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Applied Energy
Article . 2018 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Applied Energy
Article
License: CC BY NC ND
Data sources: UnpayWall
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Geographic information system algorithms to locate prospective sites for pumped hydro energy storage

Authors: Bin Lu; Matthew Stocks; Andrew Blakers; Kirsten Anderson;

Geographic information system algorithms to locate prospective sites for pumped hydro energy storage

Abstract

Abstract Pumped hydro energy storage is capable of large-scale energy time shifting and a range of ancillary services, which can facilitate high levels of photovoltaics and wind integration in electricity grids. This study aims to develop a series of advanced Geographic Information System algorithms to locate prospective sites for off-river pumped hydro across a large land area such as a state or a country. Two typical types of sites, dry-gully and turkey’s nest, are modelled and a sequence of Geographic Information System-based procedures are developed for an automated site search. A case study is conducted for South Australia, where 168 dry-gully sites and 22 turkey’s nest sites have been identified with a total water storage capacity of 441 gigalitres, equivalent to 276 gigawatt-hours of energy storage. This demonstrates the site searching algorithms can work efficiently in the identification of off-river pumped hydro sites, allowing high-resolution assessments of pumped hydro energy storage to be quickly conducted on a broad scale. The sensitivity analysis shows the significant influences of maximum dam wall heights on the number of sites and the total storage capacity. It is noted that the novel models developed in this study are also applicable to the deployments of other types of pumped hydro such as the locations of dry-gully and turkey’s nest sites adjacent to existing water bodies, old mining pits and oceans.

Country
Australia
Related Organizations
Keywords

Energy storage, Pumped hydro, Geographic information system

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
98
Top 1%
Top 10%
Top 1%
Green
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