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    The Study and Analysis of Passive Power Filter to Improve Power Quality by Using Deep Learning
    (2022-01-01)
    Dangkong, A.
    ;
    Boonseng, C.
    Passive power filter(PPFs) is widely used in large industries due to their ease of use, durability, and stability. Typically, a passive power filter's lifespan can be up to 14 years, but data has shown that it has a shorter service life because of damage to capacitors for a variety of reasons, such as capacitor's degeneration, overheating in reactor, reactor's vibration, and noise due to the flowing of harmonic current through the power filter excessively. This implies that the passive power filter system is in trouble. Furthermore, it has been found that maintaining the capacitor at a low temperature can keep the %THD level within the IEEE 519-2014 range and extend the life of the capacitor. Eventually, the collected data will be used to create a neural network for capacitor prediction and maintenance for further industrial applications.
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    Field Experience Guidelines for Maintaining Passive Power Filters to Improve for Power Factor and Power Quality Using Deep Learning Algorithm
    (2020-06-01)
    Boonseng, C.
    With more than 20 years of field experiences in Passive Power Filters (PPFs) designs, operations, and maintenances in many large scale industries in Southeast Asia, this paper reveals a simplify yet robust technique to examine and evaluate the health of PPFs that may defect during their long term functioning to maintain power factor and power quality in the electrical system. Based on the long term experience of installing a large number of PPFs, it is found that to maintenance capacitor banks in a low temperature condition will be more benefit. Under this operation condition, not only the banks can control the %THD level within the range specified by IEEE 519-1992 and 2014 standard but also make the bank last longer. Finally, the method of inspection and maintenance are proposed using neutral network algorithms for deep learning with Python. The results are complete and can be applied in industrial plants very well.