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An improved technique to estimate the total generated power by neighboring Photovoltaic Systems using single-point irradiance measurement and correlational models

Al-Hilfi, H.A.H., Shahnia, F.ORCID: 0000-0002-8434-0525 and Abu-Siada, A. (2020) An improved technique to estimate the total generated power by neighboring Photovoltaic Systems using single-point irradiance measurement and correlational models. IEEE Transactions on Industrial Informatics, 16 (6). pp. 3905-3917.

Link to Published Version: https://doi.org/10.1109/TII.2019.2941218
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Abstract

A major operational challenge of photovoltaic (PV) systems is the variability in their output power, which is mainly caused by the movements of clouds. This variability can be reduced through building several smaller PV systems, distributed within an area, rather than a single, large PV system, often referred to as the geographic smoothing. This smoothing can be expressed mathematically by the variability reduction index (VRI), which denotes the reduced level of variations in the output power of a group of neighboring PV systems. VRI considers the size of the PV systems, the distances between them, as well as the mathematical correlation model that reflects the timescale, along with the speed, direction, and density of the clouds passing over the PV systems. The VRI and solar irradiance, measured at one location, can be used to estimate the power generated by a group of neighboring PV systems. This article initially compares and assesses various VRI models through their application on a group of 16 small-scale neighboring rooftop PV systems, distributed over a square kilometer area in Brisbane, Australia. Then, a technique is proposed to improve the estimation accuracy of the overall generated power by a group of neighboring small-scale rooftop PV systems. This new technique is validated by comparing the estimated power with the measured power, generated by the investigated PV systems.

Item Type: Journal Article
Murdoch Affiliation: Engineering and Energy
Publisher: IEEE
Copyright: © 2020 IEEE
URI: http://researchrepository.murdoch.edu.au/id/eprint/55222
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