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Comparison of alternative decision-making criteria in a two-stage stochastic program for the design of distributed energy systems under uncertainty

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  • Mavromatidis, Georgios
  • Orehounig, Kristina
  • Carmeliet, Jan

Abstract

The design of distributed energy systems (DES) is affected by uncertainty, which can render designs suboptimal. DES design is further complicated by the various decision-maker attitudes towards uncertainty, which range between pessimism and optimism. An additional important factor is the risk of extreme outcomes (e.g. high costs) in highly unfavourable scenarios. Incorporating all decision-maker attitudes towards uncertainty in DES design enables more informed design decisions under uncertainty.

Suggested Citation

  • Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Comparison of alternative decision-making criteria in a two-stage stochastic program for the design of distributed energy systems under uncertainty," Energy, Elsevier, vol. 156(C), pages 709-724.
    • Handle: RePEc:eee:energy:v:156:y:2018:i:c:p:709-724
    DOI: 10.1016/j.energy.2018.05.081
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    4. Yuan, Jiahang & Luo, Xinggang & Li, Yun & Hu, Xiaoqing & Chen, Wenchong & Zhang, Yue, 2022. "Multi criteria decision-making for distributed energy system based on multi-source heterogeneous data," Energy, Elsevier, vol. 239(PD).
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    7. Wang, Meng & Yu, Hang & Lin, Xiaoyu & Jing, Rui & He, Fangjun & Li, Chaoen, 2020. "Comparing stochastic programming with posteriori approach for multi-objective optimization of distributed energy systems under uncertainty," Energy, Elsevier, vol. 210(C).
    8. 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.
    9. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2020. "Machine-learning based study on the on-site renewable electrical performance of an optimal hybrid PCMs integrated renewable system with high-level parameters’ uncertainties," Renewable Energy, Elsevier, vol. 151(C), pages 403-418.
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    11. 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.
    12. Niu, Jide & Tian, Zhe & Yue, Lu, 2020. "Robust optimal design of building cooling sources considering the uncertainty and cross-correlation of demand and source," Applied Energy, Elsevier, vol. 265(C).
    13. Bohlayer, Markus & Bürger, Adrian & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2021. "Multi-period investment pathways - Modeling approaches to design distributed energy systems under uncertainty," Applied Energy, Elsevier, vol. 285(C).
    14. Wang, Zhenfeng & Xu, Guangyin & Wang, Heng & Ren, Jingzheng, 2019. "Distributed energy system for sustainability transition: A comprehensive assessment under uncertainties based on interval multi-criteria decision making method by coupling interval DEMATEL and interva," Energy, Elsevier, vol. 169(C), pages 750-761.
    15. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    16. Wu, Yunna & Xu, Chuanbo & Ke, Yiming & Li, Xinying & Li, Lingwenying, 2019. "Portfolio selection of distributed energy generation projects considering uncertainty and project interaction under different enterprise strategic scenarios," Applied Energy, Elsevier, vol. 236(C), pages 444-464.
    17. Afzali, Sayyed Faridoddin & Cotton, James S. & Mahalec, Vladimir, 2020. "Urban community energy systems design under uncertainty for specified levels of carbon dioxide emissions," Applied Energy, Elsevier, vol. 259(C).
    18. Kuttner, Leopold, 2022. "Integrated scheduling and bidding of power and reserve of energy resource aggregators with storage plants," Applied Energy, Elsevier, vol. 321(C).
    19. Zhuang, Chaoqun & Wang, Shengwei & Shan, Kui, 2020. "A risk-based robust optimal chiller sequencing control strategy for energy-efficient operation considering measurement uncertainties," Applied Energy, Elsevier, vol. 280(C).
    20. Pickering, Bryn & Choudhary, Ruchi, 2021. "Quantifying resilience in energy systems with out-of-sample testing," Applied Energy, Elsevier, vol. 285(C).

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