Detection and Assessment of Partial Shading Scenarios on Photovoltaic Strings



Ma, Jieming, Pan, Xinyu, Man, Ka Lok, Li, Xingshuo ORCID: 0000-0002-1262-406X, Wen, Huiqing and Ting, Tiew On
(2018) Detection and Assessment of Partial Shading Scenarios on Photovoltaic Strings. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 54 (6). pp. 6279-6289.

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Abstract

There has been growing interest in using photovoltaic (PV) energy harvesting technology to reduce reliance on mineral-based energy. Partial shading scenarios (PSS) significantly affect the electrical characteristics of a PV generator. However, a few studies have devoted to the detection and assessment of the PSS. In this paper, shading rate and shading strength are used to characterize the PSS. A shading pattern detection algorithm is proposed to estimate the number of shaded modules in a PV string and distinguish the PSS from uniform irradiation scenarios. A multiple-output support vector regression is applied to estimate the shading strength. In addition, the maximum power point voltage of the applied PV generation system can be predicted from measured data. Simulation and experimental validation show the feasibility of the proposed method in the face of various environmental conditions. It could be used as a preliminary step toward automatic supervision and monitoring PV generation system.

Item Type: Article
Uncontrolled Keywords: Measurement, photovoltaic (PV) cells, partial shading conditions, partial shading detection, support vector regression (SVR)
Depositing User: Symplectic Admin
Date Deposited: 30 Jul 2018 09:50
Last Modified: 14 Mar 2024 17:51
DOI: 10.1109/TIA.2018.2848643
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3024288