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Intelligent neural-network-based adaptive power-line conditioner for real-time harmonics filtering

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1 Author(s)
Lin, H.C. ; Dept. of Autom. Eng., Chien-Kuo Inst. of Technol., Chang-Hua City, Taiwan

Conventional approaches for harmonic filtering usually employ either passive or active filtering techniques or a combination of both. The paper proposes an alternative intelligent adaptive power line conditioner (I-APLC), which is a form of neural-network-based adaptive harmonic filtering. The I-APLC makes use of one supervised learning rule (backpropagation) which underlies the adaptive self-learning in realising the optimal filter weight vector. Experimental results obtained via a prototype model of the DC variable-speed motor verified that I-APLC is feasible in terms of real-time tracking, adaptive harmonic filtering, faster training and convergence speeds, and simplicity in the online hardware implementation.

Published in:

Generation, Transmission and Distribution, IEE Proceedings-  (Volume:151 ,  Issue: 5 )