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Öğe Coordinated design of TCSC and PSS by using PSO algorithm for enhancement of SMIB power system stability(Batman Üniversitesi, 2017) Ekinci, Serdar; Hekimoğlu, BaranThe main aim of this study is to investigate the enhancement of power system stability via individual and coordinated design of Thyristor Controlled Series Compensation (TCSC) and Power System Stabilizer (PSS) in single machine infinite bus (SMIB) power system. The coordinated design problem of PSS and TCSC-based controllers is formulated as an optimization problem with an eigenvalue-based objective function. Then, particle swarm optimization (PSO) algorithm is applied to search for optimal controller parameters. To compare the performance of PSS and TCSC-based controllers, both of them are designed independently at first and then in a coordinated manner for individual and coordinated applications. The proposed stabilizers are tested on a weakly connected power system subjected to various disturbances. The eigenvalue analysis and nonlinear simulation results show the robustness and the effectiveness of the proposed controllers and their ability to provide efficient damping of low frequency oscillations. Matlab/SIMULINK software package is used for the simulations.Öğe Sine-cosine algorithm-based optimization for automatic voltage regulator system(SAGE, 2019-04-01) Hekimoğlu, BaranA novel design method, sine-cosine algorithm (SCA) is presented in this paper to determine optimum proportional-integral-derivative (PID) controller parameters of an automatic voltage regulator (AVR) system. The proposed approach is a simple yet effective algorithm that has balanced exploration and exploitation capabilities to search the solutions space effectively to find the best result. The simplicity of the algorithm provides fast and high-quality tuning of optimum PID controller parameters. The proposed SCA-PID controller is validated by using a time domain performance index. The proposed method was found efficient and robust in improving the transient response of AVR system compared with the PID controllers based on Ziegler-Nichols (ZN), differential evolution (DE), artificial bee colony (ABC) and bio-geography-based optimization (BBO) tuning methods.Öğe Parameter optimization of power system stabilizers via kidney-inspired algorithm(SAGE, 2018-06-25) Ekinci, Serdar; Demiroren, Aysen; Hekimoğlu, BaranThis article describes the application of a new population-based meta-heuristic optimization algorithm inspired by the kidney process in the human body for the tuning of power system stabilizers (PSSs) in a multi-machine power system. The tuning problem of PSS parameters is formulated as an optimization problem that aims at maximizing the damping ratio of the electromechanical modes and the kidney-inspired algorithm (KA) is used to search for the optimal parameters. The efficacy of the KA-based PSS design was successfully tested on a well-known 16-machine, 68-bus power system. The obtained results are evaluated and compared with the other results obtained by the original particle swarm optimization (PSO) and the bat algorithm (BA) methods. From the detailed eigenvalue analysis, the nonlinear simulation studies and some performance indices it has been found out that for damping oscillations, the performance of the proposed KA approach in this study is better than that obtained by other intelligent techniques (PSO and BA). Moreover, the efficiency and the superior performance of the proposed method over the other two algorithms in terms of computation time, convergence rate and solution quality are confirmed.
