Oppositional Differential Search Algorithm for the Optimal Tuning of Both Single Input and Dual Input Power System Stabilizer

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Author(s): Sourav Paul (Dr. B. C. Roy Engineering College, India)and Provas Kumar Roy (Kalyani Government Engineering College, Kalyani, India)
Copyright: 2021
Pages: 27
Source title: Research Advancements in Smart Technology, Optimization, and Renewable Energy
Source Author(s)/Editor(s): Pandian Vasant (University of Technology Petronas, Malaysia), Gerhard Weber (Poznan University of Technology, Poland)and Wonsiri Punurai (Mahidol University, Thailand)
DOI: 10.4018/978-1-7998-3970-5.ch013

Keywords: Computational Intelligence / Computer Science & IT / Electrical and Electronics Engineering / Engineering Science Reference

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Abstract

Low frequency oscillation has been a major threat in large interconnected power system. These low frequency oscillations curtain the power transfer capability of the line. Power system stabilizer (PSS) helps in diminishing these low frequency oscillations by providing auxiliary control signal to the generator excitation input, thereby restoring stability of the system. In this chapter, the authors have incorporated the concept of oppositional based learning (OBL) along with differential search algorithm (DSA) to solve PSS problem. The proposed technique has been implemented on both single input and dual input PSS, and comparative study has been done to show the supremacy of the proposed techniques. The convergence characteristics as well authenticate the sovereignty of the considered algorithms.

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Oppositional Differential Search Algorithm for the Optimal Tuning of Both Single Input and Dual Input Power System Stabilizer

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