Research Article Adaptive Rat Swarm Optimization for Optimum Tuning of SVC and PSS in a Power System AliToolabiMoghadam , 1 MortezaAghahadi , 1 MahdiyehEslami , 2 ShimaRashidi , 3 Behdad Arandian , 4 and Srete Nikolovski 5 1 School of Industrial and Information Engineering, Polytechnic University of Milan, Milan, Italy 2 Department of Electrical Engineering, Islamic Azad University, Kerman Branch, Kerman, Iran 3 Department of Computer Science, College of Science and Technology, University of Human Development, Kurdistan Region, Sulaymaniyah, Iraq 4 Department of Electrical Engineering, Islamic Azad University, Dolatabad Branch, Isfahan, Iran 5 Power Engineering Department, Faculty of Electrical Engineering, Computer Science and Information Technology, University of Osijek, Osijek 31000, Croatia Correspondence should be addressed to Mahdiyeh Eslami; mahdiyeh_eslami@yahoo.com Received 16 October 2021; Revised 24 November 2021; Accepted 3 December 2021; Published 31 January 2022 Academic Editor: Pawan Sharma Copyright©2022AliToolabiMoghadametal.isisanopenaccessarticledistributedundertheCreativeCommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. is paper presents a new approach for the coordinated design of a power system stabilizer- (PSS-) and static VAR compensator- (SVC-) based stabilizer. For this purpose, the design problem is considered as an optimization problem, while the decision variables are the controllers’ parameters. is paper proposes an effective optimization algorithm based on a rat swarm optimizer, namely, adaptive rat swarm optimization (ARSO), for solving complex optimization problems as well as coordinated design of controllers. In the proposed ARSO, instead of a random initial population, the algorithm starts the search process with fitter solutions using the concept of the opposite number. In addition, in each iteration of the optimization, the new algorithm replaces the worst solution with its opposite or a random part of the best solution to avoid getting trapped in local optima and increase the global search ability of the algorithm. e performance of the new ARSO is investigated using a set of benchmark test functions, and the results are compared with those of the standard RSO and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed ARSO for coordinated design of controllers in a power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. e numerical investigations show that the new approach may provide better optimal damping and outperform previous methods. 1. Introduction e stability of power systems has become an important area of study, and this is mostly due to the integration of power systems. As a result, more advanced control equipment and stronger protection schemes have been added to the power system to increase stability. e electromechanical oscilla- tions, which can be classified into interarea and local modes, are observed in the power system following the unbalance between mechanical and electrical torques at the synchro- nous generator, caused by the variation of power system topology or loads [1]. When these low-frequency oscillations (LFOs) are poorly damped, the generator rotor shaft and the power transfers are highly affected. e reliability and se- curity of a power system are highly affected by these os- cillations [2]. To face these adverse phenomena, power system stabi- lizers (PSSs) have long been used to improve power system stability and enhance system damping of oscillation modes. ese stabilizers are employed to add damping torque to the generator rotor oscillations derived from speed, frequency, or power of the generator where it is connected [3, 4]. Hindawi International Transactions on Electrical Energy Systems Volume 2022, Article ID 4798029, 13 pages https://doi.org/10.1155/2022/4798029