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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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    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.