A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays

Mao, Mingxuan and Zhang, Li and Duan, Qichang and Oghorada, O. and Duan, Pan and Hu, Bei (2017) A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays. International Journal of Green Energy, 14 (8). pp. 694-702. ISSN 1543-5075

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: The power-voltage (P-V) characteristic curves of a PV array are nonlinear and have multiple peaks under partially shaded conditions (PSCs). This paper proposes a novel maximum power point tracking (MPPT) method for a PV system with reduced steady-state oscillation based on a two-stage particle swarm optimization (PSO) algorithm. The grouping method of the shuffled frog leaping algorithm (SFLA) is incorporated in the basic PSO algorithm (PSO-SFLA), ensuring fast and accurate searching of the global extremum. An adaptive speed factor is also introduced into the improved PSO to further enhance its convergence speed. Tests results show that the proposed method converges in less than half the time taken by the conventional PSO method, and the power is improved by 33% under the worst PSCs, which confirms the superiority of the proposed method over the standard PSO algorithm in terms of tracking speed and steady-state oscillations under different PSCs. Keywords: Maximum Power Point Tracking (MPPT); Particle Swarm Optimization (PSO); Shuffled Frog Leaping Algorithm (SFLA); Adaptive Speed Factor; Photovoltaic (PV) System; Steady-state Oscillations; Under Partial Shading Conditions(PSCs)

Item Type: Article
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Date Deposited: 16 Oct 2019 08:57
Last Modified: 16 Oct 2019 08:57
URI: https://eprints.lmu.edu.ng/id/eprint/2538

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