A Backstepping Control Strategy for Power System Stability Enhancement

Wissem Bahloul, Mohamed Ali Zdiri, Ismail Marouani, Khalid Alqunun, Badr M. Alshammari, Mansoor Alturki, Tawfik Guesmi (), Hsan Hadj Abdallah and Kamel Tlijani
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Wissem Bahloul: Control & Energy Management Laboratory, Sfax Engineering School, University of Sfax, Sfax 3029, Tunisia
Mohamed Ali Zdiri: Control & Energy Management Laboratory, Sfax Engineering School, University of Sfax, Sfax 3029, Tunisia
Ismail Marouani: Control & Energy Management Laboratory, Sfax Engineering School, University of Sfax, Sfax 3029, Tunisia
Khalid Alqunun: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia
Badr M. Alshammari: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia
Mansoor Alturki: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia
Tawfik Guesmi: Department of Electrical Engineering, College of Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia
Hsan Hadj Abdallah: Control & Energy Management Laboratory, Sfax Engineering School, University of Sfax, Sfax 3029, Tunisia
Kamel Tlijani: Control & Energy Management Laboratory, Sfax Engineering School, University of Sfax, Sfax 3029, Tunisia

Sustainability, 2023, vol. 15, issue 11, 1-21

Abstract: Secure power system operation relies extensively on the analysis of transient stability and control. The dynamics involved in power system control are often complex and nonlinear. Most of the currently existing works approach these frequent problems with nonlinear control techniques, leading to a requirement for specific controller parameter adjustments. In these veins, this paper proposes a new method for stabilizing electric power systems, using nonlinear backstepping control by optimizing the controller’s parameters. The Jaya algorithm and Genetic algorithm are utilized as a powerful meta-heuristic optimization technique to search parameters of an optimal controller. Improvement in system damping, transient stability, and voltage regulation has been achieved by minimizing the integral time absolute error (ITAE) as the objective function. Numerical simulations on an SMIB power system under different fault conditions showed that the proposed method outperforms classical power system stabilizer (PSS) methods, reducing overshoots and settling times and eliminating steady-state errors. These findings highlight the effectiveness of the proposed approach and its potential contribution to the development of advanced nonlinear control techniques for electric power systems. The suggested optimization methods demonstrate superior performance, compared to classical methods, and achieve a reduction of 27.5% in overshoot and 87% in transient time in addition to complete elimination of static error.

Keywords: backstepping control; excitation control; genetic algorithm; Jaya algorithm; SMIB power system (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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