IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v238y2022ipas0360544221019095.html
   My bibliography  Save this article

A medium-term hybrid IGDT-Robust optimization model for optimal self scheduling of multi-carrier energy systems

Author

Listed:
  • Najafi, Arsalan
  • Pourakbari-Kasmaei, Mahdi
  • Jasinski, Michal
  • Lehtonen, Matti
  • Leonowicz, Zbigniew

Abstract

Introducing new technologies in co-generation and tri-generation systems has led to a rapid growth toward the energy hubs (EHs) as an effective way for coupling among various energy types. On the other hand, the energy systems have usually been exposed to uncertain environments due to the presence of renewable energy sources (RESs) and interaction with the electricity markets. Hence, this paper develops a novel optimization framework based on a hybrid information gap decision theory (IGDT) and robust optimization (RO) to handle the optimal self-scheduling of the EH within a medium-term horizon for large consumers. The proposed mixed-integer linear programming (MILP) framework aims to capture the advantages of both the IGDT and RO techniques in dealing with the complicated binary variables and achieving the worst-case realization arisen from wind turbine generation and day-ahead (DA) electricity market uncertainties. The RO optimization approach is presented to model the DA electricity price uncertainty while the uncertainty related to the wind turbine generations is taken into account by the IGDT. Numerical results validate the capability of the model facing uncertainties. The amount of total operation cost of the EH increases by 8.6 % taking into account the worst-case realization of uncertainties through the proposed hybrid IGDT-RO compared to the case considering perfect information. Besides, the results reveal that optimal decisions can be taken by the operator using the proposed hybrid IGDT-RO model.

Suggested Citation

  • Najafi, Arsalan & Pourakbari-Kasmaei, Mahdi & Jasinski, Michal & Lehtonen, Matti & Leonowicz, Zbigniew, 2022. "A medium-term hybrid IGDT-Robust optimization model for optimal self scheduling of multi-carrier energy systems," Energy, Elsevier, vol. 238(PA).
    • Handle: RePEc:eee:energy:v:238:y:2022:i:pa:s0360544221019095
    DOI: 10.1016/j.energy.2021.121661
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221019095
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.121661?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. Zare, Kazem & Moghaddam, Mohsen Parsa & Sheikh El Eslami, Mohammad Kazem, 2010. "Electricity procurement for large consumers based on Information Gap Decision Theory," Energy Policy, Elsevier, vol. 38(1), pages 234-242, January.
    2. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Yang, Shanlin, 2020. "A robust optimization approach for coordinated operation of multiple energy hubs," Energy, Elsevier, vol. 197(C).
    3. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Yousefi, Hossein, 2017. "Energy hub: From a model to a concept – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1512-1527.
    4. Mansouri, Seyed Amir & Ahmarinejad, Amir & Javadi, Mohammad Sadegh & Catalão, João P.S., 2020. "Two-stage stochastic framework for energy hubs planning considering demand response programs," Energy, Elsevier, vol. 206(C).
    5. Yang, Hangbo & You, Pengcheng & Shang, Ce, 2021. "Distributed planning of electricity and natural gas networks and energy hubs," Applied Energy, Elsevier, vol. 282(PA).
    6. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    7. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Feng, Nanping, 2020. "A robust optimization approach for optimal load dispatch of community energy hub," Applied Energy, Elsevier, vol. 259(C).
    8. 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.
    9. Nikmehr, Nima, 2020. "Distributed robust operational optimization of networked microgrids embedded interconnected energy hubs," Energy, Elsevier, vol. 199(C).
    10. Moradi-Dalvand, M. & Mohammadi-Ivatloo, B. & Amjady, N. & Zareipour, H. & Mazhab-Jafari, A., 2015. "Self-scheduling of a wind producer based on Information Gap Decision Theory," Energy, Elsevier, vol. 81(C), pages 588-600.
    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. Najafi, Arsalan & Homaee, Omid & Jasiński, Michał & Tsaousoglou, Georgios & Leonowicz, Zbigniew, 2023. "Integrating hydrogen technology into active distribution networks: The case of private hydrogen refueling stations," Energy, Elsevier, vol. 278(PB).
    2. Liu, Zhouding & Nazari-Heris, Morteza, 2023. "Optimal bidding strategy of multi-carrier systems in electricity markets using information gap decision theory," Energy, Elsevier, vol. 280(C).
    3. Michał Jasiński & Arsalan Najafi & Tomasz Sikorski & Paweł Kostyła & Jacek Rezmer, 2022. "Operation of an Energy Storage System Integrated with a Photovoltaic System and an Industrial Customer under Different Real and Pseudo-Real Profiles," Energies, MDPI, vol. 15(21), pages 1-27, November.
    4. Najafi, Arsalan & Homaee, Omid & Jasiński, Michał & Pourakbari-Kasmaei, Mahdi & Lehtonen, Matti & Leonowicz, Zbigniew, 2023. "Participation of hydrogen-rich energy hubs in day-ahead and regulation markets: A hybrid stochastic-robust model," Applied Energy, Elsevier, vol. 339(C).
    5. Bodong, Song & Wiseong, Jin & Chengmeng, Li & Khakichi, Aroos, 2023. "Economic management and planning based on a probabilistic model in a multi-energy market in the presence of renewable energy sources with a demand-side management program," Energy, Elsevier, vol. 269(C).
    6. Vahid-Ghavidel, Morteza & Shafie-khah, Miadreza & Javadi, Mohammad S. & Santos, Sérgio F. & Gough, Matthew & Quijano, Darwin A. & Catalao, Joao P.S., 2023. "Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system," Energy, Elsevier, vol. 265(C).
    7. Lumin Shi & Man-Wen Tian & As’ad Alizadeh & Ardashir Mohammadzadeh & Sayyad Nojavan, 2023. "Information Gap Decision Theory-Based Risk-Averse Scheduling of a Combined Heat and Power Hybrid Energy System," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    8. Dong, Weijie & He, Guoqing & Cui, Quansheng & Sun, Wenwen & Hu, Zhenlong & Ahli raad, Erfan, 2022. "Self-scheduling of a novel hybrid GTSOFC unit in day-ahead energy and spinning reserve markets within ancillary services using a novel energy storage," Energy, Elsevier, vol. 239(PE).
    9. Najafi, Arsalan & Jasiński, Michał & Leonowicz, Zbigniew, 2022. "A hybrid distributed framework for optimal coordination of electric vehicle aggregators problem," Energy, Elsevier, vol. 249(C).

    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. 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).
    2. Najafi, Arsalan & Pourakbari-Kasmaei, Mahdi & Jasinski, Michal & Lehtonen, Matti & Leonowicz, Zbigniew, 2021. "A hybrid decentralized stochastic-robust model for optimal coordination of electric vehicle aggregator and energy hub entities," Applied Energy, Elsevier, vol. 304(C).
    3. Najafi, Arsalan & Jasiński, Michał & Leonowicz, Zbigniew, 2022. "A hybrid distributed framework for optimal coordination of electric vehicle aggregators problem," Energy, Elsevier, vol. 249(C).
    4. Aslani, Mehrdad & Mashayekhi, Mehdi & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2022. "Robust optimal operation of energy hub incorporating integrated thermal and electrical demand response programs under various electric vehicle charging modes," Applied Energy, Elsevier, vol. 321(C).
    5. Najafi, Arsalan & Pourakbari-Kasmaei, Mahdi & Jasinski, Michal & Contreras, Javier & Lehtonen, Matti & Leonowicz, Zbigniew, 2022. "The role of EV based peer-to-peer transactive energy hubs in distribution network optimization," Applied Energy, Elsevier, vol. 319(C).
    6. Arsalan Najafi & Mousa Marzband & Behnam Mohamadi-Ivatloo & Javier Contreras & Mahdi Pourakbari-Kasmaei & Matti Lehtonen & Radu Godina, 2019. "Uncertainty-Based Models for Optimal Management of Energy Hubs Considering Demand Response," Energies, MDPI, vol. 12(8), pages 1-20, April.
    7. Javadi, Mohammad Sadegh & Esmaeel Nezhad, Ali & Jordehi, Ahmad Rezaee & Gough, Matthew & Santos, Sérgio F. & Catalão, João P.S., 2022. "Transactive energy framework in multi-carrier energy hubs: A fully decentralized model," Energy, Elsevier, vol. 238(PB).
    8. Wu, Yuxin & Yan, Haoyuan & Liu, Min & Zhao, Tianyang & Qiu, Jiayu & Liu, Shengwei, 2023. "Distributed energy trading on networked energy hubs under network constraints," Renewable Energy, Elsevier, vol. 209(C), pages 491-504.
    9. Aunedi, Marko & Pantaleo, Antonio Marco & Kuriyan, Kamal & Strbac, Goran & Shah, Nilay, 2020. "Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems," Applied Energy, Elsevier, vol. 276(C).
    10. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    11. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
    12. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Yang, Shanlin, 2020. "A robust optimization approach for coordinated operation of multiple energy hubs," Energy, Elsevier, vol. 197(C).
    13. Seyfi, Mohammad & Mehdinejad, Mehdi & Mohammadi-Ivatloo, Behnam & Shayanfar, Heidarali, 2022. "Deep learning-based scheduling of virtual energy hubs with plug-in hybrid compressed natural gas-electric vehicles," Applied Energy, Elsevier, vol. 321(C).
    14. 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.
    15. Bartolini, Andrea & Mazzoni, Stefano & Comodi, Gabriele & Romagnoli, Alessandro, 2021. "Impact of carbon pricing on distributed energy systems planning," Applied Energy, Elsevier, vol. 301(C).
    16. Alabi, Tobi Michael & Lu, Lin & Yang, Zaiyue, 2021. "Stochastic optimal planning scheme of a zero-carbon multi-energy system (ZC-MES) considering the uncertainties of individual energy demand and renewable resources: An integrated chance-constrained and," Energy, Elsevier, vol. 232(C).
    17. Shams, Mohammad H. & Shahabi, Majid & MansourLakouraj, Mohammad & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Adjustable robust optimization approach for two-stage operation of energy hub-based microgrids," Energy, Elsevier, vol. 222(C).
    18. Zhang, Hongyu & Tomasgard, Asgeir & Knudsen, Brage Rugstad & Svendsen, Harald G. & Bakker, Steffen J. & Grossmann, Ignacio E., 2022. "Modelling and analysis of offshore energy hubs," Energy, Elsevier, vol. 261(PA).
    19. He, Shuaijia & Gao, Hongjun & Chen, Zhe & Liu, Junyong & Zhao, Liang & Wu, Gang & Xu, Song, 2022. "Low-carbon distribution system planning considering flexible support of zero-carbon energy station," Energy, Elsevier, vol. 244(PB).
    20. Effenberger, Frank & Hilbert, Andreas, 2016. "Towards an energy information system architecture description for industrial manufacturers: Decomposition & allocation view," Energy, Elsevier, vol. 112(C), pages 599-605.

    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:238:y:2022:i:pa:s0360544221019095. 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.