Publications

NEM wind generation: Do birds of a feather flock together?

With a growing expectation that coal plants will face early retirement, this week’s ‘Chart of the week’ examines the correlation between different wind patterns in the various identified Renewable Energy Zones in the NEM.

Figure 1 illustrates the correlation between the FY2019 AEMO generated high wind renewable energy zones for the various zones (captured on a half hourly basis over FY 2019). The red colour indicates a high degree of correlation, white indicates no correlation while the degree of blue indicates negative correlation.

Ideally, there would be zones with significant negative correlation, meaning that if one particularly area was experiencing an extended wind drought, there would be a high probability of another area with good wind yields.

As would be expected, there is a tendency of high correlation within the individual states, where zones are closely located. The smallest state Tasmania has the highest degree of correlation between zones, averaging 0.59 between the three zones. South Australia falls closely behind, with correlation between the wind zones averaging 0.58, followed by Victoria with a value of 0.50 and Queensland with a value of 0.47 between the intra-regional zones. New South Wales has the most diverse intra-regional wind patterns with an average correlation of 0.38 between its zones.

There also exhibits a high degree of correlation between Victoria, South Australia, Tasmania and the southern New South Wales regions. This is largely as a result of the same weather systems driving across the Southern Ocean. This is potentially problematic for these regions with low insolation levels that are anticipated to be highly leveraged on wind generation, that may experience extended concurrent wind droughts. On a more positive note, two of the three REZs identified in the NSW Roadmap for development (New England and Central West Orana) show the least degree of correlation with the southern states.

Queensland is the region that which exhibits the least correlation in wind patterns with the rest of the NEM states and in some regions a small degree of negative correlation is observed. The strongest negative correlation value of -0.21 is observed between the Isaac region in Queensland and the Gippsland region in Victoria. This diversity of renewable resources is another important consideration along with adequate interconnection, long and short-term storage and curtailment as the NEM transitions into a low carbon grid.

For more insights and our view on the decarbonisation pricing through the energy transition, our ‘Benchmark power curve’ service provides granular price forecast for the future energy mix and market prices.