IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i22p6054-d447619.html
   My bibliography  Save this article

A Distribution System State Estimator Based on an Extended Kalman Filter Enhanced with a Prior Evaluation of Power Injections at Unmonitored Buses

Author

Listed:
  • David Macii

    (Department of Industrial Engineering, University of Trento, via Sommarive, 9, 38123 Trento, Italy)

  • Daniele Fontanelli

    (Department of Industrial Engineering, University of Trento, via Sommarive, 9, 38123 Trento, Italy)

  • Grazia Barchi

    (EURAC Research, Institute for Renewable Energy, via Alessandro Volta, 13/A, 39100 Bozen-Bolzano, Italy)

Abstract

In the context of smart grids, Distribution Systems State Estimation (DSSE) is notoriously problematic because of the scarcity of available measurement points and the lack of real-time information on loads. The scarcity of measurement data influences on the effectiveness and applicability of dynamic estimators like the Kalman filters. However, if an Extended Kalman Filter (EKF) resulting from the linearization of the power flow equations is complemented by an ancillary prior least-squares estimation of the weekly active and reactive power injection variations at all buses, significant performance improvements can be achieved. Extensive simulation results obtained assuming to deploy an increasing number of next-generation smart meters and Phasor Measurement Units (PMUs) show that not only the proposed approach is generally more accurate and precise than the classic Weighted Least Squares (WLS) estimator (chosen as a benchmark algorithm), but it is also less sensitive to both the number and the metrological features of the PMUs. Thus, low-uncertainty state estimates can be obtained even though fewer and cheaper measurement devices are used.

Suggested Citation

  • David Macii & Daniele Fontanelli & Grazia Barchi, 2020. "A Distribution System State Estimator Based on an Extended Kalman Filter Enhanced with a Prior Evaluation of Power Injections at Unmonitored Buses," Energies, MDPI, vol. 13(22), pages 1-25, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:6054-:d:447619
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/22/6054/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/22/6054/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sandels, C. & Widén, J. & Nordström, L., 2014. "Forecasting household consumer electricity load profiles with a combined physical and behavioral approach," Applied Energy, Elsevier, vol. 131(C), pages 267-278.
    2. Dai Wang & Xiaohong Guan & Ting Liu & Yun Gu & Chao Shen & Zhanbo Xu, 2014. "Extended Distributed State Estimation: A Detection Method against Tolerable False Data Injection Attacks in Smart Grids," Energies, MDPI, vol. 7(3), pages 1-22, March.
    3. Marco Todescato & Ruggero Carli & Luca Schenato & Grazia Barchi, 2020. "Smart Grid State Estimation with PMUs Time Synchronization Errors," Energies, MDPI, vol. 13(19), pages 1-20, October.
    4. Sandels, C. & Brodén, D. & Widén, J. & Nordström, L. & Andersson, E., 2016. "Modeling office building consumer load with a combined physical and behavioral approach: Simulation and validation," Applied Energy, Elsevier, vol. 162(C), pages 472-485.
    5. Basanta Raj Pokhrel & Birgitte Bak-Jensen & Jayakrishnan R. Pillai, 2019. "Integrated Approach for Network Observability and State Estimation in Active Distribution Grid," Energies, MDPI, vol. 12(12), pages 1-17, June.
    6. 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.
    7. Carstens, Herman & Xia, Xiaohua & Yadavalli, Sarma, 2018. "Measurement uncertainty in energy monitoring: Present state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2791-2805.
    8. Alessandro Pitì & Giacomo Verticale & Cristina Rottondi & Antonio Capone & Luca Lo Schiavo, 2017. "The Role of Smart Meters in Enabling Real-Time Energy Services for Households: The Italian Case," Energies, MDPI, vol. 10(2), pages 1-25, February.
    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. Enrico Dalla Maria & Mattia Secchi & David Macii, 2021. "A Flexible Top-Down Data-Driven Stochastic Model for Synthetic Load Profiles Generation," Energies, MDPI, vol. 15(1), pages 1-20, December.
    2. Marco Pau & Paolo Attilio Pegoraro, 2022. "Monitoring and Automation of Complex Power Systems," Energies, MDPI, vol. 15(8), pages 1-3, April.
    3. Junjun Xu & Yulong Jin & Tao Zheng & Gaojun Meng, 2023. "On State Estimation Modeling of Smart Distribution Networks: A Technical Review," Energies, MDPI, vol. 16(4), pages 1-19, February.

    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. Mihai Sanduleac & Gianluca Lipari & Antonello Monti & Artemis Voulkidis & Gianluca Zanetto & Antonello Corsi & Lucian Toma & Giampaolo Fiorentino & Dumitru Federenciuc, 2017. "Next Generation Real-Time Smart Meters for ICT Based Assessment of Grid Data Inconsistencies," Energies, MDPI, vol. 10(7), pages 1-16, June.
    2. Kazmi, Hussain & Munné-Collado, Íngrid & Mehmood, Fahad & Syed, Tahir Abbas & Driesen, Johan, 2021. "Towards data-driven energy communities: A review of open-source datasets, models and tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    3. Ntumba Marc-Alain Mutombo & Bubele Papy Numbi, 2022. "Development of a Linear Regression Model Based on the Most Influential Predictors for a Research Office Cooling Load," Energies, MDPI, vol. 15(14), pages 1-20, July.
    4. Giovanni Artale & Giuseppe Caravello & Antonio Cataliotti & Valentina Cosentino & Dario Di Cara & Salvatore Guaiana & Ninh Nguyen Quang & Marco Palmeri & Nicola Panzavecchia & Giovanni Tinè, 2020. "A Virtual Tool for Load Flow Analysis in a Micro-Grid," Energies, MDPI, vol. 13(12), pages 1-26, June.
    5. Giovanni Artale & Antonio Cataliotti & Valentina Cosentino & Dario Di Cara & Salvatore Guaiana & Enrico Telaretti & Nicola Panzavecchia & Giovanni Tinè, 2019. "Incremental Heuristic Approach for Meter Placement in Radial Distribution Systems," Energies, MDPI, vol. 12(20), pages 1-17, October.
    6. 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.
    7. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    8. Tomasi, Silvia, 2022. "The (Non) impact of the Spanish “Tax on the Sun” on photovoltaics prosumers uptake," Energy Policy, Elsevier, vol. 168(C).
    9. Giovanni Pau & Mario Collotta & Antonio Ruano & Jiahu Qin, 2017. "Smart Home Energy Management," Energies, MDPI, vol. 10(3), pages 1-5, March.
    10. Giacomo Valente & Vittoriano Muttillo & Mirco Muttillo & Gianluca Barile & Alfiero Leoni & Walter Tiberti & Luigi Pomante, 2019. "SPOF—Slave Powerlink on FPGA for Smart Sensors and Actuators Interfacing for Industry 4.0 Applications," Energies, MDPI, vol. 12(9), pages 1-13, April.
    11. Knobel, Alexander & Chokaev, Bekhan, 2014. "Possible Economic Outcomes of a Trade Agreement with the European Union," EconStor Preprints 121853, ZBW - Leibniz Information Centre for Economics.
    12. Fuentes, E. & Arce, L. & Salom, J., 2018. "A review of domestic hot water consumption profiles for application in systems and buildings energy performance analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1530-1547.
    13. Daniel Sousa-Dias & Daniel Amyot & Ashkan Rahimi-Kian & John Mylopoulos, 2023. "A Review of Cybersecurity Concerns for Transactive Energy Markets," Energies, MDPI, vol. 16(13), pages 1-32, June.
    14. Ildar Daminov & Rémy Rigo-Mariani & Raphael Caire & Anton Prokhorov & Marie-Cécile Alvarez-Hérault, 2021. "Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime," Energies, MDPI, vol. 14(5), pages 1-27, March.
    15. Naser Hossein Motlagh & Mahsa Mohammadrezaei & Julian Hunt & Behnam Zakeri, 2020. "Internet of Things (IoT) and the Energy Sector," Energies, MDPI, vol. 13(2), pages 1-27, January.
    16. García-Villalobos, J. & Zamora, I. & Knezović, K. & Marinelli, M., 2016. "Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks," Applied Energy, Elsevier, vol. 180(C), pages 155-168.
    17. Hegazy Rezk & Rania M. Ghoniem & Seydali Ferahtia & Ahmed Fathy & Mohamed M. Ghoniem & Reem Alkanhel, 2022. "A Comparison of Different Renewable-Based DC Microgrid Energy Management Strategies for Commercial Buildings Applications," Sustainability, MDPI, vol. 14(24), pages 1-22, December.
    18. 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.
    19. Helmo K. Morales Paredes & Matheus Branco Arcadepani & Alexandre Candido Moreira & Flávio A. Serrão Gonçalves & Fernando Pinhabel Marafão, 2023. "Enlightening Load Modeling by Means of Power Factor Decompositions," Energies, MDPI, vol. 16(10), pages 1-22, May.
    20. Zhengwei Qu & Jingchuan Yang & Yansheng Lang & Yunjing Wang & Xiaoming Han & Xinyue Guo, 2022. "Earth-Mover-Distance-Based Detection of False Data Injection Attacks in Smart Grids," Energies, MDPI, vol. 15(5), pages 1-16, February.

    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:22:p:6054-:d:447619. 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.