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Application of State Estimation in Distribution Systems with Embedded Microgrids

Author

Listed:
  • Nikolaos M. Manousakis

    (Department of Electrical & Electronics Engineering, University of West Attica, 12244 Athens, Greece)

  • George N. Korres

    (School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Athens, Greece)

Abstract

In this paper, a weighted least square (WLS) state estimation algorithm with equality constraints is proposed for smart distribution networks embedded with microgrids. Since only a limited number of real-time measurements are available at the primary or secondary substations and distributed generation sites, load estimates at unmeasured buses remote from the substations are needed to execute state estimation. The load information can be obtained by forecasted and historical data or smart real-time meters. The proposed algorithms can be applied in either grid-connected or islanded operation mode and can efficiently identify breaker status errors at the main substations and feeders, where sufficient measurement redundancy exists. The impact of the accuracy of real and pseudo-measurements on the estimated bus voltages is tested with a 55-bus distribution network including distributed generation.

Suggested Citation

  • Nikolaos M. Manousakis & George N. Korres, 2021. "Application of State Estimation in Distribution Systems with Embedded Microgrids," Energies, MDPI, vol. 14(23), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:7933-:d:688512
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    References listed on IDEAS

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    1. Depuru, Soma Shekara Sreenadh Reddy & Wang, Lingfeng & Devabhaktuni, Vijay, 2011. "Smart meters for power grid: Challenges, issues, advantages and status," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2736-2742, August.
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    Cited by:

    1. Nikolaos M. Manousakis, 2022. "Advanced Electrical Measurements Technologies," Energies, MDPI, vol. 15(9), pages 1-6, April.
    2. Luis Vargas & Henrry Moyano, 2023. "A Novel Multi-Area Distribution State Estimation Approach with Nodal Redundancy," Energies, MDPI, vol. 16(10), pages 1-19, May.

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