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- W2793061097 abstract "Fuel Cell (FC), as a type of new renewable energy sources grid-connected at Point of Common Coupling (PCC), is introduced in this study. This article presents the power quality improvement of the FC integrated to the power network through a chopper and an inverter using the conventional PI controller. Two PI controllers, tuned by three recent different evolutionary computing techniques namely Harmony Search (HS), Modified Flower Pollination Algorithm (MFPA) and Electromagnetic Field Optimization (EFO) methods are considered. The two PI controllers are used for driving the inverter connected the on-grid FC in order to govern the PCC voltage between the FC and the power network. These two controllers are exploited to drive the power and the current regulators at different voltage sag and swell conditions. The three optimization methods are compared to the Particle Swarm Optimization (PSO) with regards to voltage profile, power quality and execution time. Simulation results, using Matlab/Simulink™, show the significance of the three optimization techniques in regulating the voltage at PCC with reduced harmonics during the system voltage sag and swell conditions when compared to the PSO. Through the numerical analysis, the superiority of MFPA method among the different optimization metaheuristic techniques is highlighted particularly for enhanced dynamic voltage response purposes." @default.
- W2793061097 created "2018-03-29" @default.
- W2793061097 creator A5029782611 @default.
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- W2793061097 date "2018-06-01" @default.
- W2793061097 modified "2023-10-15" @default.
- W2793061097 title "Power quality enhancement of grid-connected fuel cell using evolutionary computing techniques" @default.
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- W2793061097 doi "https://doi.org/10.1016/j.ijhydene.2018.02.001" @default.
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