IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v283y2023ics0360544223020789.html
   My bibliography  Save this article

Integrated flexibility characterization and measurement of distributed multi-energy systems considering temporal coupling constraints

Author

Listed:
  • Tie, Yingqi
  • Hu, Bo
  • Shao, Changzheng
  • Huang, Wei
  • Qi, Feng
  • Xie, Kaigui

Abstract

The integrated flexibility of distributed multi-energy systems (DMES) has been recognized as a valuable balancing resource to the centralized energy system, which can be characterized by an integrated flexible region (IFR) of multiple energy inputs. Notably, the IFR is only captured for one single period in previous studies, whereas the time coupling in consecutive periods has a significant impact on the integrated flexibility. This paper proposes a modified IFR-based approach to characterize and measure the integrated flexibility of DMES considering the temporal coupling constraints. First, operation constraints of the DMES are formulated, followed by a vertex search method to obtain the IFR, i. e, a polytope that visualizes those operation constraints. Then, an approximation approach is proposed to decompose the original IFR into a series of lower-dimension IFRs, each of which corresponds to a specific period. The influence of states of adjacent periods is directly reflected by the position change of the vertices. The decoupled IFRs can be incorporated conveniently into the multi-period economic dispatch of the centralized energy system. Moreover, the Volume of the IFRs (VFR) is introduced as an index to quantify the flexibility of the DMES. The performance of the proposed methods is verified by the case studies.

Suggested Citation

  • Tie, Yingqi & Hu, Bo & Shao, Changzheng & Huang, Wei & Qi, Feng & Xie, Kaigui, 2023. "Integrated flexibility characterization and measurement of distributed multi-energy systems considering temporal coupling constraints," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223020789
    DOI: 10.1016/j.energy.2023.128684
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223020789
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128684?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. Wang, Yi & Cheng, Jiangnan & Zhang, Ning & Kang, Chongqing, 2018. "Automatic and linearized modeling of energy hub and its flexibility analysis," Applied Energy, Elsevier, vol. 211(C), pages 705-714.
    3. Montuori, Lina & Alcázar-Ortega, Manuel & Álvarez-Bel, Carlos, 2021. "Methodology for the evaluation of demand response strategies for the management of natural gas systems," Energy, Elsevier, vol. 234(C).
    4. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    Full references (including those not matched with items on IDEAS)

    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. Hui, Hengyu & Bao, Minglei & Ding, Yi & Song, Yonghua, 2022. "Exploring the integrated flexible region of distributed multi-energy systems with process industry," Applied Energy, Elsevier, vol. 311(C).
    2. Ramos-Teodoro, Jerónimo & Rodríguez, Francisco & Berenguel, Manuel & Torres, José Luis, 2018. "Heterogeneous resource management in energy hubs with self-consumption: Contributions and application example," Applied Energy, Elsevier, vol. 229(C), pages 537-550.
    3. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    4. Zeng, Huibin & Shao, Bilin & Dai, Hongbin & Yan, Yichuan & Tian, Ning, 2023. "Natural gas demand response strategy considering user satisfaction and load volatility under dynamic pricing," Energy, Elsevier, vol. 277(C).
    5. Wang, L.X. & Zheng, J.H. & Li, M.S. & Lin, X. & Jing, Z.X. & Wu, P.Z. & Wu, Q.H. & Zhou, X.X., 2019. "Multi-time scale dynamic analysis of integrated energy systems: An individual-based model," Applied Energy, Elsevier, vol. 237(C), pages 848-861.
    6. 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).
    7. 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).
    8. Fodstad, Marte & Crespo del Granado, Pedro & Hellemo, Lars & Knudsen, Brage Rugstad & Pisciella, Paolo & Silvast, Antti & Bordin, Chiara & Schmidt, Sarah & Straus, Julian, 2022. "Next frontiers in energy system modelling: A review on challenges and the state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    9. Jiang, Tuo & Min, Yong & Zhou, Guiping & Chen, Lei & Chen, Qun & Xu, Fei & Luo, Huanhuan, 2021. "Hierarchical dispatch method for integrated heat and power systems considering the heat transfer process," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    10. Zhou, Yuqi & Yu, Wenbin & Zhu, Shanying & Yang, Bo & He, Jianping, 2021. "Distributionally robust chance-constrained energy management of an integrated retailer in the multi-energy market," Applied Energy, Elsevier, vol. 286(C).
    11. József Magyari & Krisztina Hegedüs & Botond Sinóros-Szabó, 2022. "Integration Opportunities of Power-to-Gas and Internet-of-Things Technical Advancements: A Systematic Literature Review," Energies, MDPI, vol. 15(19), pages 1-19, September.
    12. Liu, Tianhao & Tian, Jun & Zhu, Hongyu & Goh, Hui Hwang & Liu, Hui & Wu, Thomas & Zhang, Dongdong, 2023. "Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation," Energy, Elsevier, vol. 277(C).
    13. Mittelviefhaus, Moritz & Pareschi, Giacomo & Allan, James & Georges, Gil & Boulouchos, Konstantinos, 2021. "Optimal investment and scheduling of residential multi-energy systems including electric mobility: A cost-effective approach to climate change mitigation," Applied Energy, Elsevier, vol. 301(C).
    14. Zhou, Huansheng & Zheng, J.H. & Li, Zhigang & Wu, Q.H. & Zhou, X.X., 2019. "Multi-stage contingency-constrained co-planning for electricity-gas systems interconnected with gas-fired units and power-to-gas plants using iterative Benders decomposition," Energy, Elsevier, vol. 180(C), pages 689-701.
    15. Batista, Natasha E. & Carvalho, Paulo C.M. & Fernández-Ramírez, Luis M. & Braga, Arthur P.S., 2023. "Optimizing methodologies of hybrid renewable energy systems powered reverse osmosis plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    16. Zhou, Suyang & Sun, Kaiyu & Wu, Zhi & Gu, Wei & Wu, Gaoxiang & Li, Zhe & Li, Junjie, 2020. "Optimized operation method of small and medium-sized integrated energy system for P2G equipment under strong uncertainty," Energy, Elsevier, vol. 199(C).
    17. Li, Qi & Xiao, Xukang & Pu, Yuchen & Luo, Shuyu & Liu, Hong & Chen, Weirong, 2023. "Hierarchical optimal scheduling method for regional integrated energy systems considering electricity-hydrogen shared energy," Applied Energy, Elsevier, vol. 349(C).
    18. 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.
    19. Sobhani, Seyed Omid & Sheykhha, Siamak & Madlener, Reinhard, 2020. "An integrated two-level demand-side management game applied to smart energy hubs with storage," Energy, Elsevier, vol. 206(C).
    20. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad & Hajizadeh, Amin & Mohammadi-ivatloo, Behnam, 2022. "A comprehensive review on optimization challenges of smart energy hubs under uncertainty factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).

    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:283:y:2023:i:c:s0360544223020789. 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.