Revisit Optimal PMU Placement With Full Zero-Injection Cluster and Redundancy Sharing

Due to the expensive deployment cost, finding the minimum Phasor Measurement Unit (PMU) to meet the observability requirement has been attractive since the invention of PMU. Many research efforts have been put to zero-injection nodes (ZINs) in optimal PMU placement (OPP). We revisit OPP and define a full Zero-injection cluster (ZIC) as a set of nodes adjacent to ZINs together with at least one ZIN, establishing a novel ZIC-based OPP model. Compared with the existing literature, the full ZIC can cover more nodes, resulting in a better solution. To find all full ZIC, we propose a dynamic adjacency matrix based full-ZIC search algorithm, which has quadratic-time complexity. It could have wide applications, and can be applied in many OPP works. Besides, redundant PMUs within the full ZIC can be shared within large areas post contingency. A concept of redundancy sharing is proposed for post-contingency ZIC model, whose observability can be guaranteed with proposed redundancy-sharing conditions. Comprehensive case studies are conducted using the proposed approaches. The simulation results for both IEEE cases and a real-world system show the proposed method can further reduce PMU deployment number.

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Publication Details

Journal
IEEE Transactions on Power Systems
Published
2024-09-03
DOI
https://doi.org/10.1109/tpwrs.2024.3453300
Citations
7
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
1.73
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article

Revisit Optimal PMU Placement With Full Zero-Injection Cluster and Redundancy Sharing

Yinyin Ge, Lei Wu, Hongxing Ye, Chuyue Tian
7 citations
IEEE Transactions on Power Systems
Brain Tumor Detection and Classification
1.73
article

Revisit Optimal PMU Placement With Full Zero-Injection Cluster and Redundancy Sharing

Yinyin Ge, Lei Wu, Hongxing Ye, Chuyue Tian
article en
7 citations

Abstract

Due to the expensive deployment cost, finding the minimum Phasor Measurement Unit (PMU) to meet the observability requirement has been attractive since the invention of PMU. Many research efforts have been put to zero-injection nodes (ZINs) in optimal PMU placement (OPP). We revisit OPP and define a full Zero-injection cluster (ZIC) as a set of nodes adjacent to ZINs together with at least one ZIN, establishing a novel ZIC-based OPP model. Compared with the existing literature, the full ZIC can cover more nodes, resulting in a better solution. To find all full ZIC, we propose a dynamic adjacency matrix based full-ZIC search algorithm, which has quadratic-time complexity. It could have wide applications, and can be applied in many OPP works. Besides, redundant PMUs within the full ZIC can be shared within large areas post contingency. A concept of redundancy sharing is proposed for post-contingency ZIC model, whose observability can be guaranteed with proposed redundancy-sharing conditions. Comprehensive case studies are conducted using the proposed approaches. The simulation results for both IEEE cases and a real-world system show the proposed method can further reduce PMU deployment number.

IEEE Transactions on Power SystemsVol. 40(3)
Stevens Institute of Technology (US), China XD Group (China) (CN), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 15%
Brain Tumor Detection and Classification
1.73
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Revisit Optimal PMU Placement With Full Zero-Injection Cluster and Redundancy Sharing — Yinyin Ge, Lei Wu, et al. · IEEE Transactions on Power Systems (2024) | TGRS Research Map | TGRS