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Thematic Series on Big Data Applications in Modern Power Systems

Guest Editor-in-chief: Canbing Li; Hui Liu;

This thematic series will focus on the latest development and research in

 1. Big data operation and management platform
 2. Customer usage patterns and demand side management
 3. Data-driven energy internet
 4. Data-based probabilistic prediction of equipment failures and defects
 5. Data-driven renewable energy forecasting
 6. Load forecasting with multiple time scales
 7. Predictive data-based asset management in electric utilities
 8. Risk assessment and management of power system operation

All papers and supplementary information (if any) should be submitted online and prepared according to PCMP guidelines. Authors should indicate that the paper is submitted for the thematic series in their cover letter and is not published or being considered to be published elsewhere. All submission will be subject to peer review before possible acceptance for publication in PCMP which is free of charge and highly accessed by readers from all over the world.

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Annual Journal Metrics

  • Speed
    98 days to first decision for reviewed manuscripts only
    90 days to first decision for all manuscripts
    163 days from submission to acceptance
    34 days from acceptance to publication

    Usage 
    100,617 downloads
    3 Altmetric mentions

The journal is indexed by

  • Emerging Sources Citation Index
  • SCOPUS
  • DOAJ
  • INIS Atomindex
  • Google Scholar
  • EBSCO Discovery Service
  • OCLC WorldCat Discovery Service
  • ProQuest-ExLibris Summon
  • ProQuest-ExLibris Primo
  • Institute of Scientific and Technical Information of China
  • Naver
  • Chinese Academy of Sciences (CAS) - GoOA
  • INSPEC
  • WTI Frankfurt eG
  • CNKI

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