IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v240y2019icp534-548.html
   My bibliography  Save this article

Cross-domain Pareto optimization of heterogeneous domains for the operation of smart cities

Author

Listed:
  • Stoyanova, Ivelina
  • Monti, Antonello

Abstract

This paper presents a tool for multi-objective cross-domain optimization of heterogenous energy and non-energy domains for urban areas in a comprehensive optimization approach. The multi-objective optimization concept facilitates the definition of any number of objective functions, versatile in their origin and properties, flexibly adaptable to area specifics or regional and communal priorities. The applied optimization for several domains at the lowest system level yields a comprehensive holistic solution optimal for the particular subsystem, as it is fitted for this subsystem according to its characteristics. The main advantage is the exploitation of cross-domain interactions and synergies and, therefore, the improved overall performance of the system. However, the cross-domain approach requires high-level modeling in order to overcome compatibility issues, which decreases the accuracy of domain-specific simulation and optimization compared to methods which apply detailed models. Based on the mathematical concept of multi-objective Pareto optimization, its adaptation, implementation and application in the context of Smart Cities are presented in detail. Several optimization formulations and methods are applied to the test scenario to demonstrate the concept, compare the results and evaluate the computational performance of the application. The ε-constraint method appears to be better suitable for heterogeneous domains, as the weighted sum method is highly sensitive to weight setting for heterogeneous objectives. The computational performance is very good in terms of computation time but meets numerical limitations for samples of around 500 buildings, leading to numerical infeasibility for samples of 1300 buildings. This is solved with the presented method for model aggregation. The tool is available on GitHub.

Suggested Citation

  • Stoyanova, Ivelina & Monti, Antonello, 2019. "Cross-domain Pareto optimization of heterogeneous domains for the operation of smart cities," Applied Energy, Elsevier, vol. 240(C), pages 534-548.
    • Handle: RePEc:eee:appene:v:240:y:2019:i:c:p:534-548
    DOI: 10.1016/j.apenergy.2019.02.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919303009
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.02.010?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. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Liu, Xuezhi & Wu, Jianzhong & Jenkins, Nick & Bagdanavicius, Audrius, 2016. "Combined analysis of electricity and heat networks," Applied Energy, Elsevier, vol. 162(C), pages 1238-1250.
    3. Cui, Yunfei & Geng, Zhiqiang & Zhu, Qunxiong & Han, Yongming, 2017. "Review: Multi-objective optimization methods and application in energy saving," Energy, Elsevier, vol. 125(C), pages 681-704.
    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. Lin, Jian & Zhong, Xiaoyi & Wang, Jing & Huang, Yuan & Bai, Xuetao & Wang, Xiaonan & Shah, Nilay & Xie, Shan & Zhao, Yingru, 2021. "Relative optimization potential: A novel perspective to address trade-off challenges in urban energy system planning," Applied Energy, Elsevier, vol. 304(C).
    2. Nie, Yonghui & Qiu, Yu & Yang, Annan & Zhao, Yan, 2024. "Risk-limiting dispatching strategy considering demand response in multi-energy microgrids," Applied Energy, Elsevier, vol. 353(PA).

    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. Yu Huang & Kai Yang & Weiting Zhang & Kwang Y. Lee, 2018. "Hierarchical Energy Management for the MultiEnergy Carriers System with Different Interest Bodies," Energies, MDPI, vol. 11(10), pages 1-18, October.
    2. Bao, Zhejing & Chen, Dawei & Wu, Lei & Guo, Xiaogang, 2019. "Optimal inter- and intra-hour scheduling of islanded integrated-energy system considering linepack of gas pipelines," Energy, Elsevier, vol. 171(C), pages 326-340.
    3. Lun Yang & Xia Zhao & Xinyi Li & Wei Yan, 2018. "Probabilistic Steady-State Operation and Interaction Analysis of Integrated Electricity, Gas and Heating Systems," Energies, MDPI, vol. 11(4), pages 1-21, April.
    4. Shen, Lu & Dou, Xiaobo & Long, Huan & Li, Chen & Chen, Kang & Zhou, Ji, 2021. "A collaborative voltage optimization utilizing flexibility of community heating systems for high PV penetration," Energy, Elsevier, vol. 232(C).
    5. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    6. Markensteijn, A.S. & Romate, J.E. & Vuik, C., 2020. "A graph-based model framework for steady-state load flow problems of general multi-carrier energy systems," Applied Energy, Elsevier, vol. 280(C).
    7. Hu, Xiao & Zhang, Heng & Chen, Dongwen & Li, Yong & Wang, Li & Zhang, Feng & Cheng, Haozhong, 2020. "Multi-objective planning for integrated energy systems considering both exergy efficiency and economy," Energy, Elsevier, vol. 197(C).
    8. Xi, Yufei & Zeng, Qing & Chen, Zhe & Lund, Henrik & Conejo, Antonio J., 2020. "A market equilibrium model for electricity, gas and district heating operations," Energy, Elsevier, vol. 206(C).
    9. Cai, Hanmin & You, Shi & Wang, Jiawei & Bindner, Henrik W. & Klyapovskiy, Sergey, 2018. "Technical assessment of electric heat boosters in low-temperature district heating based on combined heat and power analysis," Energy, Elsevier, vol. 150(C), pages 938-949.
    10. Bao, Zhejing & Ye, Yangli & Liu, Ruijie & Cheng, Weidong & Zhao, Qiang & Wu, Ting, 2022. "Scheduling coordination of back pressure CHP coupled electricity-heat energy system with adaptive constraint strategy to accommodate uncertain wind power," Energy, Elsevier, vol. 240(C).
    11. Hosseini, Seyed Hamid Reza & Allahham, Adib & Walker, Sara Louise & Taylor, Phil, 2020. "Optimal planning and operation of multi-vector energy networks: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    12. Qin, Xin & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "A generalized quasi-dynamic model for electric-heat coupling integrated energy system with distributed energy resources," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    13. Patrick Sunday Onen & Geev Mokryani & Rana H. A. Zubo, 2022. "Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review," Energies, MDPI, vol. 15(15), pages 1-25, August.
    14. Wang, Jiawei & You, Shi & Zong, Yi & Træholt, Chresten & Dong, Zhao Yang & Zhou, You, 2019. "Flexibility of combined heat and power plants: A review of technologies and operation strategies," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    15. Jiajia Li & Jinfu Liu & Peigang Yan & Xingshuo Li & Guowen Zhou & Daren Yu, 2021. "Operation Optimization of Integrated Energy System under a Renewable Energy Dominated Future Scene Considering Both Independence and Benefit: A Review," Energies, MDPI, vol. 14(4), pages 1-36, February.
    16. Liu, Xuezhi & Mancarella, Pierluigi, 2016. "Modelling, assessment and Sankey diagrams of integrated electricity-heat-gas networks in multi-vector district energy systems," Applied Energy, Elsevier, vol. 167(C), pages 336-352.
    17. Carvallo, Claudio & Jalil-Vega, Francisca & Moreno, Rodrigo, 2023. "A multi-energy multi-microgrid system planning model for decarbonisation and decontamination of isolated systems," Applied Energy, Elsevier, vol. 343(C).
    18. Li, Xue & Li, Wenming & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Li, Guoqing, 2020. "Collaborative scheduling and flexibility assessment of integrated electricity and district heating systems utilizing thermal inertia of district heating network and aggregated buildings," Applied Energy, Elsevier, vol. 258(C).
    19. Wei Wei & Yaping Shi & Kai Hou & Lei Guo & Linyu Wang & Hongjie Jia & Jianzhong Wu & Chong Tong, 2020. "Coordinated Flexibility Scheduling for Urban Integrated Heat and Power Systems by Considering the Temperature Dynamics of Heating Network," Energies, MDPI, vol. 13(12), pages 1-23, June.
    20. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.

    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:appene:v:240:y:2019:i:c:p:534-548. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.