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Node Type Distribution and Its Impacts on Performance of Power Grids

  • Fei Xue*
  • , Shaofeng Lu
  • , Ettore Bompard
  • , Ciwei Gao
  • , Lin Jiang
  • , Xiaoliang Wang
  • *Corresponding author for this work
    • Polytechnic University of Turin
    • Southeast University, Nanjing
    • University of Liverpool
    • Xi'an Jiaotong-Liverpool University

    Research output: Contribution to journal › Article › peer-review

    6 Citations (Scopus)

    Abstract

    The theory of complex networks has been studied extensively since its inception. However, until now, the impact of the node-type distributions is related to network topology and cannot be evaluated independently. In this paper, a network structure is modeled via an adjacency matrix (network topology) and a set of node type distribution vectors. Three specific issues that need to be considered for node type distributions in smart grid testing and planning are summarized in this paper. First, a set of metrics are proposed and defined to evaluate the impact of node-type distributions on network performance independently. Second, another metric named the generation distribution factor is proposed to evaluate the distribution of generation buses resulting from the specific function and purpose of power grids and by considering the distribution of load buses as given conditions. Third, another metric, i.e., the power supply redundancy metric based on entropy, is proposed to evaluate the inequality of load in power supply. Finally, a discrimination factor is defined to ensure the overall evaluation and comparison of different networks is made for this inequality. All proposed metrics can be applied to the IEEE-30, IEEE-118, IEEE-300 bus systems, as well as Italian power grid components. The simulation results indicate that the IEEE-118 system has the best node type distribution and minimum discrimination; the Italian system has the worst node-type distribution and most serious discrimination of load power supply.

    Original languageEnglish
    Article number6287639
    Pages (from-to)46480-46490
    Number of pages11
    JournalIEEE Access
    Volume7
    DOIs
    Publication statusPublished - 2019

    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

    Keywords

    • Complex network
    • network structure
    • node type distribution
    • power supply redundancy

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