Electrical LeaderRank Method for Node Importance Evaluation of Power Grids Considering uncertainties of Renewable Energy

  • Bin Zhou
  • , Yifei Lei
  • , Canbing Li
  • , Baling Fang*
  • , Qiuwei Wu
  • , Lijuan Li
  • , Zhenqiu Li
  • *Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

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    Abstract

    Node importance evaluation of power grids plays an important role in the safe operation and planning of power systems. This paper proposes an electrical LeaderRank (ELR) method to identify the important nodes in complex power grids, considering the renewable energy uncertainties, system topological structure, transmission power flow and the loss of loads caused by cascading failures. The proposed method uses an ELR value function to represent the importance of a system node, which can be derived iteratively from the weighted distribution strategy of its in-linked nodes. Furthermore, the uncertainties of wind and solar energy generation are modelled as interval numbers, and the interval power flow calculation is employed to obtain the interval power in transmission lines, direct adjacent matrix, and finally the interval ELR values. The performance of ELR method has been fully tested and benchmarked on the IEEE 118-bus power system and the Western Liaoning Power Grid of China. Comparative results on four performance criteria have not only demonstrated the validity and superiority of the proposed method, but also confirmed its capability to cope with the node importance evaluation of practical power grids.
    Original languageEnglish
    JournalInternational Journal of Electrical Power & Energy Systems
    Volume106
    Pages (from-to)45-55
    ISSN0142-0615
    DOIs
    Publication statusPublished - 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

    Keywords

    • Cascading failures
    • Complex network
    • Photovoltaics
    • Wind energy
    • Vulnerability

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