Abstract
Maintaining optimal power in changing environments presents a significant challenge for photovoltaic (PV) systems. This paper introduces a novel Vcp-decomposition-based adaptive strategy (VD-AS) aimed at enhancing optimal power extraction in varying environmental conditions. Distinct from the conventional maximum power point tracking (MPPT) technologies, the proposed VD-AS method estimates the peak pattern based on the voltage at the current peak on the power-voltage curve. Utilizing the peak pattern information, a sim-to-real peak identification model is capable of predicting the global maximum power point (GMPP) locus. It not only enables an accurate adaptive search for the GMPP locus but also substantially minimizes the need for unnecessary global searches when the peak pattern is consistent. Experimental results from a laboratory prototype demonstrate that the proposed method can accurately track the GMPP with a smaller voltage search range and shorter tracking time. Its tracking efficiency is generally 10% higher than that of state-of-the-art GMPP tracking methods.
Original language | English |
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Pages (from-to) | 1-9 |
Number of pages | 9 |
Journal | IEEE Transactions on Power Electronics |
Volume | 39 |
Issue number | 10 |
DOIs | |
Publication status | Accepted/In press - 4 Jul 2024 |
Externally published | Yes |
Keywords
- Adaptation models
- Current measurement
- maximum power point tracking
- optimal control
- Optimization
- Photovoltaic power systems
- Photovoltaic systems
- Tracking
- Turning
- Voltage