Please use this identifier to cite or link to this item:
|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||Category:||Electrical Engineering - Electronic Engineering - Information Engineering||Field:||Engineering and Technology||Issue Date:||1-Jun-2014||Publisher:||Elsevier Ltd||Source:||Energy, 2014, Volume 70, Pages 1-21||metadata.dc.doi:||http://dx.doi.org/10.1016/j.energy.2014.03.102||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.||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
Show full item record
Page view(s) 10101
checked on Dec 10, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.