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    Effects of Wind Turbine Height Variation on Hybrid Power System Feasibility
    (Institute of Electrical and Electronics Engineers Inc., 2024) Öztürk, Zafer; Terkes, Musa; Andic, Cenk; Öztürk, Ali; Türkay, Belgin Emre
    In carbon neutrality plans, hybrid power systems (HPS) are critical to the growing popularity of prosumers. For regions with higher wind potential, a sensitive study of wind energy in optimization frameworks with different objective functions will enhance competition against the dominant solar market. In this study, HPSs located at various case areas with higher wind potential are optimally sized for community electricity consumption and minimum cost objectives. The feasibility results of the optimum sizes are evaluated for the effects of increasing wind turbine (WT) hub heights considering flexible and constrained electricity sales. The results show that higher WT heights in Gemlik and -anakkale will optimize performance. It has also been proven that higher WT heights will increase carbon emissions up to 930.1 tons/yr, while restricting electricity sales by 40% will increase the excess electricity by up to 21.4% and reduce the renewable fraction by up to 7.5%. © 2025 Elsevier B.V., All rights reserved.
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    A Novel Puma Optimizer Based TID Controller for Load Frequency Control
    (Institute of Electrical and Electronics Engineers Inc., 2024) Andic, Cenk; Öztürk, Ali; Aydin, Esra; Türkay, Belgin Emre
    This paper presents the Puma Optimizer (PO) algorithm, a novel approach to the load frequency control problem. The proposed PO algorithm optimizes the gain parameters of the tilt-integral-derivative (TID) controller used for load frequency control in a two-area interconnected power system with a PV system. In this study, the proposed PO algorithm for optimizing the TID controller was compared with ImRSA, RSA, MGWO-CS and PDO algorithms, which were previously published in the literature. In the optimization of the TID controller’s gain parameters based on the ITAE metric, the proposed PO algorithm achieved the best performance with a value of 0.7441, followed by ImRSA with 0.8239, RSA with 0.9251, MGWO-CS with 0.9203 and PDO with 0.8108. The performance of the optimized TID controller was evaluated based on the system’s frequency response to a 0.1 p.u load disturbance in both areas. According to the simulation results obtained, it was observed that the proposed PO algorithm provided the fastest settling time and the minimum overshoot and undershoot values in the frequency response of the system in both areas and the tie-line against load changes. © 2025 Elsevier B.V., All rights reserved.
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    Quantum Genetic Algorithm for Dynamic Economic Dispatch of Active Distribution Network with Microgrid Including Renewable Energy Source
    (Institute of Electrical and Electronics Engineers Inc., 2024) Andic, Cenk; Öztürk, Ali; Türkay, Belgin Emre
    This paper presents a Quantum Genetic Algorithm (QGA) for the Dynamic Economic Dispatch (DED) of Active Distribution Networks (ADNs) with a Microgrid (MG) including renewable energy source. The economic dispatch problem aims to minimize the operating cost of the power system while meeting the load demand and satisfying operational constraints. The integration of renewable energy sources, such as wind and solar, into the power system presents new challenges due to their intermittent and uncertain nature. The proposed QGA-based DED approach considers the uncertainties of renewable energy source and enables the effective optimization of the system operation. The QGA combines the advantages of both quantum computing and genetic algorithm to provide a more efficient and effective solution. Therefore, quantum-bits (qubits) offer a much wider computational capability than the classical bits used in traditional genetic algorithms. The proposed approach is tested on the IEEE 37 bus system with two photovoltaic systems, and the results demonstrate its superior performance compared to other well-known methods which are Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. The proposed QGA provides an effective solution for the DED problem in ADNs with MGs and renewable energy sources, which can contribute to the development of sustainable and efficient power systems. © 2024 Elsevier B.V., All rights reserved.