IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i21p7442-d674682.html
   My bibliography  Save this article

Optimal Sizing of Battery Energy Storage Systems Considering Cooperative Operation with Microgrid Components

Author

Listed:
  • Hirotaka Takano

    (Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan)

  • Ryosuke Hayashi

    (Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan)

  • Hiroshi Asano

    (Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan
    Central Research Institute of Electric Power Industry, 2-6-1 Nagasaka, Yokosuka-shi 240-0196, Japan)

  • Tadahiro Goda

    (Aichi Institute of Technology, Toyota 470-0392, Japan)

Abstract

Battery energy storage systems (BESSs) are key components in efficiently managing the electric power supply and demand in microgrids. However, the BESSs have issues in their investment costs and operating lifetime, and thus, the optimal sizing of the BESSs is one of the crucial requirements in design and management of the microgrids. This paper presents a problem framework and its solution method that calculates the optimal size of the BESSs in a microgrid, considering their cooperative operations with the other components. The proposed framework is formulated as a bi-level optimization problem; however, based on the Karush–Kuhn–Tucker approach, it is regarded as a type of operation scheduling problem. As a result, the techniques developed for determining the operation schedule become applicable. In this paper, a combined algorithm of binary particle swarm optimization and quadratic programming is selected as the basis of the solution method. The validity of the authors’ proposal is verified through numerical simulations and discussion of their results.

Suggested Citation

  • Hirotaka Takano & Ryosuke Hayashi & Hiroshi Asano & Tadahiro Goda, 2021. "Optimal Sizing of Battery Energy Storage Systems Considering Cooperative Operation with Microgrid Components," Energies, MDPI, vol. 14(21), pages 1-13, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7442-:d:674682
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/21/7442/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/21/7442/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hirotaka Takano & Ryota Goto & Thin Zar Soe & Nguyen Duc Tuyen & Hiroshi Asano, 2019. "Operation Scheduling Optimization for Microgrids Considering Coordination of Their Components," Future Internet, MDPI, vol. 11(11), pages 1-11, October.
    2. Stein, Oliver & Still, Georg, 2002. "On generalized semi-infinite optimization and bilevel optimization," European Journal of Operational Research, Elsevier, vol. 142(3), pages 444-462, November.
    3. Hirotaka Takano & Ryota Goto & Ryosuke Hayashi & Hiroshi Asano, 2021. "Optimization Method for Operation Schedule of Microgrids Considering Uncertainty in Available Data," Energies, MDPI, vol. 14(9), pages 1-13, April.
    4. Benoît Colson & Patrice Marcotte & Gilles Savard, 2007. "An overview of bilevel optimization," Annals of Operations Research, Springer, vol. 153(1), pages 235-256, September.
    5. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
    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. Hajra Khan & Imran Fareed Nizami & Saeed Mian Qaisar & Asad Waqar & Moez Krichen & Abdulaziz Turki Almaktoom, 2022. "Analyzing Optimal Battery Sizing in Microgrids Based on the Feature Selection and Machine Learning Approaches," Energies, MDPI, vol. 15(21), pages 1-22, October.
    2. Md. Mahamudul Hasan & Boris Berseneff & Tim Meulenbroeks & Igor Cantero & Sajib Chakraborty & Thomas Geury & Omar Hegazy, 2022. "A Multi-Objective Co-Design Optimization Framework for Grid-Connected Hybrid Battery Energy Storage Systems: Optimal Sizing and Selection of Technology," Energies, MDPI, vol. 15(15), pages 1-21, July.
    3. Khairul Eahsun Fahim & Liyanage C. De Silva & Fayaz Hussain & Hayati Yassin, 2023. "A State-of-the-Art Review on Optimization Methods and Techniques for Economic Load Dispatch with Photovoltaic Systems: Progress, Challenges, and Recommendations," Sustainability, MDPI, vol. 15(15), pages 1-29, August.
    4. Haipeng Wang & Xuewei Wu & Kai Sun & Xiaodong Du & Yuling He & Kaiwen Li, 2023. "Economic Dispatch Optimization of a Microgrid with Wind–Photovoltaic-Load-Storage in Multiple Scenarios," Energies, MDPI, vol. 16(9), pages 1-16, May.
    5. Irina Picioroaga & Madalina Luca & Andrei Tudose & Dorian Sidea & Mircea Eremia & Constantin Bulac, 2023. "Resilience-Driven Optimal Sizing of Energy Storage Systems in Remote Microgrids," Sustainability, MDPI, vol. 15(22), pages 1-16, November.

    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. R. Paulavičius & C. S. Adjiman, 2020. "New bounding schemes and algorithmic options for the Branch-and-Sandwich algorithm," Journal of Global Optimization, Springer, vol. 77(2), pages 197-225, June.
    2. Polyxeni-Margarita Kleniati & Claire Adjiman, 2014. "Branch-and-Sandwich: a deterministic global optimization algorithm for optimistic bilevel programming problems. Part I: Theoretical development," Journal of Global Optimization, Springer, vol. 60(3), pages 425-458, November.
    3. Carvalho, Margarida & Lodi, Andrea, 2023. "A theoretical and computational equilibria analysis of a multi-player kidney exchange program," European Journal of Operational Research, Elsevier, vol. 305(1), pages 373-385.
    4. Andreas Lanz & Gregor Reich & Ole Wilms, 2022. "Adaptive grids for the estimation of dynamic models," Quantitative Marketing and Economics (QME), Springer, vol. 20(2), pages 179-238, June.
    5. Shi, Yi & Deng, Yawen & Wang, Guoan & Xu, Jiuping, 2020. "Stackelberg equilibrium-based eco-economic approach for sustainable development of kitchen waste disposal with subsidy policy: A case study from China," Energy, Elsevier, vol. 196(C).
    6. Lucio Bianco & Massimiliano Caramia & Stefano Giordani & Veronica Piccialli, 2016. "A Game-Theoretic Approach for Regulating Hazmat Transportation," Transportation Science, INFORMS, vol. 50(2), pages 424-438, May.
    7. M. Köppe & M. Queyranne & C. T. Ryan, 2010. "Parametric Integer Programming Algorithm for Bilevel Mixed Integer Programs," Journal of Optimization Theory and Applications, Springer, vol. 146(1), pages 137-150, July.
    8. Xu, Jiuping & Shu, Kejing & Wang, Fengjuan & Yang, Guocan, 2024. "Bi-level multi-objective distribution strategy integrating the permit trading scheme towards coal production capacity layout optimization: Case study from China," Resources Policy, Elsevier, vol. 91(C).
    9. Cerulli, Martina & Serra, Domenico & Sorgente, Carmine & Archetti, Claudia & Ljubić, Ivana, 2023. "Mathematical programming formulations for the Collapsed k-Core Problem," European Journal of Operational Research, Elsevier, vol. 311(1), pages 56-72.
    10. Chan Y. Han & Brian J. Lunday & Matthew J. Robbins, 2016. "A Game Theoretic Model for the Optimal Location of Integrated Air Defense System Missile Batteries," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 405-416, August.
    11. Lorenzo Lampariello & Simone Sagratella, 2015. "It is a matter of hierarchy: a Nash equilibrium problem perspective on bilevel programming," DIAG Technical Reports 2015-07, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    12. Stein, Oliver, 2012. "How to solve a semi-infinite optimization problem," European Journal of Operational Research, Elsevier, vol. 223(2), pages 312-320.
    13. Abbaspour, M. & Satkin, M. & Mohammadi-Ivatloo, B. & Hoseinzadeh Lotfi, F. & Noorollahi, Y., 2013. "Optimal operation scheduling of wind power integrated with compressed air energy storage (CAES)," Renewable Energy, Elsevier, vol. 51(C), pages 53-59.
    14. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    15. Grimm, Veronika & Schewe, Lars & Schmidt, Martin & Zöttl, Gregor, 2017. "Uniqueness of market equilibrium on a network: A peak-load pricing approach," European Journal of Operational Research, Elsevier, vol. 261(3), pages 971-983.
    16. Wei Jiang & Huiqiang Wang & Bingyang Li & Haibin Lv & Qingchuan Meng, 2020. "A multi-user multi-operator computing pricing method for Internet of things based on bi-level optimization," International Journal of Distributed Sensor Networks, , vol. 16(1), pages 15501477199, January.
    17. Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
    18. Martin Weibelzahl & Alexandra Märtz, 2020. "Optimal storage and transmission investments in a bilevel electricity market model," Annals of Operations Research, Springer, vol. 287(2), pages 911-940, April.
    19. Keon Baek & Woong Ko & Jinho Kim, 2019. "Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract," Energies, MDPI, vol. 12(14), pages 1-19, July.
    20. Thiaux, Yaël & Dang, Thu Thuy & Schmerber, Louis & Multon, Bernard & Ben Ahmed, Hamid & Bacha, Seddik & Tran, Quoc Tuan, 2019. "Demand-side management strategy in stand-alone hybrid photovoltaic systems with real-time simulation of stochastic electricity consumption behavior," Applied Energy, Elsevier, vol. 253(C), pages 1-1.

    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:gam:jeners:v:14:y:2021:i:21:p:7442-:d:674682. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.