Journal
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
Volume 54, Issue 6, Pages 6279-6289Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIA.2018.2848643
Keywords
Measurement; photovoltaic (PV) cells; partial shading conditions; partial shading detection; support vector regression (SVR)
Funding
- National Natural Science Foundation of China [61702353]
- Natural Science Foundation of Jiangsu Province [BK20160355]
- Science and Technology Project of Ministry of Housing and Urban-Rural Development [2016-K1-019]
- XJTLU Key Program Special Fund [KSF-P-02]
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There has been growing interest in using photovoltaic (PV) energy harvesting technology to reduce reliance on mineralbased 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 multipleoutput 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.
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