A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Spatial optimality and temporal variability in Australia’s wind resource
To meet electricity demand using renewable energy supply, wind farm locations should be chosen to minimise variability in output, especially at night when solar photovoltaics cannot be relied upon. Wind farm location must balance grid-proximity, resource potential, and wind correlation between farms. A top-down planning approach for farm locations can mitigate demand unmet by wind supply, yet the present Australian wind energy market has bottom-up short-term planning. Here we show a computationally tractable method for optimising farm locations to maximise total supply. We find that Australia’s currently operational and planned wind farms produce less power with more variability than a hypothetical optimal set of farms with equivalent capacity within 100 km of the Australian Energy Market Operator grid. Regardless of the superior output, this hypothetical set is still subject to variability due to large-scale weather correlated with climate modes (i.e. El Niño). We study multiple scenarios and highlight several internationally transferable planning implications.
Spatial optimality and temporal variability in Australia’s wind resource
To meet electricity demand using renewable energy supply, wind farm locations should be chosen to minimise variability in output, especially at night when solar photovoltaics cannot be relied upon. Wind farm location must balance grid-proximity, resource potential, and wind correlation between farms. A top-down planning approach for farm locations can mitigate demand unmet by wind supply, yet the present Australian wind energy market has bottom-up short-term planning. Here we show a computationally tractable method for optimising farm locations to maximise total supply. We find that Australia’s currently operational and planned wind farms produce less power with more variability than a hypothetical optimal set of farms with equivalent capacity within 100 km of the Australian Energy Market Operator grid. Regardless of the superior output, this hypothetical set is still subject to variability due to large-scale weather correlated with climate modes (i.e. El Niño). We study multiple scenarios and highlight several internationally transferable planning implications.
Spatial optimality and temporal variability in Australia’s wind resource
Andrew Gunn (author) / Roger Dargaville (author) / Christian Jakob (author) / Shayne McGregor (author)
2023
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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