Neural Network Harmonic Filter for Microgrid System
SETIAWAN, Dedy Kurniawan
HATTA, Agus Muhammad
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Development of electrical technology, especially converters technology, has made significant change inthe characteristics of electrical power systems. Moreover, the need of converting electrical signal from pure sine to distorted sine from renewable energy based generators makes the use of converter technology increase. Currently, the use of renewable energy based power plants together with traditional generators has become commonplace, commonly known as microgrid systems. This is intended to improve efficiency, reduce environmental pollution, and preserve nature. Microgrid systems have a very positive impact on the electric power system. However, microgrids also cause negative impacts such as harmonics. This research is developing active filter based on Neural Network concept. Neural Network is used as control strategies to produce signals opposite harmonic signals. The simulation results show that the active filter based on neural network can reduce the Total Harmonic Distortion (THD) in microgrid systems effectively.
- LSP-Conference Proceeding