IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v371y2024ics030626192401016x.html
   My bibliography  Save this article

Flexible dynamic boundary microgrid operation considering network and load unbalances

Author

Listed:
  • Su, Yu
  • Li, Dingrui
  • Wang, Fred
  • Olama, Mohammed
  • Ferrari, Maximiliano
  • Ollis, Ben
  • Liu, Yilu

Abstract

Flexible microgrids with dynamic boundaries have recently been introduced in the literature. With the ability to reconfigure the topology of the microgrids dynamically through remotely controlled switches, flexible microgrids with dynamic boundaries can further improve the resiliency and energy efficiency of microgrids with distributed energy resources (DERs). This paper focuses on the optimal operation considering one of the predominant characteristics of microgrids and distribution systems – unbalanced networks and loads. In existing literature, balanced modeling of microgrids is more common due to its attractive simplicity. The three-phase power unbalance has not been considered as a constraint on the generation units in a microgrid. Negative sequence constraints have also been neglected. In this article, we propose a set of constraints that is specifically related to the capabilities of inverter interfaced resources to supply unbalanced current/power when the microgrid is islanded from the main distribution grid. We incorporate the new set of constraints into two optimization formulations leveraging two convex relaxations of the three-phase power flow equations: mixed-integer linear programming (MILP) and mixed-integer semidefinite programming (MISDP) that optimize the dispatch of controllable switches and DERs in the microgrid. The algorithms are then extended to networked microgrids with grid-forming sources. We test the algorithms on a realistic community microgrid model in Puerto Rico as well as standardized IEEE distribution test feeders. The testing results demonstrate the performance of the proposed algorithms. The MILP is fast and scalable, and the MISDP enforces the negative sequence voltage constraints.

Suggested Citation

  • Su, Yu & Li, Dingrui & Wang, Fred & Olama, Mohammed & Ferrari, Maximiliano & Ollis, Ben & Liu, Yilu, 2024. "Flexible dynamic boundary microgrid operation considering network and load unbalances," Applied Energy, Elsevier, vol. 371(C).
    • Handle: RePEc:eee:appene:v:371:y:2024:i:c:s030626192401016x
    DOI: 10.1016/j.apenergy.2024.123633
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192401016X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123633?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. 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.
    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. Yongqiang Sun & Xianchun Wang & Lijuan Gao & Haiyue Yang & Kang Zhang & Bingxiang Ji & Huijuan Zhang, 2024. "Multi-Objective Optimal Scheduling for Microgrids—Improved Goose Algorithm," Energies, MDPI, vol. 17(24), pages 1-29, December.

    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. 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).
    2. 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.
    3. 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.
    4. 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.
    5. Jani, Ali & Jadid, Shahram, 2023. "Two-stage energy scheduling framework for multi-microgrid system in market environment," Applied Energy, Elsevier, vol. 336(C).
    6. Abate, Arega Getaneh & Riccardi, Rossana & Ruiz, Carlos, 2022. "Contract design in electricity markets with high penetration of renewables: A two-stage approach," Omega, Elsevier, vol. 111(C).
    7. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    8. Wenhao Zhuo & Andrey V. Savkin, 2019. "Profit Maximizing Control of a Microgrid with Renewable Generation and BESS Based on a Battery Cycle Life Model and Energy Price Forecasting," Energies, MDPI, vol. 12(15), pages 1-17, July.
    9. 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).
    10. Muhyaddin Rawa & Abdullah Abusorrah & Yusuf Al-Turki & Saad Mekhilef & Mostafa H. Mostafa & Ziad M. Ali & Shady H. E. Abdel Aleem, 2020. "Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration," Sustainability, MDPI, vol. 12(23), pages 1-25, December.
    11. González-Garrido, A. & Gaztañaga, H. & Saez-de-Ibarra, A. & Milo, A. & Eguia, P., 2020. "Electricity and reserve market bidding strategy including sizing evaluation and a novel renewable complementarity-based centralized control for storage lifetime enhancement," Applied Energy, Elsevier, vol. 262(C).
    12. 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).
    13. 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).
    14. Nikzad, Mehdi & Samimi, Abouzar, 2021. "Integration of designing price-based demand response models into a stochastic bi-level scheduling of multiple energy carrier microgrids considering energy storage systems," Applied Energy, Elsevier, vol. 282(PA).
    15. Keda Pan & Changhong Xie & Chun Sing Lai & Dongxiao Wang & Loi Lei Lai, 2020. "Photovoltaic Output Power Estimation and Baseline Prediction Approach for a Residential Distribution Network with Behind-the-Meter Systems," Forecasting, MDPI, vol. 2(4), pages 1-18, November.
    16. Yamashita, Daniela Yassuda & Vechiu, Ionel & Gaubert, Jean-Paul, 2020. "A review of hierarchical control for building microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    17. Jun Dong & Peiwen Yang & Shilin Nie, 2019. "Day-Ahead Scheduling Model of the Distributed Small Hydro-Wind-Energy Storage Power System Based on Two-Stage Stochastic Robust Optimization," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
    18. Wang, Y. & Rousis, A. Oulis & Strbac, G., 2022. "Resilience-driven optimal sizing and pre-positioning of mobile energy storage systems in decentralized networked microgrids," Applied Energy, Elsevier, vol. 305(C).
    19. Atherton, John & Hofmeister, Markus & Mosbach, Sebastian & Akroyd, Jethro & Farazi, Feroz & Kraft, Markus, 2023. "British imbalance market paradox: Variable renewable energy penetration in energy markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    20. Matamala, Yolanda & Feijoo, Felipe, 2021. "A two-stage stochastic Stackelberg model for microgrid operation with chance constraints for renewable energy generation uncertainty," Applied Energy, Elsevier, vol. 303(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:appene:v:371:y:2024:i:c:s030626192401016x. 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.