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This paper proposes a comparative assessment of NN based current controllers followed by hardware validation towards power quality improvement in grid-interactive VSI controlled solar system. The steady state errors, transient disturbances and high current harmonic effects encountered in conventional linear PI and PR controllers are nullified by employing intelligent adaptive current controller. Three adaptive current control strategies viz. ADALINE-LMS, ALLMS, and VLAS-LMS are identified by using artificial neural network topology having been controlled by different weight-regulating algorithms which helps in minimizing current harmonics generated by the widespread use of VSI, non-linear loads, faults and uncertain polluted grid. A comprehensive comparative study is driven from the proposed adaptive controller's stability and convergence criterion, current magnitudes calculated at different power zones, % overshoot, settling time and power quality and analyzed under numerous operating conditions. From the comparative assessment performed in between conventional and intelligent current controllers, it is confirmed that the intelligent control technique performs best under the non-linear loads and transient conditions whereas all the controllers perform equally good under the linear loads. Proposed methods are simulated in MATLAB/Simulink and their effectiveness is compared in terms of time responses, stability and low-order current harmonics compensation capability. The robustness of the intelligent current controller is established through the experimental performances using dSPACE RTI 1202.

A Comparative Study on Neural Network Based Controllers Used in Grid-Interactive Solar System