Grid-connected photovoltaic-systems design using evolutionary strategies

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Abstract

This paper addresses the problem of electrical losses that occur in the electrical conductors in photovoltaic (PV) plants with trackers. Thus, we propose a method which makes an optimal sizing and distribution of the elements that compose the PV to make the electrical losses by Joule effect as low as possible. To solve this problem, evolutionary algorithms implemented in matlab, have been used. Specifically the steady-state genetic algorithm (GA), the generational GA and the cross generational elitist selection, heterogeneous recombination and cataclism mutation (CHC) algorithm, which from random initial solutions, possibly far from optimal, will evolve into solutions that are increasingly closer to the desired optimum. Results have been very satisfactory, since all proposed examples have reduced by more than 40%, and CHC algorithm by more than 50%, electrical losses originated by not optimally designing the PV plant. © 2012 American Institute of Physics.

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Gómez-Lorente, D., Alameda-Hernández, E., Aznar Dols, F., & Espn Estrella, A. (2012). Grid-connected photovoltaic-systems design using evolutionary strategies. In Journal of Renewable and Sustainable Energy (Vol. 4). https://doi.org/10.1063/1.3690960

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