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Optimal placement of PMUs and communication links for distributed state estimation in distribution networks

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  • Zhao, Zhida
  • Yu, Hao
  • Li, Peng
  • Li, Peng
  • Kong, Xiangyu
  • Wu, Jianzhong
  • Wang, Chengshan

Abstract

With the expansion in scale and complexity of distribution networks, distributed state estimation (DSE), a real-time database for other on-line applications, is becoming popular for large-scale active distribution networks (ADN). Measurements from phasor measurement units (PMUs) with the same time stamp can assist DSE to obtain faster and more accurate estimation; however, the configuration of PMUs and communication links should be updated to support data collection and transmission. This paper proposes an optimal PMUs and communication links placement method for DSE in distribution networks. A network partitioning method is presented with the aim of balancing calculation times among subareas. Then, a binary integer linear programming model that simultaneously considers the optimal placement of PMUs, phasor data concentrators (PDCs) and communication links is proposed. The economy of the configuration scheme is guaranteed on the premise that the network is fully observable. Finally, case studies on the IEEE 33-node, PG&E 69-node and IEEE 123-node systems verify the feasibility of the proposed method.

Suggested Citation

  • Zhao, Zhida & Yu, Hao & Li, Peng & Li, Peng & Kong, Xiangyu & Wu, Jianzhong & Wang, Chengshan, 2019. "Optimal placement of PMUs and communication links for distributed state estimation in distribution networks," Applied Energy, Elsevier, vol. 256(C).
  • Handle: RePEc:eee:appene:v:256:y:2019:i:c:s0306261919316502
    DOI: 10.1016/j.apenergy.2019.113963
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    Cited by:

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    2. Ghadikolaee, Ebad Talebi & Kazemi, Ahad & Shayanfar, Heydar Ali, 2020. "Novel multi-objective phasor measurement unit placement for improved parallel state estimation in distribution network," Applied Energy, Elsevier, vol. 279(C).
    3. Song, Shaojian & Xiong, Hao & Lin, Yuzhang & Huang, Manyun & Wei, Zhinong & Fang, Zhi, 2022. "Robust three-phase state estimation for PV-Integrated unbalanced distribution systems," Applied Energy, Elsevier, vol. 322(C).
    4. 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.
    5. Dey, Maitreyee & Rana, Soumya Prakash & Simmons, Clarke V. & Dudley, Sandra, 2021. "Solar farm voltage anomaly detection using high-resolution μPMU data-driven unsupervised machine learning," Applied Energy, Elsevier, vol. 303(C).

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