Multi-objective states of matter search algorithm for TCSC-based smart controller design

• Published in: Electric power systems research 2016-11, Vol.140, p.874-885
• Main Authors: Mohamed, Al-Attar Ali, El-Gaafary, Ahmed A.M., Mohamed, Yahia S., Hemeida, Ashraf Mohamed
• Format: Article
• Language: English
• Subjects: ANFIS; Multi-objective states of matter search; Pareto-optimal solutions; TCSC
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2016.04.017

•This paper proposes adaptive SMS based TCSC for damping power system oscillations.•The proposed control strategy is able to reduce the size of the smart controller.•Effectiveness of the developed technique is tested on SMIB and multimachine systems.•Several case studies are applied in single and multi-objective optimization space.•Nonlinear results confirm the superior performance of the new algorithm. 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.