IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i11p3878-d823239.html
   My bibliography  Save this article

Optimal Deployment of Mobile MSSSC in Transmission System

Author

Listed:
  • Zhehan Zhao

    (School of Electrical and Electronic, University College Dublin, D04 V1W8 Dublin, Ireland
    These authors contributed equally to this work.)

  • Alireza Soroudi

    (School of Electrical and Electronic, University College Dublin, D04 V1W8 Dublin, Ireland
    These authors contributed equally to this work.)

Abstract

With the rapid development of the renewable energy source (RES), network congestion management is increasingly important for transmission system operators (TSOs). The limited transmission network capacity and traditional intervention methods result in high RES curtailment. The near-term, powerful, and flexible solutions, such as advanced flexible AC transmission systems (FACTS), are considered to mitigate the risks. The mobile modular static synchronous series compensator (MSSSC) is one of the grid-enhancing solutions. The mobility of the solution allows it to offer fast deployment and seasonal redeployability with limited cost. The demonstration of the mobile MSSSC solution has shown significant benefits for RES curtailment reduction, network congestion alleviation, and facilitating the demand and RES connection. For unlocking the true value of the mobile solution, they should be optimally allocated in the transmission networks. This paper develops a security-constrained DCOPF-based optimisation tool to investigate the optimal allocation of the mobile MSSSC solution in transmission networks. A linear mobile MSSSC model with the operation dead-band was introduced that can be used in large-scale realistic power system planning. The proposed model was implemented in the IEEE 118-bus system to assess the performance of the mobile MSSSC.

Suggested Citation

  • Zhehan Zhao & Alireza Soroudi, 2022. "Optimal Deployment of Mobile MSSSC in Transmission System," Energies, MDPI, vol. 15(11), pages 1-27, May.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:3878-:d:823239
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/11/3878/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/11/3878/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hedayat Saboori & Shahram Jadid & Mehdi Savaghebi, 2021. "Optimal Management of Mobile Battery Energy Storage as a Self-Driving, Self-Powered and Movable Charging Station to Promote Electric Vehicle Adoption," Energies, MDPI, vol. 14(3), pages 1-19, January.
    2. William E. Hart & Carl D. Laird & Jean-Paul Watson & David L. Woodruff & Gabriel A. Hackebeil & Bethany L. Nicholson & John D. Siirola, 2017. "Pyomo — Optimization Modeling in Python," Springer Optimization and Its Applications, Springer, edition 2, number 978-3-319-58821-6, December.
    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. Mahtab Kaffash & Glenn Ceusters & Geert Deconinck, 2021. "Interval Optimization to Schedule a Multi-Energy System with Data-Driven PV Uncertainty Representation," Energies, MDPI, vol. 14(10), pages 1-20, May.
    2. John V. Colias & Stella Park & Elizabeth Horn, 2021. "Optimizing B2B product offers with machine learning, mixed logit, and nonlinear programming," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 157-172, September.
    3. Pelagie Elimbi Moudio & Cristobal Pais & Zuo-Jun Max Shen, 2021. "Quantifying the impact of ecosystem services for landscape management under wildfire hazard," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(1), pages 531-560, March.
    4. David E. Bernal & Zedong Peng & Jan Kronqvist & Ignacio E. Grossmann, 2022. "Alternative regularizations for Outer-Approximation algorithms for convex MINLP," Journal of Global Optimization, Springer, vol. 84(4), pages 807-842, December.
    5. Yikai Liu & Ruozheng Wu & Aimin Yang, 2023. "Research on Medical Problems Based on Mathematical Models," Mathematics, MDPI, vol. 11(13), pages 1-26, June.
    6. Hedayat Saboori & Shahram Jadid & Mehdi Savaghebi, 2021. "Spatio-Temporal and Power–Energy Scheduling of Mobile Battery Storage for Mitigating Wind and Solar Energy Curtailment in Distribution Networks," Energies, MDPI, vol. 14(16), pages 1-19, August.
    7. repec:cte:wsrepe:34605 is not listed on IDEAS
    8. Sigler, Devon & Wang, Qichao & Liu, Zhaocai & Garikapati, Venu & Kotz, Andrew & Kelly, Kenneth J. & Lunacek, Monte & Phillips, Caleb, 2021. "Route optimization for energy efficient airport shuttle operations – A case study from Dallas Fort worth International Airport," Journal of Air Transport Management, Elsevier, vol. 94(C).
    9. Jens Baetens & Jeroen D. M. De Kooning & Greet Van Eetvelde & Lieven Vandevelde, 2020. "A Two-Stage Stochastic Optimisation Methodology for the Operation of a Chlor-Alkali Electrolyser under Variable DAM and FCR Market Prices," Energies, MDPI, vol. 13(21), pages 1-19, October.
    10. Löschenbrand, Markus, 2021. "Modeling competition of virtual power plants via deep learning," Energy, Elsevier, vol. 214(C).
    11. Golsefidi, Atefeh Hemmati & Hüttel, Frederik Boe & Peled, Inon & Samaranayake, Samitha & Pereira, Francisco Câmara, 2023. "A joint machine learning and optimization approach for incremental expansion of electric vehicle charging infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    12. Mehrjerdi, Hasan & Mahdavi, Sajad & Hemmati, Reza, 2021. "Resilience maximization through mobile battery storage and diesel DG in integrated electrical and heating networks," Energy, Elsevier, vol. 237(C).
    13. repec:cte:wsrepe:36072 is not listed on IDEAS
    14. Afshar, Shahab & Pecenak, Zachary K. & Barati, Masoud & Disfani, Vahid, 2022. "Mobile charging stations for EV charging management in urban areas: A case study in Chattanooga," Applied Energy, Elsevier, vol. 325(C).
    15. repec:cte:wsrepe:35425 is not listed on IDEAS
    16. Mascherbauer, Philipp & Kranzl, Lukas & Yu, Songmin & Haupt, Thomas, 2022. "Investigating the impact of smart energy management system on the residential electricity consumption in Austria," Working Papers "Sustainability and Innovation" S04/2022, Fraunhofer Institute for Systems and Innovation Research (ISI).
    17. Ballis, Haris & Dimitriou, Loukas, 2020. "Revealing personal activities schedules from synthesizing multi-period origin-destination matrices," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 224-258.
    18. Afshar, Shahab & Macedo, Pablo & Mohamed, Farog & Disfani, Vahid, 2021. "Mobile charging stations for electric vehicles — A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    19. Salgado, Marcelo & Negrete-Pincetic, Matias & Lorca, Álvaro & Olivares, Daniel, 2021. "A low-complexity decision model for home energy management systems," Applied Energy, Elsevier, vol. 294(C).
    20. John V. Colias & Stella Park & Elizabeth Horn, 2023. "Optimizing B2B Product Offers with Machine Learning, Mixed Logit, and Nonlinear Programming," Papers 2308.07830, arXiv.org.
    21. Nnaemeka Vincent Emodi & Scott Dwyer & Kriti Nagrath & John Alabi, 2022. "Electromobility in Australia: Tariff Design Structure and Consumer Preferences for Mobile Distributed Energy Storage," Sustainability, MDPI, vol. 14(11), pages 1-18, May.
    22. Piao, Longjian & de Vries, Laurens & de Weerdt, Mathijs & Yorke-Smith, Neil, 2021. "Electricity markets for DC distribution systems: Locational pricing trumps wholesale pricing," Energy, Elsevier, vol. 214(C).
    23. Hyung-Wook Kang & Hyun-Seong Lee & Jae-Ho Rhee & Kun-A Lee, 2023. "DC Voltage Source Based on a Battery of Supercapacitors with a Regulator in the Form of an Isolated Boost LCC Resonant Converter," Energies, MDPI, vol. 16(18), pages 1-15, September.

    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:15:y:2022:i:11:p:3878-:d:823239. 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.