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    Fitness Distance Balance Based LSHADE Algorithm for Energy Hub Economic Dispatch Problem
    (Ieee-Inst Electrical Electronics Engineers Inc, 2022) Özkaya, Burçin; Güvenç, Uğur; Bingöl, Okan
    This paper presents an improved version of Linear Population Size Reduction Success History Based Adaptive Differential Evolution (LSHADE) algorithm for solving global optimization problems. Fitness Distance Balance (FDB) selection method was used to redesign the mutation operator in order to enhance the search performance of the LSHADE algorithm. In order to test and validate the performance of the proposed algorithm, a comprehensive experimental study was carried out. For this purpose, it was tested on the CEC14 and CEC17 benchmark problems, consisting of different problem types and dimensions. Results of the FDB-LSHADE was compared to the performance of 8 other up-to-date and highly preferred metaheuristic search (MHS) algorithms. According to Friedman test results, the proposed FDBLSHADE algorithm ranked first among the all competing algorithms. Moreover, the proposed algorithm was used to solve single- and multi-objective energy hub economic dispatch (EHED) problems, which were a non-convex, a nonlinear, and high dimensional problems. To analyze the results of the proposed algorithm obtained from experimental studies, two non-parametric statistical methods, which are Wilcoxon and Friedman tests, were used. The simulation results of the proposed algorithm were compared to the results of the 8 other MHS algorithms. The results demonstrated that the FDB-LSHADE was a superior performance compared to other MHS algorithms for solving both benchmark and EHED problems.
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    Obtaining Maximum Electrical Energy with PV Panel Layout Optimization in Space Truss Roof Systems
    (2021) Bingöl, Okan; Pişirir, Onur Mahmut; Kiriş, Berkay
    Solar panel is mostly applied in many roof types on buildings. That the angle of solar radiation is different in curved space truss system affects the amount of voltage and current of the solar panels and overall system efficiency. In this study, meteorological information of Isparta city, technical data of various solar panels, intrayear random shadow effect calculations are analyzed. The technic of genetic algorithm is applied, and the process of computerized simulation is performed in order to find the optimal solar panel combination. Based on the simulation results, the highest efficiency will be obtained from the PV panels if PV panels application is made on the curved space truss roof system.
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    OPTİMAL REAKTİF GÜÇ DAĞITIMI İÇİN KIR KURDU OPTİMİZASYON ALGORİTMASI
    (2020) Güvenç, Uğur; Bingöl, Okan; Özkaya, Burçin
    Optimal reaktif güç dağıtım problemi, sürekli ve ayrık kontrol değişkenlerini içerendoğrusal olmayan ve dışbükey olmayan bir optimizasyon problemidir. Buçalışmada, kır kurdu optimizasyon algoritmasının optimal reaktif güç dağıtımproblemine uygulaması sunulmuştur. Kır kurdu optimizasyon algoritması, optimalreaktif güç dağıtım problemi için IEEE-30 ve IEEE-50 baralı sistemlerde testedilmiştir. Benzetim sonuçları, literatürde verilen SHADE-EC algoritmasınınsonuçları ile karşılaştırılmıştır. Karşılaştırma sonuçları, optimal reaktif güç dağıtımproblemini çözmek için kır kurdu optimizasyon algoritmasının üstünlüğünü vedoğruluğunu göstermiştir.
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    Stochastic Fractal Search with Chaos
    (Ieee, 2017) Bingöl, Okan; Güvenç, Uğur; Duman, Serhat; Paçacı, Serdar
    In this study, the convergence speed and fitness function accuracy have been compared with the original algorithm by developing on the Stochastic Fractal Search (SFS) algorithm. Seven classical mathematical benchmark functions used in testing the optimization algorithms in the literature were used in comparison process. In the original SFS algorithm, the Gaussian walk function is used to find new solution points in diffusion process. The step length in this walk decreases as the iteration progresses and a function depending on generation value is used to provide for a more local search. The improvement in this work is the process of adding chaotic map values to this function. According to simulation results, it is observed that seven chaotic map improves the original algorithm from ten chaotic maps applied to SFS algorithm.