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MATHEMATICAL TOOLS FOR MAXIMISING RENEWABLE ENERGY USE IN ELECTRICITY SUPPLY

Part of: General and miscellaneous specific topics

Published online by Cambridge University Press:  04 December 2017

ADRIAN GRANTHAM
ADRIAN GRANTHAM*
Affiliation:
School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia 5095, Australia email [email protected]
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Abstract

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Keywords

renewable energysolarprobabilistic forecastingstoragesynthetic

MSC classification

Primary: 00A69: General applied mathematics
Type
Abstracts of Australasian PhD Theses
Information
Bulletin of the Australian Mathematical Society , Volume 97 , Issue 1 , February 2018 , pp. 163 - 165
Copyright
© 2017 Australian Mathematical Publishing Association Inc. 

References

Boland, J., Boulaire, F., Grantham, A. and White, C., ‘Optimisation of photovoltaic system and storage’, ANZIAM J. 58 (2017), 1–32.Google Scholar
Grantham, A., Gel, Y. R. and Boland, J., ‘Nonparametric short-term probabilistic forecasting for solar radiation’, Solar Energy 133 (2016), 465–475.Google Scholar
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Whaley, D., Pudney, P., Grantham, A. and Saman, W., ‘Performance of a cluster of low-energy housing rooftop PV systems: theoretical vs actual output’, in: Proc. 52nd Annual Conf. (Australian Solar Energy Society, Melbourne, 2014), 63–72.Google Scholar