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International Journal of Photoenergy
Volume 2015 (2015), Article ID 424628, 10 pages
Research Article

An Ultrafast Maximum Power Point Setting Scheme for Photovoltaic Arrays Using Model Parameter Identification

Qatar Environment and Energy Research Institute (QEERI), Member of Qatar Foundation, P.O. Box 5825, Doha, Qatar

Received 3 December 2014; Revised 1 March 2015; Accepted 24 March 2015

Academic Editor: Francisco A. S. Neves

Copyright © 2015 Zhaohui Cen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Maximum power point tracking (MPPT) for photovoltaic (PV) arrays is essential to optimize conversion efficiency under variable and nonuniform irradiance conditions. Unfortunately, conventional MPPT algorithms such as perturb and observe (P&O), incremental conductance, and current sweep method need to iterate command current or voltage and frequently operate power converters with associated losses. Under partial overcast conditions, tracking the real MPP in multipeak P-I or P-V curve model becomes highly challenging, with associated increase in search time and converter operation, leading to unnecessary power being lost in the MPP tracking process. In this paper, the noted drawbacks in MPPT-controlled converters are addressed. In order to separate the search algorithms from converter operation, a model parameter identification approach is presented to estimate insolation conditions of each PV panel and build a real-time overall P-I curve of PV arrays. Subsequently a simple but effective global MPPT algorithm is proposed to track the MPP in the overall P-I curve obtained from the identified PV array model, ensuring that the converter works at the MPP. The novel MPPT is ultrafast, resulting in conserved power in the tracking process. Finally, simulations in different scenarios are executed to validate the novel scheme’s effectiveness and advantages.