IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i11p4530-d1164368.html
   My bibliography  Save this article

Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors

Author

Listed:
  • Gian Paramo

    (Department of Electrical & Computer Engineering, University of Florida, Gainesville, FL 32608, USA)

  • Arturo Bretas

    (Department of Electrical & Computer Engineering, University of Florida, Gainesville, FL 32608, USA
    Pacific Northwest National Laboratory, Richland, WA 99352, USA)

Abstract

The reactive nature of traditional under-frequency load shedding schemes can lead to delayed response and unnecessary loss of load. This work presents a proactive framework for power system frequency stability. Bayesian filters and synchrophasors are leveraged to produce predictions after disturbances are detected. By being able to estimate the future state of frequency corrective actions can be taken before the system reaches a critical condition. This proactive approach makes it possible to optimize the response to a disturbance, which results in a decrease in the amount of compensation utilized. The framework is tested via Matlab simulations based on Kundur’s Two-Area System, and the IEEE 14-Bus System. Performance metrics are provided and evaluated against other contemporary solutions found in literature. During testing this framework outperformed other solutions by drastically reducing the amount of load dropped during compensation.

Suggested Citation

  • Gian Paramo & Arturo Bretas, 2023. "Proactive Frequency Stability Scheme: A Distributed Framework Based on Particle Filters and Synchrophasors," Energies, MDPI, vol. 16(11), pages 1-19, June.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:11:p:4530-:d:1164368
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/11/4530/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/11/4530/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gian Paramo & Arturo Bretas & Sean Meyn, 2022. "Research Trends and Applications of PMUs," Energies, MDPI, vol. 15(15), pages 1-32, July.
    2. Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
    3. Antans Sauhats & Andrejs Utans & Jurijs Silinevics & Gatis Junghans & Dmitrijs Guzs, 2021. "Enhancing Power System Frequency with a Novel Load Shedding Method Including Monitoring of Synchronous Condensers’ Power Injections," Energies, MDPI, vol. 14(5), pages 1-21, March.
    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. Murilo Eduardo Casteroba Bento, 2023. "Wide-Area Measurement-Based Two-Level Control Design to Tolerate Permanent Communication Failures," Energies, MDPI, vol. 16(15), pages 1-15, July.
    2. Farahmand, H. & Doorman, G.L., 2012. "Balancing market integration in the Northern European continent," Applied Energy, Elsevier, vol. 96(C), pages 316-326.
    3. Moo-Sung Sohn & Jiwoong Choi & Hoseog Kang & In-Chan Choi, 2017. "Multiobjective Production Planning at LG Display," Interfaces, INFORMS, vol. 47(4), pages 279-291, August.
    4. Hussain A. Alhaiz & Ahmed S. Alsafran & Ali H. Almarhoon, 2023. "Single-Phase Microgrid Power Quality Enhancement Strategies: A Comprehensive Review," Energies, MDPI, vol. 16(14), pages 1-28, July.
    5. Grzegorz Bocewicz & Zbigniew Banaszak & Izabela Nielsen, 2019. "Multimodal processes prototyping subject to grid-like network and fuzzy operation time constraints," Annals of Operations Research, Springer, vol. 273(1), pages 561-585, February.
    6. Alix Vargas & Carmen Fuster & David Corne, 2020. "Towards Sustainable Collaborative Logistics Using Specialist Planning Algorithms and a Gain-Sharing Business Model: A UK Case Study," Sustainability, MDPI, vol. 12(16), pages 1-29, August.
    7. Mohammad Heydari & Kin Keung Lai, 2023. "Post-COVID-19 Pandemic Era and Sustainable Healthcare: Organization and Delivery of Health Economics Research (Principles and Clinical Practice)," Mathematics, MDPI, vol. 11(16), pages 1-30, August.
    8. Khayyam, Hamid & Naebe, Minoo & Bab-Hadiashar, Alireza & Jamshidi, Farshid & Li, Quanxiang & Atkiss, Stephen & Buckmaster, Derek & Fox, Bronwyn, 2015. "Stochastic optimization models for energy management in carbonization process of carbon fiber production," Applied Energy, Elsevier, vol. 158(C), pages 643-655.
    9. Karol Makowiecki & Aleksander Lisowiec & Pawel Michalski & Marcin Habrych, 2022. "UTC Synchronized Signal Generation for Synchrophasors and Sampled Values Measurements," Energies, MDPI, vol. 15(19), pages 1-14, September.
    10. Ioannis Fragkos & Bert De Reyck, 2016. "Improving the Maritime Transshipment Operations of the Noble Group," Interfaces, INFORMS, vol. 46(3), pages 203-217, April.
    11. Chung, S.H. & Lau, H.C.W. & Choy, K.L. & Ho, G.T.S. & Tse, Y.K., 2010. "Application of genetic approach for advanced planning in multi-factory environment," International Journal of Production Economics, Elsevier, vol. 127(2), pages 300-308, October.
    12. Bohle, Carlos & Maturana, Sergio & Vera, Jorge, 2010. "A robust optimization approach to wine grape harvesting scheduling," European Journal of Operational Research, Elsevier, vol. 200(1), pages 245-252, January.
    13. Pulluru, Sai Jishna & Akkerman, Renzo, 2018. "Water-integrated scheduling of batch process plants: Modelling approach and application in technology selection," European Journal of Operational Research, Elsevier, vol. 269(1), pages 227-243.
    14. M. Saqlain & S. Ali & J. Y. Lee, 2023. "A Monte-Carlo tree search algorithm for the flexible job-shop scheduling in manufacturing systems," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 548-571, June.
    15. Laing, Harry & O'Malley, Chris & Browne, Anthony & Rutherford, Tony & Baines, Tony & Moore, Andrew & Black, Ken & Willis, Mark J., 2022. "Optimisation of energy usage and carbon emissions monitoring using MILP for an advanced anaerobic digester plant," Energy, Elsevier, vol. 256(C).
    16. Olivér Ősz & Balázs Ferenczi & Máté Hegyháti, 2020. "Scheduling a forge with due dates and die deterioration," Annals of Operations Research, Springer, vol. 285(1), pages 353-367, February.
    17. Wolfgang Albrecht & Martin Steinrücke, 2020. "Continuous-time scheduling of production, distribution and sales in photovoltaic supply chains with declining prices," Flexible Services and Manufacturing Journal, Springer, vol. 32(3), pages 629-667, September.
    18. Sumit Bose & Subir Bhattacharya, 2008. "A two pass heuristic algorithm for scheduling ‘blocked out’ units in continuous process industry," Annals of Operations Research, Springer, vol. 159(1), pages 293-313, March.
    19. Lara, Cristiana L. & Koenemann, Jochen & Nie, Yisu & de Souza, Cid C., 2023. "Scalable timing-aware network design via lagrangian decomposition," European Journal of Operational Research, Elsevier, vol. 309(1), pages 152-169.
    20. Yanina Fumero & Gabriela Corsano & Jorge Montagna, 2012. "Planning and scheduling of multistage multiproduct batch plants operating under production campaigns," Annals of Operations Research, Springer, vol. 199(1), pages 249-268, October.

    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:16:y:2023:i:11:p:4530-:d:1164368. 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.