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Öğe Grasshopper optimization algorithm for automatic voltage regulator system(IEEE, 2018-06-21) Ekinci, Serdar; Hekimoğu, BaranA novel design method is presented to determine optimum proportional-integral-derivative (PID) controller parameters of an automatic voltage regulator (AVR) system utilizing the grasshopper optimization algorithm (GOA). The proposed approach is a simple and effective algorithm that is able to solve many optimization problems even those with unknown search spaces effectively. The simplicity of algorithm provides high quality tuning of optimal PID controller parameters. The integral of time weighted squared error (ITSE) is used as the performance index to confirm the performance of the proposed GOA-PID controller. When compared to the other PID controllers based on Ziegler- Nichols (ZN), differential evolution (DE), and artificial bee colony (ABC) tuning methods, the proposed method is found highly effective and robust to improve AVR system's transient response.Öğe Salp sürüsü algoritması kullanılarak AVR sistemi için PID kontrolör ayarı(IEEE, 2019-01-24) Ekinci, Serdar; Hekimoğu, BaranBu makalede salp sürüsü algoritması (SSA) adında yeni bir yapay zekaya dayalı optimizasyon metodu otomatik gerilim regülatörü (AVR) sisteminin en uygun oransal, integral, türevsel (PID) kontrolör parametrelerinin belirlemesi amacıyla kullanılmıştır. Algoritmanın basitliği, optimal PID kontrolör parametrelerinin yüksek kaliteli ayarını sağlar. Kontrolör parametrelerinin optimize edilmesi için zaman ağırlıklı karesel hatanın integrali (ITSE) amaç fonksiyonu olarak seçildi. Geçici hal cevap analizi, SSA metodunun Ziegler-Nichols (ZN) geleneksel ayarlama yönteminden ve yapay arı kolonisi (ABC) algoritmasından daha iyi bir ayarlama kabiliyetine sahip olduğunu ve bir AVR sisteminin basamak cevabını iyileştirmede daha verimli olduğunu ortaya koymuştur.Öğe PowSysGUI: A new educational software package for power system stability studies using MATLAB/Simulink(SAGE, 2017-10-01) Ekinci, Serdar; Demirören, Ayşen; Zeynelgil, Hatice LaleGraphical user interfaces have been progressively used in the classrooms to provide users of computer simulations with a friendly and visual approach to specify all input parameters with enhanced configuration flexibility. In this paper, an educational software package called PowSysGUI (Power System GUI), which runs on MATLAB and uses graphical user interfaces, has been developed for analysis and simulation of small to large size electric power systems. PowSysGUI is open-source software and anyone can see the inner structure of the program to figure out how to code a power engineering problem. It is designed as a simulation tool for researchers and educators, as it is simple to use and modify. PowSysGUI has algorithms for solving power flow, small signal stability analysis, and time-domain simulation. In the case studies, IEEE 16-machine 68-bus test system is given to show the features of the developed software tool. Moreover, classroom experience has shown that the developed software package helps in consolidating a better understanding of power system stability phenomena.Öğe Balina optimizasyon algoritması kullanılarak DADA düşürücü dönüştürücünün optimum PID denetleyici tasarımı(IEEE, 2019-01-24) Hekimoğu, Baran; Ekinci, Serdar; Kaya, SerhatBu makalede bir DA-DA düşürücü dönüştürücü sistemindeki oransal-integral-türevsel (PID) denetleyici parametrelerinin optimum değerlerini belirlemek için balina optimizasyon algoritmasını (WOA) kullanan yeni bir tasarım yöntemi sunulmaktadır. Önerilen algoritmanın basitliği optimum PID denetleyici parametrelerinin etkin bir şekilde hızlı ve yüksek kalitede ayarlanmasını sağlar. Önerilen WOA-tabanlı PID denetleyicinin performansı bir zaman domeni performans ölçütü kullanılarak doğrulanmıştır. Benzetim sonuçlarından, önerilen yöntemin genetik algoritmaya (GA) kıyasla DA-DA düşürücü dönüştürücünün geçici hal cevabını iyileştirmede daha etkin olduğu bulunmuştur.Öğe Parameter optimization of power system stabilizer via Salp Swarm algorithm(IEEE, 2018-06-21) Ekinci, Serdar; Hekimoğu, BaranA novel application of a very recent heuristic-based method, namely Salp Swarm Algorithm (SSA) is presented here for tuning of power system stabilizer (PSS) in a multi- machine power system. The tuning problem of PSS parameters is expressed as an optimization problem and the SSA method is utilized for searching the optimal parameters. The efficacy of the SSA-based PSS design was successfully tested on a well-known 3-machine, 9-bus power system. The results are comparatively evaluated with the other results obtained by the Tabu Search (TS) and the Biogeography-Based Optimization (BBO) methods. From the eigenvalue analysis and nonlinear simulation results it is confirmed that for damping oscillations, the performance of the proposed SSA approach in this study is better than that obtained by other intelligent techniques (TS and BBO).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.
