A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays
| Autor: | Qichang Duan, Li Zhang, Duan Pan, O.J.K. Oghorada, Hu Bei, Mingxuan Mao |
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| Rok vydání: | 2017 |
| Předmět: |
Engineering
Renewable Energy Sustainability and the Environment Oscillation business.industry 020209 energy 020208 electrical & electronic engineering Photovoltaic system MathematicsofComputing_NUMERICALANALYSIS Particle swarm optimization 02 engineering and technology Tracking (particle physics) Maximum power point tracking Power (physics) Nonlinear system Control theory Convergence (routing) 0202 electrical engineering electronic engineering information engineering business Algorithm |
| Zdroj: | International Journal of Green Energy. 14:694-702 |
| ISSN: | 1543-5083 1543-5075 |
| DOI: | 10.1080/15435075.2017.1324792 |
| Popis: | 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. Test 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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