TY  - JOUR
T1  - Harmonic Filter for Microgrid Based on Extreme Learning Machine
AU - Syai’in, Mat AU - Soeprijanto, Adi AU - Hatta, A.M. AU - Adiatmoko, M.F. AU - Rohiem, N.H. AU - Setiawan, D.K. 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 17
SP  - 6385
EP  - 6391
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.6385.6391
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.6385.6391
KW  - total harmonic distortion
KW  -extreme learning machine
KW  -active filter
KW  -Converter
KW  -microgrid
KW  -plants
AB  - The development of converter technology has made the price of renewable energy–based power
plants more affordable. The increasing number of renewable energy–based power plants has a positive impact
but also has a negative impact. One of the negative impacts that occur in renewable energy–based power plants
is the emergence of harmonics. Harmonics in principle cannot be removed from the electric power system but
harmonics can be controlled in order to minimize the negative impact. This research is developing active filter
based on Extreme Learning Machine (ELM) concept. ELM is used as control strategies to produces signals
opposite with harmonic signals. From the simulation results shown that the active filter based on ELM can
reduce the Total Harmonic Distortion (THD) in microgrid systems effectively.
ER  -