Hong, Cheong Heng (2018) Reduction of harmonic using PSO technique for grid connected photovoltaic system. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.
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Abstract
The use of photovoltaic (PV) system as an alternative energy technology for supplying clean energy become popular nowadays due to the reduction of investment capital cost. However, harmonic produced by the inverter of the PV system has led to power quality issue in the power grid. Therefore, it is highly important to control and reducing the amount of harmonic contributed by the PV. There are many existing modulation technique that had been proposed to minimize the content of the harmonic which include the use of single wave pulse-width PWM, multi-wave PWM, carrier-based PWM, sine-wave PWM and space vector PWM. In this report, a new methodology to eliminate the selective harmonic by using the harmonics elimination PWM (HEPWM) as the modulation scheme of the PV conversion system is proposed. Heuristic based algorithm approach of Modified Particle Swarm Optimization (MPSO) has been deployed in MATLab software to solve the nonlinear transcendental equations of the HEPWM. MPSO algorithm doesn’t required a good initial estimation and can be simple to be implemented with a powerful computer. Therefore, the main objective in this study is to determine the optimal switching angles for the multilevel inverter of the PV system. The obtained switching angle is used to control the multilevel inverters in order to synthesize an output stepped voltage waveform with minimum harmonic content. The simulation results show that the specific lower order of harmonics for the inverter can be removed and the overall voltage total harmonic distortion (THD) level can be reduced.
Item Type: | Thesis (Masters) |
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Additional Information: | Thesis (Sarjana Kejuruteraan (Elektrik - Kuasa)) - Universiti Teknologi Malaysia, 2018 |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Electrical Engineering |
ID Code: | 78592 |
Deposited By: | Fazli Masari |
Deposited On: | 29 Aug 2018 07:33 |
Last Modified: | 29 Aug 2018 07:33 |
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