Abstract
Maximum power point trackers (MPPT) are required in order to obtain optimal photovoltaic power. To achieve this task, an intelligent fuzzy particle swarm optimization (FPSO) MPPT algorithm has been proposed in this paper. Also an inverter control strategy has been gated with a ripple factor compensation-based modified space vector pulse width modulation (SVPWM) method. The proposed system performance is verified under varying sun irradiance, partial shadow, and loading conditions. For load bus voltage regulation, the buck-boost Zeta converter is selected due to least ripple voltage output. The experimental responses verify the efficiency and improved system performance, which is realized through a MATLAB/Simulink interfaced dSPACE DS1104 real-time board. The proposed MPPT and inverter current controller provides high tracking efficiency and anti-islanding protection with superior dynamic control of the system performance by injecting sinusoidal inverter current to the utility grid. The novelty of this paper is experimental implementation and verification of FPSO-based hybrid MPPT as well as modified SVPWM inverter control has neither been discussed nor implemented before using dSPACE platform by the author's best review.
| Original language | English |
|---|---|
| Article number | 8333784 |
| Journal | IEEE Systems Journal |
| Volume | 13 |
| Issue number | 2 |
| Pages (from-to) | 1861 - 1871 |
| Number of pages | 11 |
| ISSN | 1932-8184 |
| DOIs | |
| Publication status | Published - Jun 2019 |
Keywords
- Buck-boost Zeta converter
- Control systems
- Fuzzy particle swarm optimization (FPSO)
- Inverters
- Mathematical model
- Maximum power point (MPP)
- Maximum power point trackers
- Meteorology
- Photovoltaic (PV) system
- Space vector pulse width modulation
- Space vector pulse width modulation (SVPWM)
- Voltage control