bibentry(
  bibtype  = "Manual",
  title    = "aemo: Download Australian Energy Market Operator Data",
  author   = person("Charles", "Coverdale"),
  year     = format(Sys.Date(), "%Y"),
  note     = sprintf("R package version %s", meta$Version),
  url      = "https://cran.r-project.org/package=aemo",
  textVersion = sprintf(
    "Coverdale, C. (%s). aemo: Download Australian Energy Market Operator Data. R package version %s. https://cran.r-project.org/package=aemo",
    format(Sys.Date(), "%Y"),
    meta$Version
  ),
  header   = "To cite the 'aemo' R package in publications:"
)

bibentry(
  bibtype  = "InProceedings",
  title    = "NEMOSIS -- NEM Open Source Information Service: open-source access to Australian National Electricity Market Data",
  author   = c(person("Nicholas", "Gorman"),
               person("Naser", "Haghdadi"),
               person("Anna", "Bruce"),
               person("Iain", "MacGill")),
  booktitle = "Asia-Pacific Solar Research Conference",
  year     = "2018",
  address  = "Sydney, Australia",
  url      = "https://www.ceem.unsw.edu.au/sites/default/files/documents/194_D-I_Gorman_N_2018.pdf",
  header   = "For the Python equivalent (NEMOSIS) and the data-model conventions this package follows, cite:"
)

bibentry(
  bibtype  = "Article",
  title    = "NEMSEER: A Python package for downloading and handling historical National Electricity Market forecast data produced by the Australian Energy Market Operator",
  author   = c(person("Abhijith", "Prakash"),
               person("Anna", "Bruce"),
               person("Iain", "MacGill")),
  journal  = "Journal of Open Source Software",
  volume   = "8",
  number   = "92",
  pages    = "5883",
  year     = "2023",
  doi      = "10.21105/joss.05883",
  header   = "For the forecast-vintage workflow that aemo_predispatch(run_datetime=) mirrors, cite:"
)
