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Spatio-temporal characterisation of extended low direct normal irradiance events over Australia using satellite derived solar radiation data

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  • Elliston, Ben
  • MacGill, Iain
  • Prasad, Abhnil
  • Kay, Merlinde

Abstract

As part of an on-going program to develop technological scenarios for 100 per cent renewable generation within the Australian National Electricity Market (NEM), we explore the degree to which concentrating solar thermal (CST) power might reliably contribute to the generation mix. We analyse satellite-derived hourly direct normal irradiance data provided by the Australian Bureau of Meteorology for Australia over a 13-year period. This large data set covers sufficient time to enable us to characterise the frequency and duration of rare events such as extended periods of heavy cloud cover and hence low solar insolation over regions of Australia. The results highlight those regions with both the highest and lowest occurrence of extended periods of low DNI. They also identify regions whose correlated climatic characteristics would reduce overall CST generation variability if the plants were distributed across them. As such, the findings may assist both project developers, and long-term system planning for reserve generation capacity in future high renewable generation mixes.

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  • Elliston, Ben & MacGill, Iain & Prasad, Abhnil & Kay, Merlinde, 2015. "Spatio-temporal characterisation of extended low direct normal irradiance events over Australia using satellite derived solar radiation data," Renewable Energy, Elsevier, vol. 74(C), pages 633-639.
    • Handle: RePEc:eee:renene:v:74:y:2015:i:c:p:633-639
    DOI: 10.1016/j.renene.2014.08.067
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    References listed on IDEAS

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    1. Zhang, Yabei & Smith, Steven J. & Kyle, G. Page & Stackhouse Jr., Paul W., 2010. "Modeling the potential for thermal concentrating solar power technologies," Energy Policy, Elsevier, vol. 38(12), pages 7884-7897, December.
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    Cited by:

    1. Salcedo-Sanz, Sancho & Deo, Ravinesh C. & Cornejo-Bueno, Laura & Camacho-Gómez, Carlos & Ghimire, Sujan, 2018. "An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia," Applied Energy, Elsevier, vol. 209(C), pages 79-94.
    2. Dasari, Hari Prasad & Desamsetti, Srinivas & Langodan, Sabique & Attada, Raju & Kunchala, Ravi Kumar & Viswanadhapalli, Yesubabu & Knio, Omar & Hoteit, Ibrahim, 2019. "High-resolution assessment of solar energy resources over the Arabian Peninsula," Applied Energy, Elsevier, vol. 248(C), pages 354-371.
    3. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2017. "Assessment of solar and wind resource synergy in Australia," Applied Energy, Elsevier, vol. 190(C), pages 354-367.
    4. Prasad, Abhnil Amtesh & Yang, Yuqing & Kay, Merlinde & Menictas, Chris & Bremner, Stephen, 2021. "Synergy of solar photovoltaics-wind-battery systems in Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    5. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2015. "Assessment of direct normal irradiance and cloud connections using satellite data over Australia," Applied Energy, Elsevier, vol. 143(C), pages 301-311.
    6. Mohammadi, Kasra & Goudarzi, Navid, 2018. "Association of direct normal irradiance with El Niño Southern Oscillation and its consequence on concentrated solar power production in the US Southwest," Applied Energy, Elsevier, vol. 212(C), pages 1126-1137.

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