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[期刊论文]

Multi-stage optimization placement of DPMUs based on node metric indices

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author:

Lin, Junjie (Lin, Junjie.) [1] | Chen, Haoyu (Chen, Haoyu.) [2] | Jiang, Changxu (Jiang, Changxu.) [3] | Unfold

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Abstract:

The proliferation of distributed energy resources and the introduction of new loads in distribution networks present significant challenges for monitoring and operation. To satisfy the enhanced observability and controllability requirements of modern distribution networks, there is an increasing demand for advanced monitoring devices. Distribution Network Phasor Measurement Units (DPMUs) offer high-precision measurement data with precise timestamps, thereby improving both the accuracy and redundancy of measurements within the distribution network.This paper introduces an optimization model for the strategic placement of PMUs within distribution networks, leveraging node metric indices. The indices considered are node degree, spatiotemporal correlation, and node power ratio. The relative importance of these indices is determined using an improved entropy weight method, which quantifies the differentiation of nodes within the network. This method facilitates the prioritized placement of DPMUs at critical nodes. The proposed model also incorporates constraints such as the depth of unobservability and zero injection nodes. Utilizing a 0–1 integer programming algorithm, the model derives a multi-stage optimal placement scheme for PMU placement. This scheme evolves from incomplete observability to critical observability and ultimately to full redundancy. Importantly, this approach allows for the monitoring of key nodes within the distribution network and enhances measurement redundancy without necessitating an increase in the number of placements. © 2024 Elsevier Ltd

Keyword:

Electric power distribution Energy resources Integer programming Observability Phasor measurement units Redundancy

Community:

  • [ 1 ] [Lin, Junjie]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 310108, China
  • [ 2 ] [Chen, Haoyu]Shandong Province Electric Power Company Economic Technology Research Institute, Jinan; 250021, China
  • [ 3 ] [Jiang, Changxu]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 310108, China
  • [ 4 ] [Han, Kunyu]State Grid Beijing City Power Supply Company, Beijing; 100035, China
  • [ 5 ] [Wei, Xinchi]State Grid Shanghai Electric Power Research Institute, Shanghai; 200437, China
  • [ 6 ] [Fang, Chen]State Grid Shanghai Electric Power Research Institute, Shanghai; 200437, China

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Source :

Sustainable Energy, Grids and Networks

Year: 2024

Volume: 39

Cited Count:

WoS CC Cited Count:

30 Days PV: 1

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