An approach with filters-neural network for harmonic detection
Yong Wang · Power System Protection and Control · 2011
High-precision detection of harmonic is the basis of the assessment of energy metering and power quality.Aiming at the problem that the accuracy of algorithms of neural network harmonic detecting is largely affected by the fundamental frequency accuracy,this paper presents the digital filter combining with Newton's inverse interpolation algorithm to get fundamental frequency with high accuracy,then uses linear neural network algorithm to detect frequency,amplitude and phase of power system harmonics.The results show that under the interference of frequency fluctuation and white noise,it can still get accurate harmonic parameters,whose accuracy is much higher than that of the FFT algorithm and FFT algorithm with the Hanning window,and it has certain application value in power system.