File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Open grid model of Australia’s National Electricity Market allowing backtesting against historic data

TitleOpen grid model of Australia’s National Electricity Market allowing backtesting against historic data
Authors
KeywordsWind power
Electricity
Power producers
Issue Date2018
PublisherNature Research (part of Springer Nature): Fully open access journals. The Journal's web site is located at http://www.nature.com/sdata/
Citation
Scientific Data, 2018, v. 5, p. article no. 180203 How to Cite?
AbstractRising electricity prices, concerns regarding system security, and emissions reduction are central to an energy policy debate under way in Australia. To better evaluate mechanisms that seek to address the nexus of engineering, economic, and environmental challenges facing the country’s electricity system, we have constructed network and generator datasets describing the operation of Australia’s largest transmission network. These data have been collated using open-source software, and are available under an open license. They include the geospatial locations of network elements, and have been designed to interface with a public database maintained by the Australian Energy Market Operator. This interface allows historic data, such as generator dispatch and regional load signals, to be integrated with market models. Interactive network maps, independent datasets, and power-flow models have been used to assess the completeness and functionality of the derived datasets. In the context of Australia, these data can be used to examine geospatial and temporal impacts of power injections from renewables. More generally, they allow market models to be benchmarked against realised outcomes.
Persistent Identifierhttp://hdl.handle.net/10722/279144
ISSN
2021 Impact Factor: 8.501
2020 SCImago Journal Rankings: 2.565
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXenophon, A-
dc.contributor.authorHill, D-
dc.date.accessioned2019-10-21T02:20:22Z-
dc.date.available2019-10-21T02:20:22Z-
dc.date.issued2018-
dc.identifier.citationScientific Data, 2018, v. 5, p. article no. 180203-
dc.identifier.issn2052-4463-
dc.identifier.urihttp://hdl.handle.net/10722/279144-
dc.description.abstractRising electricity prices, concerns regarding system security, and emissions reduction are central to an energy policy debate under way in Australia. To better evaluate mechanisms that seek to address the nexus of engineering, economic, and environmental challenges facing the country’s electricity system, we have constructed network and generator datasets describing the operation of Australia’s largest transmission network. These data have been collated using open-source software, and are available under an open license. They include the geospatial locations of network elements, and have been designed to interface with a public database maintained by the Australian Energy Market Operator. This interface allows historic data, such as generator dispatch and regional load signals, to be integrated with market models. Interactive network maps, independent datasets, and power-flow models have been used to assess the completeness and functionality of the derived datasets. In the context of Australia, these data can be used to examine geospatial and temporal impacts of power injections from renewables. More generally, they allow market models to be benchmarked against realised outcomes.-
dc.languageeng-
dc.publisherNature Research (part of Springer Nature): Fully open access journals. The Journal's web site is located at http://www.nature.com/sdata/-
dc.relation.ispartofScientific Data-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectWind power-
dc.subjectElectricity-
dc.subjectPower producers-
dc.titleOpen grid model of Australia’s National Electricity Market allowing backtesting against historic data-
dc.typeArticle-
dc.identifier.emailHill, D: dhill@eee.hku.hk-
dc.identifier.authorityHill, D=rp01669-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1038/sdata.2018.203-
dc.identifier.pmid30351307-
dc.identifier.pmcidPMC6206589-
dc.identifier.scopuseid_2-s2.0-85055182438-
dc.identifier.hkuros307211-
dc.identifier.volume5-
dc.identifier.spagearticle no. 180203-
dc.identifier.epagearticle no. 180203-
dc.identifier.isiWOS:000448054500001-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl2052-4463-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats