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.
| Original language | English |
|---|---|
| Article number | 8387864 |
| Pages (from-to) | 6279-6289 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Industry Applications |
| Volume | 54 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1 Nov 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Measurement
- partial shading conditions
- partial shading detection
- photovoltaic (PV) cells
- support vector regression (SVR)
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