Analyzing the research subjects and hot topics of power system reliability through the Web of Science from 1991 to 2015

  • Jingjing Wang
  • , Xian Zhao*
  • , Xiaoxin Guo
  • , Bolong Li
  • *Corresponding author for this work

    Research output: Contribution to journalReview articlepeer-review

    40 Citations (Scopus)

    Abstract

    Electric energy is an important ingredient for the development of industrial and it also makes our lives comfortable. The electric energy from conventional generation system is mainly obtained by conversion from fossil fuels, nuclear and other non-renewable energy. In the last few decades, due to the environmental pollution and energy exhaustion, more and more researchers began to study the renewable energy (wind power, solar energy, biomass energy, etc.) generation system. However, the random features of the new energy generation system may cause system easily failure. Thus related researchers emphasize on the renewable generation system's reliability and stability problem. The aim of this paper is mainly to explore the research contents of major countries, institutions and authors in the power system reliability research based on the Web of Science dataset and related software. And this paper further studies the collaboration network and cooperative contents among them. In addition, using the analysis of the cited frequency is to find the highly influential countries, institutions and authors. Author keywords frequency analysis and co-occurrence analysis are applied to explore the current hot topics, and predict future development direction. This study provides a useful perspective for the related researchers to undertake power system reliability research in future.

    Original languageEnglish
    Pages (from-to)700-713
    Number of pages14
    JournalRenewable and Sustainable Energy Reviews
    Volume82
    DOIs
    Publication statusPublished - 2018

    Keywords

    • Citation analysis
    • Cooperative relationship
    • Keywords frequency analysis
    • Power system reliability
    • Productive analysis

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