IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v137y2017icp878-887.html
   My bibliography  Save this article

Performance comparison of energy supply systems under uncertain energy demands based on a mixed-integer linear model

Author

Listed:
  • Yokoyama, Ryohei
  • Nakamura, Ryo
  • Wakui, Tetsuya

Abstract

In designing energy supply systems, several alternatives for design specifications are proposed, and their performances are evaluated and compared. In this paper, a method of comparing performances of two energy supply systems under uncertain energy demands is proposed based on a mixed-integer linear model. Uncertain energy demands are expressed by intervals. The minimum and maximum, and consequently their interval of the difference in the value of a performance criterion are evaluated for all the possible energy demands within their intervals. An optimization problem for this evaluation is formulated as a minimax mixed-integer linear programming one with integer and continuous operation variables. The problem is solved by evaluating upper and lower bounds for the optimal value of the difference in the value of the performance criterion repeatedly. In a case study, the minimum and maximum of the reduction in the annual total cost of a cogeneration system in comparison with a conventional energy supply system are evaluated, and the corresponding energy demands and operational strategies are identified. The influence of the uncertainty in energy demands on these results is also examined. Through the case study, the validity and effectiveness of the proposed method are clarified.

Suggested Citation

  • Yokoyama, Ryohei & Nakamura, Ryo & Wakui, Tetsuya, 2017. "Performance comparison of energy supply systems under uncertain energy demands based on a mixed-integer linear model," Energy, Elsevier, vol. 137(C), pages 878-887.
    • Handle: RePEc:eee:energy:v:137:y:2017:i:c:p:878-887
    DOI: 10.1016/j.energy.2017.03.149
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421730542X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.03.149?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. 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.
    2. Ashouri, Araz & Petrini, Flavio & Bornatico, Raffaele & Benz, Michael J., 2014. "Sensitivity analysis for robust design of building energy systems," Energy, Elsevier, vol. 76(C), pages 264-275.
    3. T. Assavapokee & M. J. Realff & J. C. Ammons, 2008. "Min-Max Regret Robust Optimization Approach on Interval Data Uncertainty," Journal of Optimization Theory and Applications, Springer, vol. 137(2), pages 297-316, May.
    4. Sauleh Siddiqui & Steven A Gabriel & Shapour Azarm, 2015. "Solving mixed-integer robust optimization problems with interval uncertainty using Benders decomposition," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(4), pages 664-673, April.
    5. 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.
    6. Gustafsson, Stig-Inge, 1998. "Sensitivity analysis of building energy retrofits," Applied Energy, Elsevier, vol. 61(1), pages 13-23, September.
    7. Wang, Jiangjiang & Zhai, Zhiqiang (John) & Jing, Youyin & Zhang, Xutao & Zhang, Chunfa, 2011. "Sensitivity analysis of optimal model on building cooling heating and power system," Applied Energy, Elsevier, vol. 88(12), pages 5143-5152.
    8. 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.
    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. Yokoyama, Ryohei & Tokunaga, Akira & Wakui, Tetsuya, 2018. "Robust optimal design of energy supply systems under uncertain energy demands based on a mixed-integer linear model," Energy, Elsevier, vol. 153(C), pages 159-169.
    2. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Weng, Peifen & Ren, Jianxing, 2018. "Coupling optimization of urban spatial structure and neighborhood-scale distributed energy systems," Energy, Elsevier, vol. 144(C), pages 472-481.

    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. Yokoyama, Ryohei & Tokunaga, Akira & Wakui, Tetsuya, 2018. "Robust optimal design of energy supply systems under uncertain energy demands based on a mixed-integer linear model," Energy, Elsevier, vol. 153(C), pages 159-169.
    2. Yokoyama, Ryohei & Kamada, Hiroki & Shinano, Yuji & Wakui, Tetsuya, 2021. "A hierarchical optimization approach to robust design of energy supply systems based on a mixed-integer linear model," Energy, Elsevier, vol. 229(C).
    3. Jungho Park & Hadi El-Amine & Nevin Mutlu, 2021. "An Exact Algorithm for Large-Scale Continuous Nonlinear Resource Allocation Problems with Minimax Regret Objectives," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1213-1228, July.
    4. Lu, Yuehong & Wang, Shengwei & Yan, Chengchu & Shan, Kui, 2015. "Impacts of renewable energy system design inputs on the performance robustness of net zero energy buildings," Energy, Elsevier, vol. 93(P2), pages 1595-1606.
    5. Henao, Felipe & Rodriguez, Yeny & Viteri, Juan Pablo & Dyner, Isaac, 2019. "Optimising the insertion of renewables in the Colombian power sector," Renewable Energy, Elsevier, vol. 132(C), pages 81-92.
    6. 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.
    7. Pang, Zhihong & O'Neill, Zheng, 2018. "Uncertainty quantification and sensitivity analysis of the domestic hot water usage in hotels," Applied Energy, Elsevier, vol. 232(C), pages 424-442.
    8. Henao, Felipe & Dyner, Isaac, 2020. "Renewables in the optimal expansion of colombian power considering the Hidroituango crisis," Renewable Energy, Elsevier, vol. 158(C), pages 612-627.
    9. Majewski, Dinah Elena & Lampe, Matthias & Voll, Philip & Bardow, André, 2017. "TRusT: A Two-stage Robustness Trade-off approach for the design of decentralized energy supply systems," Energy, Elsevier, vol. 118(C), pages 590-599.
    10. Soon-Ryul Nam & Sang-Hee Kang & Joo-Ho Lee & Eun-Jae Choi & Seon-Ju Ahn & Joon-Ho Choi, 2013. "EMS-Data-Based Load Modeling to Evaluate the Effect of Conservation Voltage Reduction at a National Level," Energies, MDPI, vol. 6(8), pages 1-14, July.
    11. Sandrine Mathy & Patrick Criqui & Katharina Knoop & Manfred Fischedick & Sascha Samadi, 2016. "Uncertainty management and the dynamic adjustment of deep decarbonization pathways," Climate Policy, Taylor & Francis Journals, vol. 16(sup1), pages 47-62, June.
    12. Cai, Yanpeng & Applegate, Scott & Yue, Wencong & Cai, Jianying & Wang, Xuan & Liu, Gengyuan & Li, Chunhui, 2017. "A hybrid life cycle and multi-criteria decision analysis approach for identifying sustainable development strategies of Beijing's taxi fleet," Energy Policy, Elsevier, vol. 100(C), pages 314-325.
    13. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).
    14. Unai Aldasoro & María Merino & Gloria Pérez, 2019. "Time consistent expected mean-variance in multistage stochastic quadratic optimization: a model and a matheuristic," Annals of Operations Research, Springer, vol. 280(1), pages 151-187, September.
    15. 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.
    16. 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.
    17. Anca N. Iuga (Butnariu) & Vasile N. Popa & Luminița I. Popa, 2018. "Comparative Analysis of Automotive Products Regarding the Influence of Eco-Friendly Methods to Emissions’ Reduction," Energies, MDPI, vol. 12(1), pages 1-24, December.
    18. Jeon, Jun-Seo & Lee, Seung-Rae & Pasquinelli, Lisa & Fabricius, Ida Lykke, 2015. "Sensitivity analysis of recovery efficiency in high-temperature aquifer thermal energy storage with single well," Energy, Elsevier, vol. 90(P2), pages 1349-1359.
    19. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    20. Yildiz, Yusuf & Korkmaz, Koray & Göksal Özbalta, Türkan & Durmus Arsan, Zeynep, 2012. "An approach for developing sensitive design parameter guidelines to reduce the energy requirements of low-rise apartment buildings," Applied Energy, Elsevier, vol. 93(C), pages 337-347.

    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:137:y:2017:i:c:p:878-887. 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.