A self-synchronized ADALINE network for on-line tracking of power system harmonics

This paper presents a modified adaptive linear neuron (ADALINE) structure, called self-synchronized adaptive linear neuron (S-ADALINE) network for fast and accurate estimation of power system harmonics. The proposed network relies on the Levenberg gradient descent (LGD) method based parameter updating rule and is capable of dealing with both nominal and off-nominal frequency conditions, rather than the existing modified Widrow–Hoff delta rule based ADALINE network which provides good accuracy only at nominal frequency. Moreover, the S-ADALINE provides faster response and better noise immunity than the conventional approach. The only flaw of the proposed network is its high computational load. Based on simulation studies, performances of the proposed harmonic estimator at different operating conditions have been presented and its accuracy and response time have been compared with the conventional ADALINE structure.