IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v118y2017icp590-599.html
   My bibliography  Save this article

TRusT: A Two-stage Robustness Trade-off approach for the design of decentralized energy supply systems

Author

Listed:
  • Majewski, Dinah Elena
  • Lampe, Matthias
  • Voll, Philip
  • Bardow, André

Abstract

The design of decentralized energy supply systems is a complex task and thus best addressed by mathematical optimization. However, design problems typically rely on uncertain input data, such as future energy demands or prices. Still, conventional optimization models are usually deterministic and thus neglect uncertainties. For this reason, the deterministic optimal solution is in general suboptimal or even infeasible. Robust design methods are available to guarantee security of energy supply, however, they usually lead to significant additional costs. In this work, we show that energy supply systems with guaranteed secure energy supply are not expensive per se. For this purpose, we propose the Two-stage Robustness Trade-off (TRusT) approach. The TRusT approach considers the trade-off between expected costs in the nominal scenario and costs in the worst case while guaranteeing security of energy supply. Thereby, the TRusT approach identifies balanced robust energy supply systems which are cost-efficient in both the daily business and the worst case. The TRusT approach can be applied and solved efficiently. In a case study, we identify robust design options which ensure security of energy supply at low additional costs. Hence, the TRusT approach is a suitable tool to design cost-efficient and secure energy systems.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:118:y:2017:i:c:p:590-599
    DOI: 10.1016/j.energy.2016.10.065
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216314992
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2016.10.065?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. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    3. 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.
    4. Sy, Charlle L. & Aviso, Kathleen B. & Ubando, Aristotle T. & Tan, Raymond R., 2016. "Target-oriented robust optimization of polygeneration systems under uncertainty," Energy, Elsevier, vol. 116(P2), pages 1334-1347.
    5. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    6. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
    7. Voll, Philip & Klaffke, Carsten & Hennen, Maike & Bardow, André, 2013. "Automated superstructure-based synthesis and optimization of distributed energy supply systems," Energy, Elsevier, vol. 50(C), pages 374-388.
    8. Månsson, André & Johansson, Bengt & Nilsson, Lars J., 2014. "Assessing energy security: An overview of commonly used methodologies," Energy, Elsevier, vol. 73(C), pages 1-14.
    9. Ji, L. & Niu, D.X. & Huang, G.H., 2014. "An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand," Energy, Elsevier, vol. 67(C), pages 186-199.
    10. Kaundinya, Deepak Paramashivan & Balachandra, P. & Ravindranath, N.H., 2009. "Grid-connected versus stand-alone energy systems for decentralized power--A review of literature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2041-2050, October.
    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 & 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).
    2. Jing, Rui & Kuriyan, Kamal & Kong, Qingyuan & Zhang, Zhihui & Shah, Nilay & Li, Ning & Zhao, Yingru, 2019. "Exploring the impact space of different technologies using a portfolio constraint based approach for multi-objective optimization of integrated urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    3. Wissocq, Thibaut & Ghazouani, Sami & Le Bourdiec, Solène, 2019. "A methodology for designing thermodynamic energy conversion systems in industrial mass/heat integration problems based on MILP models," Energy, Elsevier, vol. 185(C), pages 121-135.
    4. Petkov, Ivalin & Gabrielli, Paolo & Spokaite, Marija, 2021. "The impact of urban district composition on storage technology reliance: trade-offs between thermal storage, batteries, and power-to-hydrogen," Energy, Elsevier, vol. 224(C).
    5. 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.
    6. 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.
    7. Tao Zhang & Minli Wang & Peihong Wang & Junyu Liang, 2020. "Optimal Design of a Combined Cooling, Heating, and Power System and Its Ability to Adapt to Uncertainty," Energies, MDPI, vol. 13(14), pages 1-17, July.
    8. Wang, Yongli & Wang, Yudong & Huang, Yujing & Li, Fang & Zeng, Ming & Li, Jiapu & Wang, Xiaohai & Zhang, Fuwei, 2019. "Planning and operation method of the regional integrated energy system considering economy and environment," Energy, Elsevier, vol. 171(C), pages 731-750.
    9. Urban, Kristof L. & Scheller, Fabian & Bruckner, Thomas, 2021. "Suitability assessment of models in the industrial energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    10. Niu, Jide & Li, Xiaoyuan & Tian, Zhe & Yang, Hongxing, 2023. "A framework for quantifying the value of information to mitigate risk in the optimal design of distributed energy systems under uncertainty," Applied Energy, Elsevier, vol. 350(C).
    11. Groissböck, Markus, 2019. "Are open source energy system optimization tools mature enough for serious use?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 234-248.
    12. Petkov, Ivalin & Gabrielli, Paolo, 2020. "Power-to-hydrogen as seasonal energy storage: an uncertainty analysis for optimal design of low-carbon multi-energy systems," Applied Energy, Elsevier, vol. 274(C).
    13. Pickering, Bryn & Choudhary, Ruchi, 2021. "Quantifying resilience in energy systems with out-of-sample testing," Applied Energy, Elsevier, vol. 285(C).
    14. Gabrielli, Paolo & Fürer, Florian & Mavromatidis, Georgios & Mazzotti, Marco, 2019. "Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis," Applied Energy, Elsevier, vol. 238(C), pages 1192-1210.
    15. Kaiwen Li & Yuanming Song & Rui Wang, 2022. "Multi-Objective Optimal Sizing of HRES under Multiple Scenarios with Undetermined Probability," Mathematics, MDPI, vol. 10(9), pages 1-19, May.

    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. Akbari, Kaveh & Jolai, Fariborz & Ghaderi, Seyed Farid, 2016. "Optimal design of distributed energy system in a neighborhood under uncertainty," Energy, Elsevier, vol. 116(P1), pages 567-582.
    2. Shunichi Ohmori, 2021. "A Predictive Prescription Using Minimum Volume k -Nearest Neighbor Enclosing Ellipsoid and Robust Optimization," Mathematics, MDPI, vol. 9(2), pages 1-16, January.
    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. 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.
    5. Shipra Agrawal & Yichuan Ding & Amin Saberi & Yinyu Ye, 2012. "Price of Correlations in Stochastic Optimization," Operations Research, INFORMS, vol. 60(1), pages 150-162, February.
    6. Grani A. Hanasusanto & Vladimir Roitch & Daniel Kuhn & Wolfram Wiesemann, 2017. "Ambiguous Joint Chance Constraints Under Mean and Dispersion Information," Operations Research, INFORMS, vol. 65(3), pages 751-767, June.
    7. Dimitris Bertsimas & Melvyn Sim & Meilin Zhang, 2019. "Adaptive Distributionally Robust Optimization," Management Science, INFORMS, vol. 65(2), pages 604-618, February.
    8. Huan Xu & Constantine Caramanis & Shie Mannor, 2012. "Optimization Under Probabilistic Envelope Constraints," Operations Research, INFORMS, vol. 60(3), pages 682-699, June.
    9. Hua Sun & Ziyou Gao & W. Szeto & Jiancheng Long & Fangxia Zhao, 2014. "A Distributionally Robust Joint Chance Constrained Optimization Model for the Dynamic Network Design Problem under Demand Uncertainty," Networks and Spatial Economics, Springer, vol. 14(3), pages 409-433, December.
    10. Ruiwei Jiang & Siqian Shen & Yiling Zhang, 2017. "Integer Programming Approaches for Appointment Scheduling with Random No-Shows and Service Durations," Operations Research, INFORMS, vol. 65(6), pages 1638-1656, December.
    11. Xie, Chen & Wang, Liangquan & Yang, Chaolin, 2021. "Robust inventory management with multiple supply sources," European Journal of Operational Research, Elsevier, vol. 295(2), pages 463-474.
    12. Marla, Lavanya & Rikun, Alexander & Stauffer, Gautier & Pratsini, Eleni, 2020. "Robust modeling and planning: Insights from three industrial applications," Operations Research Perspectives, Elsevier, vol. 7(C).
    13. Xiong, Xing & Li, Yanzhi & Yang, Wenguo & Shen, Huaxiao, 2022. "Data-driven robust dual-sourcing inventory management under purchase price and demand uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    14. Georgios P. Trachanas & Aikaterini Forouli & Nikolaos Gkonis & Haris Doukas, 2020. "Hedging uncertainty in energy efficiency strategies: a minimax regret analysis," Operational Research, Springer, vol. 20(4), pages 2229-2244, December.
    15. Zhaolin Hu & Jing Cao & L. Jeff Hong, 2012. "Robust Simulation of Global Warming Policies Using the DICE Model," Management Science, INFORMS, vol. 58(12), pages 2190-2206, December.
    16. Huan Xu & Constantine Caramanis & Shie Mannor, 2012. "A Distributional Interpretation of Robust Optimization," Mathematics of Operations Research, INFORMS, vol. 37(1), pages 95-110, February.
    17. Vishal Gupta & Paat Rusmevichientong, 2021. "Small-Data, Large-Scale Linear Optimization with Uncertain Objectives," Management Science, INFORMS, vol. 67(1), pages 220-241, January.
    18. Zhi Chen & Weijun Xie, 2021. "Regret in the Newsvendor Model with Demand and Yield Randomness," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4176-4197, November.
    19. Korotkov, Vladimir & Wu, Desheng, 2020. "Evaluating the quality of solutions in project portfolio selection," Omega, Elsevier, vol. 91(C).
    20. Arash Gourtani & Huifu Xu & David Pozo & Tri-Dung Nguyen, 2016. "Robust unit commitment with $$n-1$$ n - 1 security criteria," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 83(3), pages 373-408, June.

    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:118:y:2017:i:c:p:590-599. 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.