On statistical power grid observability under communication constraints (invited paper)

Minglei You, Jing Jiang, Andrea M. Tonello, Tilemachos Doukoglou, Hongjian Sun

    Research output: Contribution to journalArticlepeer-review

    17 Citations (Scopus)
    36 Downloads (Pure)

    Abstract

    Phasor Measurement Units (PMUs) have enabled real-time power grid monitoring and control applications realizing an integrated power grid and communication system. The communication network formed by PMUs has strict latency requirements. If PMU measurements cannot reach the control centre within the latency bound, they will be invalid for calculation and may compromise the observability of the whole power grid as well as related applications. To address this issue, this study proposes a model to account for the power grid observability under communication constraints, where effective capacity is adopted to perform a cross-layer statistical analysis in the communication system. Based on this model, three algorithms are proposed for improving power grid observability, which are an observability redundancy algorithm, an observability sensitivity algorithm and an observability probability algorithm. These three algorithms aim at enhancing the power system observability via the optimal communication resource allocation for a given grid infrastructure. Case studies show that the proposed algorithms can improve the power system performance under constrained wireless communication resources.
    Original languageEnglish
    Pages (from-to)40-47
    JournalIET Smart Grid
    Volume1
    Issue number2
    Early online date3 Jul 2018
    DOIs
    Publication statusPublished - Jul 2018

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Fingerprint

    Dive into the research topics of 'On statistical power grid observability under communication constraints (invited paper)'. Together they form a unique fingerprint.

    Cite this