade and global warming: a trade theory view of the Kyoto protocol," Journal of Environmental Economics and Management, Elsevier, vol. 49(2), pages 205-234, March.
    9. Huang, G. H. & Baetz, B. W. & Patry, G. G., 1995. "Grey fuzzy integer programming: An application to regional waste management planning under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 29(1), pages 17-38, March.
    10. Chen, W.T. & Li, Y.P. & Huang, G.H. & Chen, X. & Li, Y.F., 2010. "A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty," Applied Energy, Elsevier, vol. 87(3), pages 1033-1047, March.
    11. Dale A. Carlson & Anne M. Sholtz, 1994. "Designing Pollution Market Instruments: Cases Of Uncertainty," Contemporary Economic Policy, Western Economic Association International, vol. 12(4), pages 114-125, October.
    12. A. Denny Ellerman & Ian Sue Wing, 2000. "Supplementarity: An Invitation to Monopsony?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 29-59.
    13. Jean-Baptiste, Philippe & Ducroux, Rene, 2003. "Energy policy and climate change," Energy Policy, Elsevier, vol. 31(2), pages 155-166, January.
    14. Birge, John R. & Louveaux, Francois V., 1988. "A multicut algorithm for two-stage stochastic linear programs," European Journal of Operational Research, Elsevier, vol. 34(3), pages 384-392, March.
    15. Vine, Edward & Kats, Gregory & Sathaye, Jayant & Joshi, Hemant, 2003. "International greenhouse gas trading programs: a discussion of measurement and accounting issues," Energy Policy, Elsevier, vol. 31(3), pages 211-224, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hao Yang & Wei He & Yu Li, 2022. "Optimization of Ecological Water Replenishment Scheme Based on the Interval Fuzzy Two-Stage Stochastic Programming Method: Boluo Lake National Nature Reserve, Jilin Province, China," IJERPH, MDPI, vol. 19(9), pages 1-17, April.
    2. Guangxiao Hu & Xiaoming Ma & Junping Ji, 2017. "A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China," Sustainability, MDPI, vol. 9(11), pages 1-12, October.
    3. Cristóbal, Jorge & Guillén-Gosálbez, Gonzalo & Kraslawski, Andrzej & Irabien, Angel, 2013. "Stochastic MILP model for optimal timing of investments in CO2 capture technologies under uncertainty in prices," Energy, Elsevier, vol. 54(C), pages 343-351.
    4. Federica Cucchiella & Idiano D Adamo & Massimo Gastaldi, 2015. "Profitability Analysis for Biomethane: A Strategic Role in the Italian Transport Sector," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 440-449.
    5. Piao, M.J. & Li, Y.P. & Huang, G.H. & Nie, S., 2015. "Risk analysis for Shanghai's electric power system under multiple uncertainties," Energy, Elsevier, vol. 87(C), pages 104-119.
    6. Noshchenko, Olga & Hagspiel, Verena, 2024. "Environmental and economic multi-objective real options analysis: Electrification choices for field development investment planning," Energy, Elsevier, vol. 295(C).
    7. Zhu, Y. & Li, Y.P. & Huang, G.H. & Fu, D.Z., 2013. "Modeling for planning municipal electric power systems associated with air pollution control – A case study of Beijing," Energy, Elsevier, vol. 60(C), pages 168-186.
    8. Liang, M.S. & Huang, G.H. & Chen, J.P. & Li, Y.P., 2022. "Development of non-deterministic energy-water-carbon nexus planning model: A case study of Shanghai, China," Energy, Elsevier, vol. 246(C).
    9. Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "GHG-mitigation oriented and coal-consumption constrained inexact robust model for regional energy structure adjustment – A case study for Jiangsu Province, China," Renewable Energy, Elsevier, vol. 123(C), pages 549-562.
    10. Jarmila Zimmermannová, 2015. "Pilot Analysis of the Behaviour of Companies Within the 3rd Trading Period of the EU ETS in the Czech Republic," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(6), pages 2213-2220.
    11. Petr Cermak & Jarmila Zimmermannova & Jan Lavrincik & Miroslav Pokorny & Jiri Martinu, 2015. "The Broker Simulation Model in the Emission Allowances Trading Area," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 80-95.
    12. Zhu, Y. & Li, Y.P. & Huang, G.H., 2013. "Planning carbon emission trading for Beijing's electric power systems under dual uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 113-128.
    13. Jiang, Jingjing & Xie, Dejun & Ye, Bin & Shen, Bo & Chen, Zhanming, 2016. "Research on China’s cap-and-trade carbon emission trading scheme: Overview and outlook," Applied Energy, Elsevier, vol. 178(C), pages 902-917.
    14. Anjos, Miguel F. & Feijoo, Felipe & Sankaranarayanan, Sriram, 2022. "A multinational carbon-credit market integrating distinct national carbon allowance strategies," Applied Energy, Elsevier, vol. 319(C).
    15. Tsai, Wen-Hsien & Lee, Kuen-Chang & Liu, Jau-Yang & Lin, Hsiu-Ling & Chou, Yu-Wei & Lin, Sin-Jin, 2012. "A mixed activity-based costing decision model for green airline fleet planning under the constraints of the European Union Emissions Trading Scheme," Energy, Elsevier, vol. 39(1), pages 218-226.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Y.P. & Huang, G.H. & Li, M.W., 2014. "An integrated optimization modeling approach for planning emission trading and clean-energy development under uncertainty," Renewable Energy, Elsevier, vol. 62(C), pages 31-46.
    2. Chen, W.T. & Li, Y.P. & Huang, G.H. & Chen, X. & Li, Y.F., 2010. "A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty," Applied Energy, Elsevier, vol. 87(3), pages 1033-1047, March.
    3. Zhou, Y. & Li, Y.P. & Huang, G.H., 2015. "Planning sustainable electric-power system with carbon emission abatement through CDM under uncertainty," Applied Energy, Elsevier, vol. 140(C), pages 350-364.
    4. Zhu, Y. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Nie, S., 2015. "A dynamic model to optimize municipal electric power systems by considering carbon emission trading under uncertainty," Energy, Elsevier, vol. 88(C), pages 636-649.
    5. Chen, C. & Li, Y.P. & Huang, G.H., 2013. "An inexact robust optimization method for supporting carbon dioxide emissions management in regional electric-power systems," Energy Economics, Elsevier, vol. 40(C), pages 441-456.
    6. Li, Y.P. & Huang, G.H. & Chen, X., 2011. "An interval-valued minimax-regret analysis approach for the identification of optimal greenhouse-gas abatement strategies under uncertainty," Energy Policy, Elsevier, vol. 39(7), pages 4313-4324, July.
    7. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    8. 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.
    9. Liang, M.S. & Huang, G.H. & Chen, J.P. & Li, Y.P., 2022. "Development of non-deterministic energy-water-carbon nexus planning model: A case study of Shanghai, China," Energy, Elsevier, vol. 246(C).
    10. Maqsood, Imran & Huang, Guo H. & Scott Yeomans, Julian, 2005. "An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 208-225, November.
    11. Chen, C. & Li, Y.P. & Huang, G.H., 2016. "Interval-fuzzy municipal-scale energy model for identification of optimal strategies for energy management – A case study of Tianjin, China," Renewable Energy, Elsevier, vol. 86(C), pages 1161-1177.
    12. 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.
    13. Simic, Vladimir, 2016. "End-of-life vehicles allocation management under multiple uncertainties: An interval-parameter two-stage stochastic full-infinite programming approach," Resources, Conservation & Recycling, Elsevier, vol. 114(C), pages 1-17.
    14. 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.
    15. 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.
    16. Zhu, Y. & Li, Y.P. & Huang, G.H., 2013. "Planning carbon emission trading for Beijing's electric power systems under dual uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 113-128.
    17. Liu, Y. & Huang, G.H. & Cai, Y.P. & Cheng, G.H. & Niu, Y.T. & An, K., 2009. "Development of an inexact optimization model for coupled coal and power management in North China," Energy Policy, Elsevier, vol. 37(11), pages 4345-4363, November.
    18. 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.
    19. Chen, C. & Li, Y.P. & Huang, G.H. & Zhu, Y., 2012. "An inexact robust nonlinear optimization method for energy systems planning under uncertainty," Renewable Energy, Elsevier, vol. 47(C), pages 55-66.
    20. Piao, M.J. & Li, Y.P. & Huang, G.H. & Nie, S., 2015. "Risk analysis for Shanghai's electric power system under multiple uncertainties," Energy, Elsevier, vol. 87(C), pages 104-119.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:36:y:2011:i:9:p:5677-5689. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.