Implementation of Echo-State Network-Based Control for Power Quality Improvement

This paper proposes a new control algorithm for mitigation of power quality problems at the distribution level. The control algorithm is designed on the basis of echo-state network, which is a type of recurrent neural network. This technique is used to extract fundamental weight components from nonsinusoidal load currents. These weight components are used to evaluate reference grid currents and consequently generate switching logic for the voltage source converter used in the active filter. The shunt-connected active filter with the proposed control algorithm is used to overcome several current-related power quality problems and provides the load compensation. Problems such as the presence of lower order harmonics, insufficient reactive power, and load unbalancing are corrected using a shunt filter in both the power factor correction and voltage regulation modes. The proposed control algorithm is validated on a real time system which is a prototype of a shunt filter. The algorithm is tested in MATLAB using Sim Power Systems and SIMULINK and implemented on a digital signal processor.

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