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Prof. Mohamed Ahmed Ebrahim Mohamed :: Publications:

Title:
Performance Assessment of AI-Based MPPT Techniques For Grid Connected Photovoltaic System
Authors: M. A. Ebrahim; H. A. AbdelHadi; H. M. Mahmoud; E. M. Saied; M. M. Salama
Year: 2016
Keywords: Photovoltaic; maximum power point tracking techniques; PI controller; particle swarm optimization
Journal: 4th International Conference on Renewable Energy: Generation and Applications, At BELFORT - FRANCE
Volume: 1
Issue: 1
Pages: 1-9
Publisher: UTBM
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

Integrating photovoltaic (PV) plants into electric power system exhibits challenges to power system dynamic performance. These challenges stem primarily from the natural characteristics of PV plants, which differ in some respects from the conventional plants. The most important challenge is how to extract and regulate the maximum power from sun. This paper presents optimal design for the most commonly used Maximum Power Point Tracking (MPPT) techniques based on Proportional Integral tuned by Particle Swarm Optimization (PI-PSO). These suggested techniques are, (1) the incremental conductance, (2) perturb and observe, (3) fractional short circuit current and (4) fractional open circuit voltage techniques. A comparative study with respect to the energy availability ratio from photovoltaic panels was performed. The simulation results have proved that the proposed controllers have an impressive tracking response. The system dynamic performance improved greatly using the proposed controllers.

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