Optimal energy harvesting from a multistrings PV generator based on artificial bee colony algorithm

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hdl:2117/192477
Document typeArticle
Defense date2020-06-08
Rights accessOpen Access
Abstract
Photovoltaic (PV) systems based on multistring configuration are the best effective solution, given its advantages in terms of system availability, reliability, and energy efficiency. In this particular configuration each substring has its own dc–dc converter and a dedicated maximum power search algorithm which increase the cost and complexity. In this article, an efficient centralized global maximum power tracking (GMPPT) algorithm for multistring PV array subject to partial shading conditions is proposed. The algorithm is based on artificial bee colony (ABC) as an optimization approach to provide the optimal duty cycles allowing the extraction of the optimal global maximum power from each substring. In particular, the proposed approach allows significant reduction of the required sensors to only one pair of current and voltage sensors, at the common point of connection of the overall PV strings. The simulation study has been carried out under Cadence/Pspice and MATLAB/Simulink platforms on the I–V curves to confirm the effectiveness of the proposed algorithm when several shading patterns occur. In addition, complex shading pattern of a daily profile has been also carried out to demonstrate the GMPPT finding in dynamically variable conditions. Performance comparison against particle swarm optimization based maximum power point tracking algorithm and the traditional perturb and observe method has also been carried out. The obtained simulation and experimental results have shown the effectiveness and a good tracking capability of the proposed ABC algorithm in a multistring PV array configuration under uniform and nonuniform irradiance.
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CitationMotahhir, S. [et al.]. Optimal energy harvesting from a multistrings PV generator based on artificial bee colony algorithm. "IEEE systems journal", 8 Juny 2020, p. 1-8.
ISSN1932-8184
Publisher versionhttps://ieeexplore.ieee.org/document/9110785
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