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    Enhancing the Estimation of the Overall Produced Power by Several Adjacent Photovoltaic Systems Using Existing Correlational Factors

    Access Status
    Fulltext not available
    Authors
    Al-Hilfi, H.
    Shahnia, F.
    Abu-Siada, Ahmed
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Al-Hilfi, H. and Shahnia, F. and Abu-Siada, A. 2018. Enhancing the Estimation of the Overall Produced Power by Several Adjacent Photovoltaic Systems Using Existing Correlational Factors, pp. 43-47.
    Source Title
    IEEE International Symposium on Industrial Electronics
    DOI
    10.1109/ISIE.2018.8433850
    ISBN
    9781538637050
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/72101
    Collection
    • Curtin Research Publications
    Abstract

    © 2018 IEEE. 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.

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