IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v35y2007i11p5643-5655.html
   My bibliography  Save this article

Fuzzy possibilistic model for medium-term power generation planning with environmental criteria

Author

Listed:
  • Muela, E.
  • Schweickardt, G.
  • Garces, F.

Abstract

No abstract is available for this item.

Suggested Citation

  • Muela, E. & Schweickardt, G. & Garces, F., 2007. "Fuzzy possibilistic model for medium-term power generation planning with environmental criteria," Energy Policy, Elsevier, vol. 35(11), pages 5643-5655, November.
  • Handle: RePEc:eee:enepol:v:35:y:2007:i:11:p:5643-5655
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(07)00218-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Soderholm, Patrik & Sundqvist, Thomas, 2003. "Pricing environmental externalities in the power sector: ethical limits and implications for social choice," Ecological Economics, Elsevier, vol. 46(3), pages 333-350, October.
    3. Nelson, Richard R., 2008. "Bounded rationality, cognitive maps, and trial and error learning," Journal of Economic Behavior & Organization, Elsevier, vol. 67(1), pages 78-89, July.
    4. 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.
    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. 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.
    2. 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.
    3. Nie, S. & Huang, Z.C. & Huang, G.H. & Yu, L. & Liu, J., 2018. "Optimization of electric power systems with cost minimization and environmental-impact mitigation under multiple uncertainties," Applied Energy, Elsevier, vol. 221(C), pages 249-267.
    4. Dong, C. & Huang, G.H. & Cai, Y.P. & Xu, Y., 2011. "An interval-parameter minimax regret programming approach for power management systems planning under uncertainty," Applied Energy, Elsevier, vol. 88(8), pages 2835-2845, August.
    5. Nie, S. & Li, Y.P. & Liu, J. & Huang, Charley Z., 2017. "Risk management of energy system for identifying optimal power mix with financial-cost minimization and environmental-impact mitigation under uncertainty," Energy Economics, Elsevier, vol. 61(C), pages 313-329.
    6. Dzene, Ilze & Rošā, Marika & Blumberga, Dagnija, 2011. "How to select appropriate measures for reductions in negative environmental impact? Testing a screening method on a regional energy system," Energy, Elsevier, vol. 36(4), pages 1878-1883.
    7. Chen, F. & Huang, G.H. & Fan, Y.R. & Chen, J.P., 2017. "A copula-based fuzzy chance-constrained programming model and its application to electric power generation systems planning," Applied Energy, Elsevier, vol. 187(C), pages 291-309.
    8. Wang, Xingwei & Cai, Yanpeng & Chen, Jiajun & Dai, Chao, 2013. "A grey-forecasting interval-parameter mixed-integer programming approach for integrated electric-environmental management–A case study of Beijing," Energy, Elsevier, vol. 63(C), pages 334-344.
    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. 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.
    11. Li, Y.F. & Huang, G.H. & Li, Y.P. & Xu, Y. & Chen, W.T., 2010. "Regional-scale electric power system planning under uncertainty--A multistage interval-stochastic integer linear programming approach," Energy Policy, Elsevier, vol. 38(1), pages 475-490, January.
    12. Jin, S.W. & Li, Y.P. & Huang, G.H. & Nie, S., 2018. "Analyzing the performance of clean development mechanism for electric power systems under uncertain environment," Renewable Energy, Elsevier, vol. 123(C), pages 382-397.
    13. Zhang, Xiaodong & Huang, Guo H. & Nie, Xianghui, 2009. "Optimal decision schemes for agricultural water quality management planning with imprecise objective," Agricultural Water Management, Elsevier, vol. 96(12), pages 1723-1731, December.
    14. 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.
    15. Zhu, Y. & Li, Y.P. & Huang, G.H., 2012. "Planning municipal-scale energy systems under functional interval uncertainties," Renewable Energy, Elsevier, vol. 39(1), pages 71-84.
    16. Pizarro-Alonso, Amalia & Ravn, Hans & Münster, Marie, 2019. "Uncertainties towards a fossil-free system with high integration of wind energy in long-term planning," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    17. Yu, L. & Li, Y.P. & Huang, G.H., 2016. "A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China," Energy, Elsevier, vol. 98(C), pages 190-203.
    18. Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
    19. 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.
    20. 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.
    21. 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.
    22. Deveci, Kaan & Güler, Önder, 2020. "A CMOPSO based multi-objective optimization of renewable energy planning: Case of Turkey," Renewable Energy, Elsevier, vol. 155(C), pages 578-590.
    23. Jin, S.W. & Li, Y.P. & Nie, S. & Sun, J., 2017. "The potential role of carbon capture and storage technology in sustainable electric-power systems under multiple uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 467-480.
    24. 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.

    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. Vuciterna, Rina & Thomsen, Michael & Popp, Jennie & Musliu, Arben, 2017. "Efficiency and Competitiveness of Kosovo Raspberry Producers," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252770, Southern Agricultural Economics Association.
    2. Collan, Mikael, 2008. "New Method for Real Option Valuation Using Fuzzy Numbers," Working Papers 466, IAMSR, Åbo Akademi.
    3. Wenyao Niu & Yuan Rong & Liying Yu & Lu Huang, 2022. "A Novel Hybrid Group Decision Making Approach Based on EDAS and Regret Theory under a Fermatean Cubic Fuzzy Environment," Mathematics, MDPI, vol. 10(17), pages 1-30, August.
    4. de Andres-Sanchez, Jorge, 2007. "Claim reserving with fuzzy regression and Taylor's geometric separation method," Insurance: Mathematics and Economics, Elsevier, vol. 40(1), pages 145-163, January.
    5. Mikhailov, L., 2004. "A fuzzy approach to deriving priorities from interval pairwise comparison judgements," European Journal of Operational Research, Elsevier, vol. 159(3), pages 687-704, December.
    6. Hongyi Sun & Bingqian Zhang & Wenbin Ni, 2022. "A Hybrid Model Based on SEM and Fuzzy TOPSIS for Supplier Selection," Mathematics, MDPI, vol. 10(19), pages 1-19, September.
    7. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
    8. Sakawa, Masatoshi & Kato, Kosuke, 1998. "An interactive fuzzy satisficing method for structured multiobjective linear fractional programs with fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 107(3), pages 575-589, June.
    9. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.
    10. Baudry, Gino & Delrue, Florian & Legrand, Jack & Pruvost, Jérémy & Vallée, Thomas, 2017. "The challenge of measuring biofuel sustainability: A stakeholder-driven approach applied to the French case," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 933-947.
    11. Bogdana Stanojević & Milan Stanojević & Sorin Nădăban, 2021. "Reinstatement of the Extension Principle in Approaching Mathematical Programming with Fuzzy Numbers," Mathematics, MDPI, vol. 9(11), pages 1-16, June.
    12. Svajone Bekesiene & Serhii Mashchenko, 2023. "On Nash Equilibria in a Finite Game for Fuzzy Sets of Strategies," Mathematics, MDPI, vol. 11(22), pages 1-12, November.
    13. Qian-Yun Tan & Cui-Ping Wei & Qi Liu & Xiang-Qian Feng, 2016. "The Hesitant Fuzzy Linguistic TOPSIS Method Based on Novel Information Measures," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(05), pages 1-22, October.
    14. Reinhard Madlener & Weiyu Gao & Ilja Neustadt & Peter Zweifel, 2008. "Promoting renewable electricity generation in imperfect markets: price vs. quantity policies," SOI - Working Papers 0809, Socioeconomic Institute - University of Zurich.
    15. Hsiao, Tzy-yih, 2006. "Establish standards of standard costing with the application of convergent gray zone test," European Journal of Operational Research, Elsevier, vol. 168(2), pages 593-611, January.
    16. Zola, Fernanda Cavicchioli & Colmenero, João Carlos & Aragão, Franciely Velozo & Rodrigues, Thaisa & Junior, Aldo Braghini, 2020. "Multicriterial model for selecting a charcoal kiln," Energy, Elsevier, vol. 190(C).
    17. Adel Hatami-Marbini & Madjid Tavana & Kobra Gholami & Zahra Ghelej Beigi, 2015. "A Bounded Data Envelopment Analysis Model in a Fuzzy Environment with an Application to Safety in the Semiconductor Industry," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 679-701, February.
    18. Manuel Casal-Guisande & Alberto Comesaña-Campos & Alejandro Pereira & José-Benito Bouza-Rodríguez & Jorge Cerqueiro-Pequeño, 2022. "A Decision-Making Methodology Based on Expert Systems Applied to Machining Tools Condition Monitoring," Mathematics, MDPI, vol. 10(3), pages 1-30, February.
    19. James Liou & Mei-Ling Chuang, 2010. "Evaluating corporate image and reputation using fuzzy MCDM approach in airline market," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(6), pages 1079-1091, October.
    20. Tan, Raymond R. & Aviso, Kathleen B. & Barilea, Ivan U. & Culaba, Alvin B. & Cruz, Jose B., 2012. "A fuzzy multi-regional input–output optimization model for biomass production and trade under resource and footprint constraints," Applied Energy, Elsevier, vol. 90(1), pages 154-160.

    More about this item

    Statistics

    Access and download statistics

    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:enepol:v:35:y:2007:i:11:p:5643-5655. 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.elsevier.com/locate/enpol .

    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.