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Enhancing the estimation of the overall produced power by several adjacent photovoltaic systems using existing correlational factors

Al-Hilfi, H.A.H., Shahnia, F. and Abu-Siada, A. (2018) Enhancing the estimation of the overall produced power by several adjacent photovoltaic systems using existing correlational factors. In: IEEE 27th International Symposium on Industrial Electronics (ISIE) 2018, 13-15 June 2018, Cairns, QLD

Link to Published Version: https://doi.org/10.1109/ISIE.2018.8433850
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Abstract

Cloud movements lead to the variability of the produced power by a photovoltaic (PV) system. However, the overall variability of the power produced by several adjacent PVs, distributed in any locality, reduces with respect to that area's size. This is referred to as the variability reduction index (VRI) and can be used to estimate the overall produced power by several adjacent PVs as it considers correlation models that represent the timescale and the distances between the PVs, the speed, direction and density of the clouds as well as the PV size. This paper compares different VRI models and proposes an enhanced technique which has a better estimation accuracy. The performance of the developed technique is validated by comparing the estimated power with the actual power for 16 adjacent small-scale rooftop PVs distributed over a kilometer square area in Brisbane, Australia.

Publication Type: Conference Paper
Murdoch Affiliation: School of Engineering and Information Technology
URI: http://researchrepository.murdoch.edu.au/id/eprint/41890
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