Andrew Gunn , Roger Dargaville, Christian Jakob, Shayne McGregor

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 AEMO 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.