A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions

Under partial shading conditions (PSCs), photovoltaic (PV) system characteristics vary and may have multiple power peaks. Conventional maximum power point tracking (MPPT) methods are unable to track the global peak. In addition, it takes a considerable time to reach the maximum power point (MPP). To...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.38481-38492
Main Authors: Joisher, Mansi, Singh, Dharampal, Taheri, Shamsodin, Espinoza-Trejo, Diego R., Pouresmaeil, Edris, Taheri, Hamed
Format: Article
Language:English
Subjects:
Algorithms
Convergence
Converters
differential evaluation
Maximum power point trackers
maximum power point tracking
Maximum power tracking
Microcontrollers
Optimization
partial shading condition
Particle swarm optimization
Performance evaluation
Photovoltaic cells
Photovoltaic systems
Shading
Sociology
Statistics
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Summary:Under partial shading conditions (PSCs), photovoltaic (PV) system characteristics vary and may have multiple power peaks. Conventional maximum power point tracking (MPPT) methods are unable to track the global peak. In addition, it takes a considerable time to reach the maximum power point (MPP). To address these issues, this paper proposes an improved hybrid MPPT method using the conventional evolutional algorithms, i.e., Particle Swarm Optimization (PSO) and Differential Evaluation (DE). The main feature of the proposed hybrid MPPT method is the advantage of one method compensates for shortcomings of the other method. Furthermore, the algorithm is simple and rapid. It can be easily implemented on a low-cost microcontroller. To evaluate the performance of the proposed method, MATLAB simulations are carried out under different PSCc. Experimental verifications are conducted using a boost converter setup, an ET-M53695 panel and a TMS320F28335 DSP. Finally, the simulation and hardware results are compared to those from the PSO and DE methods. The superiority of the hybrid method over PSO and DE methods is highlighted through the results.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2975742