IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v134y2017icp893-901.html
   My bibliography  Save this article

A goal programming based model system for community energy plan

Author

Listed:
  • Huang, Zishuo
  • Yu, Hang
  • Chu, Xiangyang
  • Peng, Zhenwei

Abstract

Community energy system optimization model has great contribution to formulate community energy planning indexes. But an inappropriate response of uncertainty always makes such “optimal plan” work ended in nothing. It is still a herculean task to solve a hybrid programming model which contains stochastic and fuzzy parameters. In order to acquire more flexible and reliable energy planning indicators in a convenient way, a goal programming based model system (GPMS) is proposed to conduct dynamic variation analysis of community energy flow. GPMS contains general linear programming model, goal programming model and grey relational degree model for results analysis. General linear programming model is used to calculate optimal community energy flow on baseline situation. Deviational variables associated with each independent parameter and total fossil energy consumption (TFEC) are introduced in goal programming model. Many kinds of optimum community secondary energy flow maps can be acquired by adjusting the weight which has been given to TFEC’s deviation variables. The grey correlation degree, a measure of relevancy between two data series, is used to evaluate these optimum community energy flow results. At last, this GPMS for community energy plan is introduced, as well as a case study in Tianjin.

Suggested Citation

  • Huang, Zishuo & Yu, Hang & Chu, Xiangyang & Peng, Zhenwei, 2017. "A goal programming based model system for community energy plan," Energy, Elsevier, vol. 134(C), pages 893-901.
    • Handle: RePEc:eee:energy:v:134:y:2017:i:c:p:893-901
    DOI: 10.1016/j.energy.2017.06.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217310514
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.06.057?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. Mirakyan, Atom & De Guio, Roland, 2013. "Integrated energy planning in cities and territories: A review of methods and tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 289-297.
    2. Ahmed, Sajjad & Elsholkami, Mohamed & Elkamel, Ali & Du, Juan & Ydstie, Erik B. & Douglas, Peter L., 2014. "Financial risk management for new technology integration in energy planning under uncertainty," Applied Energy, Elsevier, vol. 128(C), pages 75-81.
    3. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    4. Hiremath, R.B. & Shikha, S. & Ravindranath, N.H., 2007. "Decentralized energy planning; modeling and application--a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(5), pages 729-752, June.
    5. Dylan Jones & Mehrdad Tamiz, 2010. "Practical Goal Programming," International Series in Operations Research and Management Science, Springer, edition 1, number 978-1-4419-5771-9, December.
    6. 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.
    7. Sperling, Karl & Hvelplund, Frede & Mathiesen, Brian Vad, 2011. "Centralisation and decentralisation in strategic municipal energy planning in Denmark," Energy Policy, Elsevier, vol. 39(3), pages 1338-1351, March.
    8. Huang, Zishuo & Yu, Hang & Peng, Zhenwei & Zhao, Mei, 2015. "Methods and tools for community energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1335-1348.
    9. Mendes, Gonçalo & Ioakimidis, Christos & Ferrão, Paulo, 2011. "On the planning and analysis of Integrated Community Energy Systems: A review and survey of available tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4836-4854.
    10. Hu, Qing & Huang, Guohe & Cai, Yanpeng & Huang, Ying, 2011. "Feasibility-based inexact fuzzy programming for electric power generation systems planning under dual uncertainties," Applied Energy, Elsevier, vol. 88(12), pages 4642-4654.
    11. Safaei, Amir & Freire, Fausto & Antunes, Carlos Henggeler, 2013. "A model for optimal energy planning of a commercial building integrating solar and cogeneration systems," Energy, Elsevier, vol. 61(C), pages 211-223.
    12. Sadri, A. & Ardehali, M.M. & Amirnekooei, K., 2014. "General procedure for long-term energy-environmental planning for transportation sector of developing countries with limited data based on LEAP (long-range energy alternative planning) and EnergyPLAN," Energy, Elsevier, vol. 77(C), pages 831-843.
    13. 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.
    14. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    15. Lund, Henrik & Werner, Sven & Wiltshire, Robin & Svendsen, Svend & Thorsen, Jan Eric & Hvelplund, Frede & Mathiesen, Brian Vad, 2014. "4th Generation District Heating (4GDH)," Energy, Elsevier, vol. 68(C), pages 1-11.
    16. Manfren, Massimiliano & Caputo, Paola & Costa, Gaia, 2011. "Paradigm shift in urban energy systems through distributed generation: Methods and models," Applied Energy, Elsevier, vol. 88(4), pages 1032-1048, April.
    17. Busch, Jonathan & Roelich, Katy & Bale, Catherine S.E. & Knoeri, Christof, 2017. "Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks," Energy Policy, Elsevier, vol. 100(C), pages 170-180.
    18. Bahramara, S. & Moghaddam, M. Parsa & Haghifam, M.R., 2016. "Optimal planning of hybrid renewable energy systems using HOMER: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 609-620.
    19. Kikuchi, Yasunori & Kimura, Seiichiro & Okamoto, Yoshitaka & Koyama, Michihisa, 2014. "A scenario analysis of future energy systems based on an energy flow model represented as functionals of technology options," Applied Energy, Elsevier, vol. 132(C), pages 586-601.
    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. Broz, Diego & Vanzetti, Nicolás & Corsano, Gabriela & Montagna, Jorge M., 2019. "Goal programming application for the decision support in the daily production planning of sawmills," Forest Policy and Economics, Elsevier, vol. 102(C), pages 29-40.
    2. Habib Zare & Mahyar Kamali Saraji & Madjid Tavana & Dalia Streimikiene & Fausto Cavallaro, 2021. "An Integrated Fuzzy Goal Programming—Theory of Constraints Model for Production Planning and Optimization," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    3. Huang, Zishuo & Yu, Hang & Chu, Xiangyang & Peng, Zhenwei, 2018. "A novel optimization model based on game tree for multi-energy conversion systems," Energy, Elsevier, vol. 150(C), pages 109-121.
    4. Gezen, Mesliha & Karaaslan, Abdulkerim, 2022. "Energy planning based on Vision-2023 of Turkey with a goal programming under fuzzy multi-objectives," Energy, Elsevier, vol. 261(PA).
    5. Ren, Hongbo & Wu, Qiong & Li, Qifen & Yang, Yongwen, 2020. "Optimal design and management of distributed energy network considering both efficiency and fairness," Energy, Elsevier, vol. 213(C).

    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. Huang, Zishuo & Yu, Hang & Peng, Zhenwei & Zhao, Mei, 2015. "Methods and tools for community energy planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1335-1348.
    2. Yazdanie, M. & Orehounig, K., 2021. "Advancing urban energy system planning and modeling approaches: Gaps and solutions in perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    3. Charani Shandiz, Saeid & Rismanchi, Behzad & Foliente, Greg, 2021. "Energy master planning for net-zero emission communities: State of the art and research challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    4. Rasmus Magni Johannsen & Poul Alberg Østergaard & David Maya-Drysdale & Louise Krog Elmegaard Mouritsen, 2021. "Designing Tools for Energy System Scenario Making in Municipal Energy Planning," Energies, MDPI, vol. 14(5), pages 1-17, March.
    5. Chang, Miguel & Thellufsen, Jakob Zink & Zakeri, Behnam & Pickering, Bryn & Pfenninger, Stefan & Lund, Henrik & Østergaard, Poul Alberg, 2021. "Trends in tools and approaches for modelling the energy transition," Applied Energy, Elsevier, vol. 290(C).
    6. Bouw, Kathelijne & Noorman, Klaas Jan & Wiekens, Carina J. & Faaij, André, 2021. "Local energy planning in the built environment: An analysis of model characteristics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    7. Gopisetty, Satya & Treffinger, Peter & Reindl, Leonhard Michael, 2017. "Open-source energy planning tool with easy-to-parameterize components for the conception of polygeneration systems," Energy, Elsevier, vol. 126(C), pages 756-765.
    8. David Drysdale & Brian Vad Mathiesen & Henrik Lund, 2019. "From Carbon Calculators to Energy System Analysis in Cities," Energies, MDPI, vol. 12(12), pages 1-21, June.
    9. Scheller, Fabian & Bruckner, Thomas, 2019. "Energy system optimization at the municipal level: An analysis of modeling approaches and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 444-461.
    10. Rae, Callum & Kerr, Sandy & Maroto-Valer, M. Mercedes, 2020. "Upscaling smart local energy systems: A review of technical barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    11. Ma, Weiwu & Xue, Xinpei & Liu, Gang, 2018. "Techno-economic evaluation for hybrid renewable energy system: Application and merits," Energy, Elsevier, vol. 159(C), pages 385-409.
    12. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    13. Fuchs, Marcus & Teichmann, Jens & Lauster, Moritz & Remmen, Peter & Streblow, Rita & Müller, Dirk, 2016. "Workflow automation for combined modeling of buildings and district energy systems," Energy, Elsevier, vol. 117(P2), pages 478-484.
    14. Omu, Akomeno & Choudhary, Ruchi & Boies, Adam, 2013. "Distributed energy resource system optimisation using mixed integer linear programming," Energy Policy, Elsevier, vol. 61(C), pages 249-266.
    15. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    16. Huang, Zishuo & Yu, Hang & Peng, Zhenwei & Feng, Yifu, 2017. "Planning community energy system in the industry 4.0 era: Achievements, challenges and a potential solution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 710-721.
    17. Mirakyan, Atom & De Guio, Roland, 2013. "Integrated energy planning in cities and territories: A review of methods and tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 289-297.
    18. Bruno Domenech & Laia Ferrer‐Martí & Rafael Pastor, 2019. "Comparison of various approaches to design wind‐PV rural electrification projects in remote areas of developing countries," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(3), May.
    19. Allegrini, Jonas & Orehounig, Kristina & Mavromatidis, Georgios & Ruesch, Florian & Dorer, Viktor & Evins, Ralph, 2015. "A review of modelling approaches and tools for the simulation of district-scale energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1391-1404.
    20. Zakeri, Behnam & Syri, Sanna & Rinne, Samuli, 2015. "Higher renewable energy integration into the existing energy system of Finland – Is there any maximum limit?," Energy, Elsevier, vol. 92(P3), pages 244-259.

    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:134:y:2017:i:c:p:893-901. 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.