Yazar "Can, Ozay" seçeneğine göre listele

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    Automatic generation controller based on whale optimization algorithm in PV-thermal power systems
    (Gazi Univ, Fac Engineering Architecture, 2023) Can, Ozay; Eroğlu, Hasan; Öztürk, Ali
    To ensure a balance between the power generated and the consumed power in power systems, a control process namely automatic generation control (AGC) must be carried out. This process becomes more challenging due to increasing use of renewable energy sources (RES) such as wind turbines (WT) and photovoltaic (PV) panels. Therefore, AGC needs to be performed more sensitively. In this study, it has been aimed to determine the parameters of the PID controller by using the whale optimization algorithm (WOA) for the AGC in a hybrid power system consisting of photovoltaic (PV) system and thermal generator. The performance of WOA tuned PID controller is tested under load change in area-1 and area-2. Additionally, comparisons have been made with the performances of other optimization techniques such as firefly algorithm (FA), genetic algorithm (GA) and population extremal algorithm (PEO). The results obtained indicated that the WOA tuned PID controller proposed in the study gave better results than the other methods in terms of overshoot values and settling time of system frequency.
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    Enhancing automatic generation control in renewable energy-integrated thermal power systems with a novel PID+Iλ controller tuned by INFO algorithm
    (Sage Publications Ltd, 2025) Can, Ozay; Ayas, Mustafa Sinasi; Celik, Emre
    Electrical systems need to balance generation and demand to ensure that customers are supplied with safe and high-quality electricity. Failure to maintain this balance may result in unwanted frequency oscillation and, accordingly, tie-line power variation. Automatic generation control (AGC) is an important mechanism for controlling system responses and keeping them within predetermined bounds. Integrating renewable energy sources (RESs) into the grid can be complicated due to their erratic and weather-dependent nature, leading to imbalances in generation and consumption. To reduce these disparities, this study focuses on developing a novel proportional-integral-derivative (PID)+I-lambda controller for the AGC in a two-area thermal power system utilizing wind turbines and photovoltaic (PV) panels as renewables. For achieving the best possible performance, the controller parameters are optimized using the weighted mean of vectors (INFO) algorithm. Simulation studies are conducted to evaluate the performance of the proposed controller under different load demands and RES scenarios. Comparative studies are also conducted to evaluate the true efficacy of the INFO-tuned PID+I-lambda controller against some published control schemes available in the literature. It is found that our proposal outperforms its rivals in mitigating the unwanted system oscillations, lessening the overshoot/undershoot, and shortening the settling time of frequency and tie-line power responses.
  • Küçük Resim Yok
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    Frequency and voltage stability improvement in a two-area thermal power system using a novel controller and RIME optimizer
    (Pergamon-Elsevier Science Ltd, 2025) Can, Ozay; Ayas, Mustafa Sinasi; Celik, Emre
    This work presents a novel method for integrating the Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) processes to enhance frequency and voltage stability in two-area non-reheat thermal power systems. In this study, we present a novel Proportional Derivative-(1+Double Integral) (PD-(1+II)) controller, which is optimized through the utilization of the recently created Rime Optimization Algorithm (RIME). This represents the first time that the RIME algorithm and the PD-(1+II) controller are used in the context of coupled LFC-AVR systems. Our comprehensive research encompasses six distinct scenarios, including AVR system tuning, LFC system tuning, combined LFC-AVR system tuning, disturbance analysis, nonlinearity analysis, and parameter sensitivity analysis. A comparative analysis is conducted between the proposed RIME-tuned PD-(1+II) controller and established techniques such as the Nonlinear Threshold Accepting (NLTA) algorithm and its multi-objective version (MONLTA) tuned PID controllers, i.e. MONLTA-PID and NLTA-PID controllers. The simulation results demonstrate that the RIME-tuned PD-(1+II) controller consistently outperforms existing techniques. It exhibits superior performance in terms of overshoot reduction (100 % decrease in frequency deviation and 30 % decrease in terminal voltage) and faster settling times (50 % decrease in frequency control and 30 % decrease in voltage control) when compared to current methods. Furthermore, the controller demonstrates resilience in the presence of a diverse range of disturbances, nonlinearities, and parameter variations, highlighting its adaptability and reliability in a multitude of operational scenarios. The efficacy and reliability of the proposed methodology are further substantiated by statistical analysis, which demonstrates that it outperforms existing optimization algorithms, including the Gorilla Troops Optimizer (GTO) and the Whale Optimization Algorithm (WOA), with the RIME algorithm achieving an average ITSE value of 0.0881 compared to 0.1023 for GTO and 0.1057 for WOA.
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    A Novel Grey Wolf Optimizer Based Load Frequency Controller for Renewable Energy Sources Integrated Thermal Power Systems
    (Taylor & Francis Inc, 2022) Can, Ozay; Öztürk, Ali; Eroğlu, Hasan; Kotb, Hossam
    The frequency value should be kept constant to ensure and maintain synchronization in power systems. When the balance between generation and load is interrupted, the frequency value increases or decreases. This frequency deviation may lead to serious problems in the power system. Therefore, a design of a controller is required to keep the system frequency and tie-line power variations within specified limits, which is called automatic generation control (AGC) or load frequency control (LFC). This paper aims to determine the optimal controller parameters used in the LFC for a two-area non-reheat thermal power system integrated with various renewable energy sources (RES) such as photovoltaic (PV) and wind energy systems. The proposed controller is a PI-(1 + DD) controller which is a combination of proportional, integral, and double derivative controllers. The optimal gains of the proposed controller are determined by the Grey Wolf Optimization (GWO) algorithm. Moreover, the performance of the PI-(1 + DD) controller is tested under various scenarios such as different step load perturbations, random load changes, system parameters and RES variation. The results show that the PI-(1 + DD) controller provides an improvement of about 40% in system frequency overshoot and about 45% in settling time compared to other controllers.