Yazar "Taplamacioglu, M. C." seçeneğine göre listele

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    Robust Tuning of Power System Stabilizer by Using Orthogonal Learning Artificial Bee Colony
    (Elsevier Science Bv, 2015) Eke, I.; Taplamacioglu, M. C.; Lee, Kwang Y.
    This study presents a design technique of a robust power system stabilizer using different performance indices obtained from artificial bee colony (ABC) algorithm. The parameters of a power system stabilizer (PSS) are tuned by using the ABC algorithm to achieve an acceptable overshoot and settling time at all load points within a wide region of operation. The objective function allows the selection of the stabilizer parameters to minimize the overshoot and settling time at all load conditions. For robust PSS performance, a wide range of operating conditions is considered for search space. The designed PSS is applied to a single-machine infinite-bus system operating at different loading conditions and the results demonstrated that the developed technique is very effective.
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    Solving the Optimal Power Flow Quadratic Cost Functions using Vortex Search Algorithm
    (Elsevier Science Bv, 2017) Aydin, O.; Tezcan, S. S.; Eke, I; Taplamacioglu, M. C.
    This study proposes solving the constraint optimal power flow problem (OPF) by using vortex search algorithm (VSA). VSA is inspired by natural vortexes. Piecewise quadratic fuel cost and quadratic cost curve with valve point loadings test cases are solved on IEEE-30 bus test system by taking into consideration the system constraints such as generation limits, voltages at nodes, tap settings. The obtained test results show that VSA gives better results than any other algorithms which are used to solve the OPF problem. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.