Optimal fuzzy logic controller based PSO for photovoltaic system
In this study, an off-grid photovoltaic (PV) inverter generates three-phase power to supply the local load and is controlled using an optimized fuzzy logic controller (FLC) using particle swarm optimization (PSO) to control the photovoltaic system’s output. The PSO improves the three-phase inverter’...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-03-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484722024258 |
| Summary: | In this study, an off-grid photovoltaic (PV) inverter generates three-phase power to supply the local load and is controlled using an optimized fuzzy logic controller (FLC) using particle swarm optimization (PSO) to control the photovoltaic system’s output. The PSO improves the three-phase inverter’s membership functions (MFs) by using the objective function as mean square error (MSE) for voltage at the output. The best-obtained outcome of the PSO is used to trigger the gate drives of the PWM inverter. The system has been simulated and modeled using MATLAB/Simulink to validate the performance of the proposed method and shows the best control output from the inverter and has been tested in a different types of loads. The motivation for using FLC to control the shape of MFs was about saving time consumed in trial and error. The results present an output of three-phase voltage and current waveform subjected to different loading conditions. |
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| ISSN: | 2352-4847 |