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Exploring the impact space of different technologies using a portfolio constraint based approach for multi-objective optimization of integrated urban energy systems

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  • Jing, Rui
  • Kuriyan, Kamal
  • Kong, Qingyuan
  • Zhang, Zhihui
  • Shah, Nilay
  • Li, Ning
  • Zhao, Yingru

Abstract

Optimization-based modelling provides valuable guidance for designing integrated urban energy systems. However, modelers have to make certain assumptions and they may lack awareness of realistic conditions such as decision-makers’ preferences on certain technology, which can easily lead the obtained optimal solution to be invalid. Therefore, instead of focusing on one “fragile” optimal solution, this paper provides a systematic overview of the contribution each technology can bring to the whole system design so as to achieve the optimum. To achieve this, a portfolio constraint based approach is proposed, which is inspired by the modelling to generate alternatives (MGA) method as well as the eps-constraint method for multi-objective optimization. By varying the threshold values of portfolio constraints, a series of solutions can be gathered as an “impact space” representing the economic and environmental contributions of each technology for the whole system design. A practical Fitting of Ellipses method is further applied to quantify the size of the impact space. Through observing the formation of the impact space, more valuable insights on system design can be obtained.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:rensus:v:113:y:2019:i:c:40
    DOI: 10.1016/j.rser.2019.109249
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    as
    1. Clara F. Heuberger & Iain Staffell & Nilay Shah & Niall Mac Dowell, 2018. "Impact of myopic decision-making and disruptive events in power systems planning," Nature Energy, Nature, vol. 3(8), pages 634-640, August.
    2. Jing, Rui & Wang, Meng & Liang, Hao & Wang, Xiaonan & Li, Ning & Shah, Nilay & Zhao, Yingru, 2018. "Multi-objective optimization of a neighborhood-level urban energy network: Considering Game-theory inspired multi-benefit allocation constraints," Applied Energy, Elsevier, vol. 231(C), pages 534-548.
    3. 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.
    4. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Kendall, Alissa & Træholt, Chresten, 2018. "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, Elsevier, vol. 230(C), pages 836-844.
    5. Qu, Kaiping & Yu, Tao & Zhang, Xiaoshun & Li, Haofei, 2019. "Homogenized adjacent points method: A novel Pareto optimizer for linearized multi-objective optimal energy flow of integrated electricity and gas system," Applied Energy, Elsevier, vol. 233, pages 338-351.
    6. Mavrotas, George & Florios, Kostas, 2013. "An improved version of the augmented epsilon-constraint method (AUGMECON2) for finding the exact Pareto set in Multi-Objective Integer Programming problems," MPRA Paper 105034, University Library of Munich, Germany.
    7. kianmehr, Ehsan & Nikkhah, Saman & Rabiee, Abbas, 2019. "Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner’s and DisCo’s perspectives," Renewable Energy, Elsevier, vol. 132(C), pages 471-485.
    8. Zhang, Di & Evangelisti, Sara & Lettieri, Paola & Papageorgiou, Lazaros G., 2015. "Optimal design of CHP-based microgrids: Multiobjective optimisation and life cycle assessment," Energy, Elsevier, vol. 85(C), pages 181-193.
    9. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    10. Voll, Philip & Jennings, Mark & Hennen, Maike & Shah, Nilay & Bardow, André, 2015. "The optimum is not enough: A near-optimal solution paradigm for energy systems synthesis," Energy, Elsevier, vol. 82(C), pages 446-456.
    11. Saber, Hossein & Moeini-Aghtaie, Moein & Ehsan, Mehdi, 2018. "Developing a multi-objective framework for expansion planning studies of distributed energy storage systems (DESSs)," Energy, Elsevier, vol. 157(C), pages 1079-1089.
    12. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    13. Liu, Zifa & Chen, Yixiao & Zhuo, Ranqun & Jia, Hongjie, 2018. "Energy storage capacity optimization for autonomy microgrid considering CHP and EV scheduling," Applied Energy, Elsevier, vol. 210(C), pages 1113-1125.
    14. Liu, Songsong & Papageorgiou, Lazaros G., 2013. "Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry," Omega, Elsevier, vol. 41(2), pages 369-382.
    15. Ju, Liwei & Tan, Zhongfu & Li, Huanhuan & Tan, Qingkun & Yu, Xiaobao & Song, Xiaohua, 2016. "Multi-objective operation optimization and evaluation model for CCHP and renewable energy based hybrid energy system driven by distributed energy resources in China," Energy, Elsevier, vol. 111(C), pages 322-340.
    16. DeCarolis, Joseph F., 2011. "Using modeling to generate alternatives (MGA) to expand our thinking on energy futures," Energy Economics, Elsevier, vol. 33(2), pages 145-152, March.
    17. 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.
    18. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.
    19. 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.
    20. Si, Fangyuan & Wang, Jinkuan & Han, Yinghua & Zhao, Qiang & Han, Peng & Li, Yan, 2018. "Cost-efficient multi-energy management with flexible complementarity strategy for energy internet," Applied Energy, Elsevier, vol. 231(C), pages 803-815.
    21. 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.
    22. E. Downey Brill, Jr., 1979. "The Use of Optimization Models in Public-Sector Planning," Management Science, INFORMS, vol. 25(5), pages 413-422, May.
    23. Fazlollahi, Samira & Mandel, Pierre & Becker, Gwenaelle & Maréchal, Francois, 2012. "Methods for multi-objective investment and operating optimization of complex energy systems," Energy, Elsevier, vol. 45(1), pages 12-22.
    24. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    25. Wu, Chenyu & Gu, Wei & Xu, Yinliang & Jiang, Ping & Lu, Shuai & Zhao, Bo, 2018. "Bi-level optimization model for integrated energy system considering the thermal comfort of heat customers," Applied Energy, Elsevier, vol. 232(C), pages 607-616.
    26. Unternährer, Jérémy & Moret, Stefano & Joost, Stéphane & Maréchal, François, 2017. "Spatial clustering for district heating integration in urban energy systems: Application to geothermal energy," Applied Energy, Elsevier, vol. 190(C), pages 749-763.
    27. Hocine, Amine & Kouaissah, Noureddine & Bettahar, Samir & Benbouziane, Mohamed, 2018. "Optimizing renewable energy portfolios under uncertainty: A multi-segment fuzzy goal programming approach," Renewable Energy, Elsevier, vol. 129(PA), pages 540-552.
    28. Mazzeo, Domenico & Oliveti, Giuseppe & Baglivo, Cristina & Congedo, Paolo M., 2018. "Energy reliability-constrained method for the multi-objective optimization of a photovoltaic-wind hybrid system with battery storage," Energy, Elsevier, vol. 156(C), pages 688-708.
    29. E. Downey Brill, Jr. & Shoou-Yuh Chang & Lewis D. Hopkins, 1982. "Modeling to Generate Alternatives: The HSJ Approach and an Illustration Using a Problem in Land Use Planning," Management Science, INFORMS, vol. 28(3), pages 221-235, March.
    Full references (including those not matched with items on IDEAS)

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