A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays |
| |
Authors: | Mingxuan Mao Li Zhang Qichang Duan OJK Oghorada Pan Duan Bei Hu |
| |
Institution: | 1. Automation College, Chongqing University, Chongqing, China;2. School of Electronic and Electrical Engineering, University of Leeds, Leeds, United Kingdom;3. State Grid Chongqing Electric Power Company Nan’an Power Supply Subsidiary Company, State Grid, Chongqing, China |
| |
Abstract: | 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. |
| |
Keywords: | Adaptive speed factor Maximum Power Point Tracking (MPPT) Particle Swarm Optimization (PSO) Photovoltaic (PV) System Shuffled Frog Leaping Algorithm (SFLA) steady-state oscillations Under Partial Shading Conditions (PSCs) |
|
|