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Integrated Approach for Network Observability and State Estimation in Active Distribution Grid

Author

Listed:
  • Basanta Raj Pokhrel

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

  • Birgitte Bak-Jensen

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

  • Jayakrishnan R. Pillai

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

Abstract

This paper presents a unique integrated approach to meter placement and state estimation to ensure the network observability of active distribution systems. It includes observability checking, minimum measurement utilization, network state estimation, and trade-off evaluation between the number of real measurements used and the accuracy of the estimated state. In network parameter estimation, observability assessment is a preliminary task. It is handled by data analysis and filtering followed by calculation of the triangular factors of the singular, symmetric gain matrix using an algebraic method. Usually, to cover the deficiency of essential real measurements in distribution systems, huge numbers of virtual measurements are used. These pseudo measurements are calculated values, which are based on the network parameters, real measurements, and forecasted load/generation. Due to the application of a huge number of pseudo-measurements, large margins of error exists in the calculation phase. Therefore, there is still a high possibility of having large errors in estimated states, even though the network is classified as being observable. Hence, an integrated approach supported by forecasting is introduced in this work to overcome this critical issue. Finally, estimation of the trade-off in accuracy with respect to the number of real measurements used has been evaluated in order to justify the method’s practical application. The proposed method is applied to a Danish network, and the results are discussed.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2230-:d:239027
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    Citations

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    Cited by:

    1. 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.
    2. Sepideh Radhoush & Maryam Bahramipanah & Hashem Nehrir & Zagros Shahooei, 2022. "A Review on State Estimation Techniques in Active Distribution Networks: Existing Practices and Their Challenges," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

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