IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i20p5367-d428331.html
   My bibliography  Save this article

Smart Meter Measurement-Based State Estimation for Monitoring of Low-Voltage Distribution Grids

Author

Listed:
  • Karthikeyan Nainar

    (Department of Energy Technology, Aalborg Univerisity, 9220 Aalborg, Denmark)

  • Florin Iov

    (Department of Energy Technology, Aalborg Univerisity, 9220 Aalborg, Denmark)

Abstract

The installation of smart meters at customer premises provides opportunities for the monitoring of distribution grids. This paper addresses the problem of improving the observability of low-voltage distribution grids using smart metering infrastructure. In particular, this paper deals with the application of state estimation algorithm using smart meter measurements for near-real-time monitoring of low-voltage distribution grids. This application is proposed to use a nonlinear weighted least squares method-based algorithm for estimating the node voltages from minimum number of smart meter measurements. This paper mainly deals with sensitivity analysis of the state estimation algorithm with respect to multiple uncertainties for, e.g., measurements errors, line parameter errors, and pseudo-measurements. Simulation studies are conducted to estimate the accuracy of the DSSE under various operating scenarios of a real-life low-voltage grid, and cost-effective ways to improve the accuracy of the state estimation algorithm are also evaluated. The paper concludes that by using smart meter measurements from few locations, voltage profiles of the low-voltage grid can be estimated with reasonable accuracy in near-real-time.

Suggested Citation

  • Karthikeyan Nainar & Florin Iov, 2020. "Smart Meter Measurement-Based State Estimation for Monitoring of Low-Voltage Distribution Grids," Energies, MDPI, vol. 13(20), pages 1-18, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5367-:d:428331
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/20/5367/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/20/5367/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ahmad, Fiaz & Rasool, Akhtar & Ozsoy, Emre & Sekar, Raja & Sabanovic, Asif & Elitaş, Meltem, 2018. "Distribution system state estimation-A step towards smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2659-2671.
    2. Thiago Mota Soares & Ubiratan Holanda Bezerra & Maria Emília de Lima Tostes, 2019. "Full-Observable Three-Phase State Estimation Algorithm Applied to Electric Distribution Grids," Energies, MDPI, vol. 12(7), pages 1-16, April.
    3. McDonald, Jim, 2008. "Adaptive intelligent power systems: Active distribution networks," Energy Policy, Elsevier, vol. 36(12), pages 4346-4351, December.
    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. Ivan Alymov & Moshe Averbukh, 2024. "Monitoring Energy Flows for Efficient Electricity Control in Low-Voltage Smart Grids," Energies, MDPI, vol. 17(9), pages 1-17, April.
    2. Ruipeng Guo & Lilan Dong & Hao Wu & Fangdi Hou & Chen Fang, 2021. "A Practical GERI-Based Method for Identifying Multiple Erroneous Parameters and Measurements Simultaneously," Energies, MDPI, vol. 14(12), pages 1-21, June.
    3. Sepideh Radhoush & Bradley M. Whitaker & Hashem Nehrir, 2023. "An Overview of Supervised Machine Learning Approaches for Applications in Active Distribution Networks," Energies, MDPI, vol. 16(16), pages 1-29, August.
    4. Karthikeyan Nainar & Florin Iov, 2021. "Three-Phase State Estimation for Distribution-Grid Analytics," Clean Technol., MDPI, vol. 3(2), pages 1-14, May.
    5. Fabio Napolitano & Juan Diego Rios Penaloza & Fabio Tossani & Alberto Borghetti & Carlo Alberto Nucci, 2021. "Three-Phase State Estimation of a Low-Voltage Distribution Network with Kalman Filter," Energies, MDPI, vol. 14(21), pages 1-19, November.
    6. Jingyeong Park & Daisuke Kodaira & Kofi Afrifa Agyeman & Taeyoung Jyung & Sekyung Han, 2021. "Adaptive Power Flow Prediction Based on Machine Learning," Energies, MDPI, vol. 14(13), pages 1-18, June.

    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. Karthikeyan Nainar & Florin Iov, 2021. "Three-Phase State Estimation for Distribution-Grid Analytics," Clean Technol., MDPI, vol. 3(2), pages 1-14, May.
    2. Edward J. Smith & Duane A. Robinson & Sean Elphick, 2024. "DER Control and Management Strategies for Distribution Networks: A Review of Current Practices and Future Directions," Energies, MDPI, vol. 17(11), pages 1-40, May.
    3. Sander Claeys & Marta Vanin & Frederik Geth & Geert Deconinck, 2021. "Applications of optimization models for electricity distribution networks," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(5), September.
    4. Hao Xiao & Wei Pei & Zuomin Dong & Li Kong & Dan Wang, 2018. "Application and Comparison of Metaheuristic and New Metamodel Based Global Optimization Methods to the Optimal Operation of Active Distribution Networks," Energies, MDPI, vol. 11(1), pages 1-29, January.
    5. Oleksandr Miroshnyk & Oleksandr Moroz & Taras Shchur & Andrii Chepizhnyi & Mohamed Qawaqzeh & Sławomir Kocira, 2023. "Investigation of Smart Grid Operation Modes with Electrical Energy Storage System," Energies, MDPI, vol. 16(6), pages 1-13, March.
    6. Darius Corbier & Frédéric Gonand & Marie Bessec, 2015. "Impacts of decentralised power generation on distribution networks: a statistical typology of European countries," Working Papers 1509, Chaire Economie du climat.
    7. Lefeng, Shi & Shengnan, Lv & Chunxiu, Liu & Yue, Zhou & Cipcigan, Liana & Acker, Thomas L., 2020. "A framework for electric vehicle power supply chain development," Utilities Policy, Elsevier, vol. 64(C).
    8. de Joode, J. & Jansen, J.C. & van der Welle, A.J. & Scheepers, M.J.J., 2009. "Increasing penetration of renewable and distributed electricity generation and the need for different network regulation," Energy Policy, Elsevier, vol. 37(8), pages 2907-2915, August.
    9. Israa T. Aziz & Hai Jin & Ihsan H. Abdulqadder & Sabah M. Alturfi & Wisam H. Alobaidi & Firas M.F. Flaih, 2019. "T 2 S 2 G: A Novel Two-Tier Secure Smart Grid Architecture to Protect Network Measurements," Energies, MDPI, vol. 12(13), pages 1-24, July.
    10. István Táczi & Bálint Sinkovics & István Vokony & Bálint Hartmann, 2021. "The Challenges of Low Voltage Distribution System State Estimation—An Application Oriented Review," Energies, MDPI, vol. 14(17), pages 1-17, August.
    11. Aqdas Naz & Nadeem Javaid & Muhammad Babar Rasheed & Abdul Haseeb & Musaed Alhussein & Khursheed Aurangzeb, 2019. "Game Theoretical Energy Management with Storage Capacity Optimization and Photo-Voltaic Cell Generated Power Forecasting in Micro Grid," Sustainability, MDPI, vol. 11(10), pages 1-22, May.
    12. Veldman, Else & Gibescu, Madeleine & Slootweg, Han (J.G.) & Kling, Wil L., 2013. "Scenario-based modelling of future residential electricity demands and assessing their impact on distribution grids," Energy Policy, Elsevier, vol. 56(C), pages 233-247.
    13. Fabio Napolitano & Juan Diego Rios Penaloza & Fabio Tossani & Alberto Borghetti & Carlo Alberto Nucci, 2021. "Three-Phase State Estimation of a Low-Voltage Distribution Network with Kalman Filter," Energies, MDPI, vol. 14(21), pages 1-19, November.
    14. Yuan, Jiahai & Xu, Yan & Hu, Zhaoguang, 2012. "Delivering power system transition in China," Energy Policy, Elsevier, vol. 50(C), pages 751-772.
    15. Ghadi, M. Jabbari & Ghavidel, Sahand & Rajabi, Amin & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2019. "A review on economic and technical operation of active distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 38-53.
    16. Poppen, Silvia, 2014. "Auswirkungen dezentraler Erzeugungsanlagen auf das Stromversorgungssystem: Ausgestaltungsmöglichkeiten der Bereitstellung neuer Erzeugungsanlagen," Arbeitspapiere 146, University of Münster, Institute for Cooperatives.
    17. Margossian, Harag & Kfouri, Ronald & Saliba, Rita, 2023. "Measurement protection to prevent cyber–physical attacks against power system State Estimation," International Journal of Critical Infrastructure Protection, Elsevier, vol. 43(C).
    18. Gilbert Ahamer, 2022. "Why Biomass Fuels Are Principally Not Carbon Neutral," Energies, MDPI, vol. 15(24), pages 1-39, December.
    19. Ilia Shushpanov & Konstantin Suslov & Pavel Ilyushin & Denis N. Sidorov, 2021. "Towards the Flexible Distribution Networks Design Using the Reliability Performance Metric," Energies, MDPI, vol. 14(19), pages 1-24, September.
    20. Brown, Stephen & Pyke, David & Steenhof, Paul, 2010. "Electric vehicles: The role and importance of standards in an emerging market," Energy Policy, Elsevier, vol. 38(7), pages 3797-3806, July.

    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:13:y:2020:i:20:p:5367-:d:428331. 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.