A Scalable PDC Placement Technique for Fast and Resilient Monitoring of Large Power Grids

Md Zahidul Islam, Shamsun N. Edib, Vinod M. Vokkarane, Yuzhang Lin, Xiaoyuan Fan

Research output: Contribution to journalArticlepeer-review


The Wide Area Measurement System (WAMS) is a key enabler of real-time monitoring of power grids. The essential goals of WAMS design are fast and resilient data transfer from phasor measurement units (PMU) to phasor data concentrators (PDC). We propose a scalable two-stage PDC placement technique for minimizing the end-to-end delay while maintaining resiliency. In the prescreening stage, the plausible candidates of PDC configurations are identified based on a graph theory-based multi-median function (MMF). A computationally efficient meta-heuristic algorithm is used to address scalability. In the candidate selection stage, two different algorithms, namely Suurballe's and Dijkstra's, are employed to identify the best of those plausible PDC configurations as the final design. This technique not only minimizes the hop paths between PMUs and PDCs, but also ensures network resiliency against single PMU, PDC, or communication link failure by incorporating the roles of PMUs in power grid observability into routing policy. Simulation results on the IEEE 57-bus test power system and the 2000-bus test power system demonstrate the effectiveness and scalability of the proposed technique.

Original languageEnglish (US)
Pages (from-to)1-12
Number of pages12
JournalIEEE Transactions on Control of Network Systems
StateAccepted/In press - 2023


  • communication network
  • Observability
  • Phasor Data Concentrator (PDC)
  • Phasor Measurement Unit (PMU)
  • Phasor measurement units
  • power grid monitoring
  • Power grids
  • Power measurement
  • Resilience
  • resiliency
  • smart grid
  • State estimation
  • Wide Area Management System (WAMS)
  • Wide area measurements

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications
  • Control and Optimization


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