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Optimising the deployment of renewable resources for the Australian NEM (National Electricity Market) and the effect of atmospheric length scales

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  • Huva, Robert
  • Dargaville, Roger
  • Rayner, Peter

Abstract

This study sheds new light on the variability of wind power across the Australian NEM (National Electricity Market) and in doing so gives an insight on the potential network configuration for a high RE (Renewable Electricity) future. We present idealised cost-minimised simulations for the NEM utilising onshore wind, large-scale solar, pumped hydro and OCGT (open cycle gas turbines) technologies. A model using gridded meteorological data from the regional ACCESS-R (Australian Community Climate and Earth-System Simulator) simulates wind and solar technology output along with generation from OCGT to meet demand in the NEM for the period 2010–2011. A cost for connecting each location to the nearest major load centre is introduced and a base scenario created from an initial connection cost of $1 M/km. A sensitivity study reveals that a cost of $8 M/km results in the contraction of all renewable resources to four major wind installations. Compared to the base scenario the four major wind locations share much of the variability in renewable energy output, demonstrating that the NEM region has four distinct wind regimes. Separated by 1,400 km these four wind installations provide an optimisation-based decorrelation length for the NEM. This information is particularly useful for long-term planners of large-scale energy infrastructure.

Suggested Citation

  • Huva, Robert & Dargaville, Roger & Rayner, Peter, 2016. "Optimising the deployment of renewable resources for the Australian NEM (National Electricity Market) and the effect of atmospheric length scales," Energy, Elsevier, vol. 96(C), pages 468-473.
    • Handle: RePEc:eee:energy:v:96:y:2016:i:c:p:468-473
    DOI: 10.1016/j.energy.2015.12.082
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    References listed on IDEAS

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    1. Elliston, Ben & Diesendorf, Mark & MacGill, Iain, 2012. "Simulations of scenarios with 100% renewable electricity in the Australian National Electricity Market," Energy Policy, Elsevier, vol. 45(C), pages 606-613.
    2. Huva, Robert & Dargaville, Roger & Caine, Simon, 2012. "Prototype large-scale renewable energy system optimisation for Victoria, Australia," Energy, Elsevier, vol. 41(1), pages 326-334.
    3. Elliston, Ben & MacGill, Iain & Diesendorf, Mark, 2013. "Least cost 100% renewable electricity scenarios in the Australian National Electricity Market," Energy Policy, Elsevier, vol. 59(C), pages 270-282.
    4. Humpert, Christof, 2012. "Long distance transmission systems for the future electricity supply – Analysis of possibilities and restrictions," Energy, Elsevier, vol. 48(1), pages 278-283.
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    Cited by:

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    2. Graham Palmer & Joshua Floyd, 2017. "An Exploration of Divergence in EPBT and EROI for Solar Photovoltaics," Biophysical Economics and Resource Quality, Springer, vol. 2(4), pages 1-20, December.
    3. Deason, Wesley, 2018. "Comparison of 100% renewable energy system scenarios with a focus on flexibility and cost," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3168-3178.

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