Abstract
This paper presents a novel controller design of a thyristor controlled series capacitor based on an optimized adaptive neuro-fuzzy inference system. The modified states of matter search algorithm are implemented to fit the premise and consequent parameters of the neuro fuzzy system. The design objectives are to reduce the power system oscillations and find a minimum number of strongest fuzzy rules, trends toward building a low-size controller model. Therefore, fuzzy decision-making mechanism is employed to rank the Pareto-optimal set to extract the best compromise solution. The proposed controller design depends upon the expected wide range of operating conditions. The effectiveness of smart control strategy based controller is tested and compared on single machine infinite bus and multimachine power systems under small scale disturbance as well as large scale disturbances.
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