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A hierarchical optimization approach to robust design of energy supply systems based on a mixed-integer linear model

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  • Yokoyama, Ryohei
  • Kamada, Hiroki
  • Shinano, Yuji
  • Wakui, Tetsuya

Abstract

In designing energy supply systems, designers should heighten the robustness in performance criteria against the uncertainty in energy demands. In this paper, a robust optimal design method using a hierarchical mixed-integer linear programming (MILP) method is proposed to maximize the robustness of energy supply systems under uncertain energy demands based on a mixed-integer linear model. A robust optimal design problem is formulated as a three-level min-max-min MILP one by expressing uncertain energy demands by intervals, evaluating the robustness in a performance criterion based on the minimax regret criterion, and considering relationships among integer design variables, uncertain energy demands, and integer and continuous operation variables. This problem is solved by evaluating upper and lower bounds for the minimum of the maximum regret of the performance criterion repeatedly outside, and evaluating lower and upper bounds for the maximum regret repeatedly inside. Different types of optimization problems are solved by applying a hierarchical MILP method developed for ordinary optimal design problems without and with its modifications. In a case study, the proposed approach is applied to the robust optimal design of a cogeneration system. Through the study, its validity and effectiveness are ascertained, and some features of the obtained robust designs are clarified.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:229:y:2021:i:c:s0360544221005922
    DOI: 10.1016/j.energy.2021.120343
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    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. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "Optimal design of distributed energy resource systems coupled with energy distribution networks," Energy, Elsevier, vol. 85(C), pages 433-448.
    3. 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.
    4. 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.
    5. 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.
    6. Kotireddy, Rajesh & Hoes, Pieter-Jan & Hensen, Jan L.M., 2018. "A methodology for performance robustness assessment of low-energy buildings using scenario analysis," Applied Energy, Elsevier, vol. 212(C), pages 428-442.
    7. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "An MILP (mixed integer linear programming) model for optimal design of district-scale distributed energy resource systems," Energy, Elsevier, vol. 90(P2), pages 1901-1915.
    8. Karmellos, M. & Georgiou, P.N. & Mavrotas, G., 2019. "A comparison of methods for the optimal design of Distributed Energy Systems under uncertainty," Energy, Elsevier, vol. 178(C), pages 318-333.
    9. 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.
    10. Dajun Yue & Jiyao Gao & Bo Zeng & Fengqi You, 2019. "A projection-based reformulation and decomposition algorithm for global optimization of a class of mixed integer bilevel linear programs," Journal of Global Optimization, Springer, vol. 73(1), pages 27-57, January.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
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