Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/9604
Title: MPPT-based artificial intelligence techniques for photovoltaic systems and its implementation into field programmable gate array chips: Review of current status and future perspectives
Authors: Mellit, Adel 
Kalogirou, Soteris A. 
Keywords: Artificial intelligence
Field programmable gate arrays chip
Implementation
Maximum power point tracking
Photovoltaic systems
Programmable logic devices
Real-time applications
Issue Date: 1-Jun-2014
Publisher: Elsevier Ltd
Source: Energy, 2014, Volume 70, Pages 1-21
Abstract: In this paper, the applications of artificial intelligence-based methods for tracking the maximum power point have been reviewed and analysed. The reviewed methods are based upon neural networks, fuzzy logic, evolutionary algorithms, which include genetic algorithms, particle swarm optimization, ant colony optimization, and other hybrid methods. Rapid advances in programmable logic devices (PLDs) including field programmable gate arrays (FPGAs) give good opportunities to integrate efficiently such techniques for real time applications. An attempt is made to highlight the future trends and challenges in the development of embedded intelligent digital maximum power point tracking (MPPT) controllers into FPGA chip. Special attention is also given to the cost, complexity of implementation, efficiency, and possible practical realization. We believe that this review provides valuable information for engineers, designers and scientist working in this area and show future trends in the development of embedded intelligent techniques for renewable energy systems.
URI: http://ktisis.cut.ac.cy/handle/10488/9604
ISSN: 03605442
Rights: © 2014 Elsevier Ltd.
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