Abstract
This research deals with designing a new adaptive neuro controller-based Distributed Static Compensator (DSTATCOM). It works on a multi-layer neural network-based Anti-Hebbian Least Mean Square (AHLMS) control scheme. This scheme combines different weighting factors like step size, learning rate, convergence factor, and integral weight to achieve the approximate weight, thus developing reduced storage capacity while diminishing static error. Furthermore, this AHLMS controller accomplishes accurate harmonic reduction and power factor improvement under modified loading states on the grid side. Besides this, the voltage regulation at the DC bus and balanced voltage at the point of regular coupling (PCC) is enhanced further. As a result, system efficiency and power quality are obtained with the reduced size of the DSTATCOM. The analytical results are demonstrated using MATLAB/Simulink to promote the suitable Power Distribution System (PDS) controller as per the IEEE-519 standard.
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