Particle swarm optimization based maximum power point tracking for Partially Shaded Photovoltaic Arrays
This paper presents particle swarm optimization based perturb and observe (PSO-P&O) algorithm for maximizing output power of photovoltaic (PV) array under partially shaded conditions (PSC). During PSC, the P-V characteristic of PV will become more complex with multiple maximum power points (MPP...
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| Main Author: | |
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| Format: | Article |
| Language: | en |
| Published: |
United Kingdom Simulation Society
2016
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| Online Access: | https://eprints.ums.edu.my/id/eprint/20504/1/Particle%20swarm%20optimization%20based%20maximum%20power%20point%20tracking%20for%20Partially%20Shaded%20Photovoltaic%20Arrays.pdf https://eprints.ums.edu.my/id/eprint/20504/ https://doi.org/10.5013/IJSSST.a.17.34.20 |
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| Summary: | This paper presents particle swarm optimization based perturb and observe (PSO-P&O) algorithm for maximizing
output power of photovoltaic (PV) array under partially shaded conditions (PSC). During PSC, the P-V characteristic of PV will become more complex with multiple maximum power points (MPP). Most of the conventional maximum power point tracking (MPPT) algorithms, such as P&O, will be trapped at the local MPP and hence limiting the maximum power generation. As such, investigation on PSO-P&O algorithm is carried out to maximize the PV generated power principally under PSC operation. The performances of conventional P&O and the proposed PSO-P&O algorithms are investigated particularly on the transient and steady state responses under various shaded conditions. The simulation results show the developed PSO- P&O algorithm is able to facilitate the PV array to reach the global MPP and assist the PV array to produce more stable output power compared to the
conventional P&O algorithm. |
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