IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v235y2021ics0360544221014195.html
   My bibliography  Save this article

Adaptive robust optimization for the energy management of the grid-connected energy hubs based on hybrid meta-heuristic algorithm

Author

Listed:
  • AkbaiZadeh, MohammadReza
  • Niknam, Taher
  • Kavousi-Fard, Abdollah

Abstract

This paper describes the energy management of energy hubs connected to electricity, gas, and heating networks in which the hub is incorporated as a coordination framework between distributed generations and energy storage systems. The deterministic model of the proposed scheme minimizes the total operating cost of these energy networks in the presence of energy hubs constrained to the optimal power flow equations of different networks and the formulation of hubs with sources and storages. The problem is subject to uncertainties of load, energy prices, renewable sources, and consumption energy of mobile storages. Additionally, the scheme inherently is a non-convex mixed-integer nonlinear programming framework. Adaptive robust optimization is used to model these uncertainties, which is based on a hybrid metaheuristic algorithm due to the nonlinear and non-convex nature of the proposed problem. Hence, a combination of Ant-lion Optimizer and Krill herd Optimization algorithm has been employed, which provides a robust optimal solution with approximate unique response conditions in the worst-case scenario. Eventually, the numerical results obtained by implementing the proposed scheme on a sample test system confirm the capability of the mentioned scheme in improving the operation condition of different energy networks in the worst-case scenario. Consequently, the total energy loss in all mentioned networks and maximum voltage and temperature drop decrease by roughly 8%, 44%, and 74% with respect to power flow analysis in this scenario.

Suggested Citation

  • AkbaiZadeh, MohammadReza & Niknam, Taher & Kavousi-Fard, Abdollah, 2021. "Adaptive robust optimization for the energy management of the grid-connected energy hubs based on hybrid meta-heuristic algorithm," Energy, Elsevier, vol. 235(C).
    • Handle: RePEc:eee:energy:v:235:y:2021:i:c:s0360544221014195
    DOI: 10.1016/j.energy.2021.121171
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221014195
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.121171?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. Dini, Anoosh & Pirouzi, Sasan & Norouzi, Mohammadali & Lehtonen, Matti, 2019. "Grid-connected energy hubs in the coordinated multi-energy management based on day-ahead market framework," Energy, Elsevier, vol. 188(C).
    2. Bozorgavari, Seyed Aboozar & Aghaei, Jamshid & Pirouzi, Sasan & Nikoobakht, Ahmad & Farahmand, Hossein & Korpås, Magnus, 2020. "Robust planning of distributed battery energy storage systems in flexible smart distribution networks: A comprehensive study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    3. Heidari, A. & Mortazavi, S.S. & Bansal, R.C., 2020. "Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies," Applied Energy, Elsevier, vol. 261(C).
    4. Samet, Haidar & Khorshidsavar, Morteza, 2018. "Analytic time series load flow," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3886-3899.
    5. Zafarani, Hamidreza & Taher, Seyed Abbas & Shahidehpour, Mohammad, 2020. "Robust operation of a multicarrier energy system considering EVs and CHP units," Energy, Elsevier, vol. 192(C).
    6. Shabanpour-Haghighi, Amin & Seifi, Ali Reza, 2015. "Multi-objective operation management of a multi-carrier energy system," Energy, Elsevier, vol. 88(C), pages 430-442.
    7. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    8. Pirouzi, Sasan & Aghaei, Jamshid & Niknam, Taher & Farahmand, Hossein & Korpås, Magnus, 2018. "Exploring prospective benefits of electric vehicles for optimal energy conditioning in distribution networks," Energy, Elsevier, vol. 157(C), pages 679-689.
    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. Wilberforce, Tabbi & Rezk, Hegazy & Olabi, A.G. & Epelle, Emmanuel I. & Abdelkareem, Mohammad Ali, 2023. "Comparative analysis on parametric estimation of a PEM fuel cell using metaheuristics algorithms," Energy, Elsevier, vol. 262(PB).
    2. Weng, Xuemeng & Xuan, Ping & Heidari, Ali Asghar & Cai, Zhennao & Chen, Huiling & Mansour, Romany F. & Ragab, Mahmoud, 2023. "A vertical and horizontal crossover sine cosine algorithm with pattern search for optimal power flow in power systems," Energy, Elsevier, vol. 271(C).
    3. Sina Parhoudeh & Pablo Eguía López & Abdollah Kavousi Fard, 2023. "Stochastic Coordinated Management of Electrical–Gas–Thermal Networks in Flexible Energy Hubs Considering Day-Ahead Energy and Ancillary Markets," Sustainability, MDPI, vol. 15(13), pages 1-26, July.
    4. Akbari, Ehsan & Mousavi Shabestari, Seyed Farzin & Pirouzi, Sasan & Jadidoleslam, Morteza, 2023. "Network flexibility regulation by renewable energy hubs using flexibility pricing-based energy management," Renewable Energy, Elsevier, vol. 206(C), pages 295-308.
    5. 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).
    6. Khaligh, Vahid & Ghezelbash, Azam & Mazidi, Mohammadreza & Liu, Jay & Ryu, Jun-Hyung, 2023. "P-robust energy management of a multi-energy microgrid enabled with energy conversions under various uncertainties," Energy, Elsevier, vol. 271(C).
    7. Zhou, Yanting & Ma, Zhongjing & Zhang, Jinhui & Zou, Suli, 2022. "Data-driven stochastic energy management of multi energy system using deep reinforcement learning," Energy, Elsevier, vol. 261(PA).
    8. Lu, Xinhui & Li, Haobin & Zhou, Kaile & Yang, Shanlin, 2023. "Optimal load dispatch of energy hub considering uncertainties of renewable energy and demand response," Energy, Elsevier, vol. 262(PB).
    9. Andreas Dimou & Konstantinos Moustakas & Stergios Vakalis, 2023. "The Role of Hydrogen and H 2 Mobility on the Green Transition of Islands: The Case of Anafi (Greece)," Energies, MDPI, vol. 16(8), pages 1-14, April.
    10. Han, Yulin & Zheng, Jingyuan & Luo, Xiaoyan & Qian, Yu & Yang, Siyu, 2023. "Multi-scenario data-driven robust optimisation for industrial steam power systems under uncertainty," Energy, Elsevier, vol. 263(PD).

    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. Dini, Anoosh & Hassankashi, Alireza & Pirouzi, Sasan & Lehtonen, Matti & Arandian, Behdad & Baziar, Ali Asghar, 2022. "A flexible-reliable operation optimization model of the networked energy hubs with distributed generations, energy storage systems and demand response," Energy, Elsevier, vol. 239(PA).
    2. 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).
    3. Norouzi, Mohammadali & Aghaei, Jamshid & Pirouzi, Sasan & Niknam, Taher & Fotuhi-Firuzabad, Mahmud, 2022. "Flexibility pricing of integrated unit of electric spring and EVs parking in microgrids," Energy, Elsevier, vol. 239(PB).
    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. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    6. Dini, Anoosh & Pirouzi, Sasan & Norouzi, Mohammadali & Lehtonen, Matti, 2019. "Grid-connected energy hubs in the coordinated multi-energy management based on day-ahead market framework," Energy, Elsevier, vol. 188(C).
    7. Azimi, Maryam & Salami, Abolfazl, 2021. "A new approach on quantification of flexibility index in multi-carrier energy systems towards optimally energy hub management," Energy, Elsevier, vol. 232(C).
    8. Lu, Xinhui & Li, Haobin & Zhou, Kaile & Yang, Shanlin, 2023. "Optimal load dispatch of energy hub considering uncertainties of renewable energy and demand response," Energy, Elsevier, vol. 262(PB).
    9. Soleimani, Borhan & Keihan Asl, Dariush & Estakhr, Javad & Seifi, Ali Reza, 2022. "Integrated optimization of multi-carrier energy systems: Water-energy nexus case," Energy, Elsevier, vol. 257(C).
    10. Wang, Jiangjiang & Deng, Hongda & Qi, Xiaoling, 2022. "Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks," Energy, Elsevier, vol. 261(PA).
    11. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    12. 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).
    13. Xiang, Yue & Guo, Yongtao & Wu, Gang & Liu, Junyong & Sun, Wei & Lei, Yutian & Zeng, Pingliang, 2022. "Low-carbon economic planning of integrated electricity-gas energy systems," Energy, Elsevier, vol. 249(C).
    14. Norouzi, Mohammadali & Aghaei, Jamshid & Niknam, Taher & Alipour, Mohammadali & Pirouzi, Sasan & Lehtonen, Matti, 2023. "Risk-averse and flexi-intelligent scheduling of microgrids based on hybrid Boltzmann machines and cascade neural network forecasting," Applied Energy, Elsevier, vol. 348(C).
    15. Xiang, Yue & Wu, Gang & Shen, Xiaodong & Ma, Yuhang & Gou, Jing & Xu, Weiting & Liu, Junyong, 2021. "Low-carbon economic dispatch of electricity-gas systems," Energy, Elsevier, vol. 226(C).
    16. Li, Qiang & Gao, Mengkai & Lin, Houfei & Chen, Ziyu & Chen, Minyou, 2019. "MAS-based distributed control method for multi-microgrids with high-penetration renewable energy," Energy, Elsevier, vol. 171(C), pages 284-295.
    17. Constantino Dário Justo & José Eduardo Tafula & Pedro Moura, 2022. "Planning Sustainable Energy Systems in the Southern African Development Community: A Review of Power Systems Planning Approaches," Energies, MDPI, vol. 15(21), pages 1-28, October.
    18. Àlex Alonso & Jordi de la Hoz & Helena Martín & Sergio Coronas & Pep Salas & José Matas, 2020. "A Comprehensive Model for the Design of a Microgrid under Regulatory Constraints Using Synthetical Data Generation and Stochastic Optimization," Energies, MDPI, vol. 13(21), pages 1-26, October.
    19. Beigvand, Soheil Derafshi & Abdi, Hamdi & La Scala, Massimo, 2017. "A general model for energy hub economic dispatch," Applied Energy, Elsevier, vol. 190(C), pages 1090-1111.
    20. Magda I. El-Afifi & Magdi M. Saadawi & Abdelfattah A. Eladl, 2022. "Cogeneration Systems Performance Analysis as a Sustainable Clean Energy and Water Source Based on Energy Hubs Using the Archimedes Optimization Algorithm," Sustainability, MDPI, vol. 14(22), pages 1-26, November.

    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:235:y:2021:i:c:s0360544221014195. 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.