@article{MAKHILLJEAS2019141718293,
    title = {Harmonic Filter for Microgrid Based on Extreme Learning Machine},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {17},
    pages = {6385-6391},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.6385.6391},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.6385.6391},
    author = {Mat,Adi,A.M.,M.F.,N.H. and},
    keywords = {total harmonic distortion,extreme learning machine,active filter,Converter,microgrid,plants},
    abstract = {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.}
    }