Yazar "Bakir, Huseyin" seçeneğine göre listele

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    Dynamic FDB selection method and its application: modeling and optimizing of directional overcurrent relays coordination
    (Springer, 2021) Kahraman, Hamdi Tolga; Bakir, Huseyin; Duman, Serhat; Kati, Mehmet; Aras, Sefa; Guvenc, Ugur
    This article has four main objectives. These are: to develop the dynamic fitness-distance balance (dFDB) selection method for meta-heuristic search algorithms, to develop a strong optimization algorithm using the dFDB method, to create an optimization model of the coordination of directional overcurrent relays (DOCRs) problem, and to optimize the DOCRs problem using the developed algorithm, respectively. A comprehensive experimental study was conducted to analyze the performance of the developed dFDB selection method and to evaluate the optimization results of the DOCRs problem. Experimental studies were carried out in two steps. In the first step, to test the performance of the developed dFDB method and optimization algorithm, studies were conducted on three different benchmark test suites consisting of different problem types and dimensions. The data obtained from the experimental studies were analyzed using non-parametric statistical methods and the most effective among the developed optimization algorithms was determined. In the second step, the DOCRs problem was optimized using the developed algorithm. The performance of the proposed method for the solution to the DOCRs coordination problem was evaluated on five test systems including the IEEE 3-bus, the IEEE 4-bus, the 8-bus, the 9-bus, and the IEEE 30-bus test systems. The numerical results of the developed algorithm were compared with previously proposed algorithms available in the literature. Simulation results showed the effectiveness of the proposed method in minimizing the relay operating time for the optimal coordination of DOCRs.
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    Dynamic switched crowding-based multi-objective particle swarm optimization algorithm for solving multi-objective AC-DC optimal power flow problem
    (Elsevier, 2024) Bakir, Huseyin; Kahraman, Hamdi Tolga; Yilmaz, Samet; Duman, Serhat; Guvenc, Ugur
    In this paper, the multi-objective AC-DC optimal power flow (MO/AC-DC OPF) problem in the presence of renewable energy sources (RESs), flexible AC transmission system (FACTS) devices and multi-terminal direct current (MTDC) systems is introduced for the first time. Conflicting objective functions and the high complexity of the objective and constraint spaces are the main challenges in finding optimal solutions for MO/AC-DC OPF. To overcome these challenges, twelve different versions of the dynamic switched crowding-based multi-objective particle swarm optimization (DSC-MOPSO) algorithm are introduced in this paper. Studies on multimodal optimization problems have shown that all DSC-MOPSO versions have better performance metrics than the MOPSO algorithm. Using the developed DSC-MOPSO and its strong competitors, the Pareto-optimal solution sets of the MO/AC-DC OPF problem are investigated. In these investigations, the performances of the algorithms are tested for the minimization of dual and triple objectives such as fuel cost, voltage level deviation, emission and power loss in a modified IEEE 30-bus power grid. According to the simulation results, the proposed DSC-MOPSO achieved an improvement in fuel cost between 0.02 % and 5.05 % and a reduction in active power loss between 0.44 % and 30.74% compared to its competitors. The Hypervolume (HV) performance metric was used to evaluate the Pareto-front coverage performance of DSC-MOPSO and other optimizers. The results from nine case studies of the MO/AC-DC OPF were statistically analyzed by the Friedman test according to the 1/HV metric. According to the Friedman test results, the rankings of DSC-MOPSO and MOMA are 1.984 and 3.079, respectively, ranking first and second among all competitors. Finally, in this study, feasible solutions for MO/AC-DC OPF problem are identified for the first time and the stability of competitive algorithms in finding these solutions is analyzed for the first time. The success rates and search times of DSC-MOPSO and MOMA algorithms in finding feasible solutions for MO/AC-DC OPF are 91.01 % (30.641 s) and 82.01 % (46.038 s), respectively.
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    Energy Hub Economic Dispatch by Symbiotic Organisms Search Algorithm
    (Springer International Publishing Ag, 2020) Guvenc, Ugur; Ozkaya, Burcin; Bakir, Huseyin; Duman, Serhat; Bingol, Okan
    Energy hub receives various energy carriers such as gas, electricity, and heat in its input and then converts them into required demands such as gas, cool, heat, compressed air, and electricity. The energy hub economic dispatch problem is a non-smooth, high-dimension, non-convex, and non-differential problem, it should be solved subject to equality and inequality constraints. In this study, symbiotic organisms search algorithm is carried out for energy hub economic dispatch problem to minimize the energy cost of the system. In an attempt to show the efficiency of the proposed algorithm, an energy hub system, which has 7 hubs and 17 energy production units, has been used. Simulation results of the symbiotic organisms search algorithm have been compared with some heuristic algorithms to show the ability of the proposed algorithm.
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    Improved adaptive gaining-sharing knowledge algorithm with FDB-based guiding mechanism for optimization of optimal reactive power flow problem
    (Springer, 2023) Bakir, Huseyin; Duman, Serhat; Guvenc, Ugur; Kahraman, Hamdi Tolga
    Optimal reactive power flow (ORPF) is of great importance for the electrical reliability and economic operation of modern power systems. The integration of distributed generations (DGs) and two-terminal high voltage direct current (HVDC) systems into electrical networks has further complicated the ORPF problem. Due to the high computational complexity of the ORPF problem, a powerful and robust optimization algorithm is required to solve it. This paper proposes a powerful metaheuristic algorithm namely fitness-distance balance-based adaptive gaining-sharing knowledge (FDBAGSK). In the performance evaluation, 39 IEEE CEC benchmark functions are used to compare FDBAGSK with the original AGSK algorithm. Moreover, the proposed algorithm is applied to perform the ORPF task in modified IEEE 30- and IEEE 57-bus test systems. The effectiveness of the FDBAGSK method was tested for the optimization of three non-convex objectives: active power loss, voltage deviation and voltage stability index. The ORPF results obtained from the FDBAGSK algorithm are compared with other optimization algorithms in the literature. Given that all results are together, it has been observed that FDBAGSK is an effective method that can be used in solving global optimization and constrained real-world engineering problems.
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    A novel optimal power flow model for efficient operation of hybrid power networks
    (Pergamon-Elsevier Science Ltd, 2023) Bakir, Huseyin; Duman, Serhat; Guvenc, Ugur; Kahraman, Hamdi Tolga
    In the power industry, the design of an efficient optimal power flow (OPF) model is one of the important research challenges. This study presents the formulation and solution of the OPF problem in the presence of RESs, VSC-MTDC transmission lines, and FACTS devices, simultaneously. Fuel cost, voltage deviation, and power loss were selected as OPF objectives and optimized with state-of-the-art metaheuristic algorithms such as MFO, BSA, COA, MRFO, TLABC, and FDB-TLABC. Based on the optimization results, FDB-TLABC has obtained the best fuel cost results of 785.5850 $/h, 815.1251 $/h, and 820.3022 $/h on the IEEE 30-bus power network. Besides, the algorithm reduced voltage deviation and active power loss by 11.76% and 0.52% compared to TLABC which second most successful algorithm, respectively. The experimental results are statistically analyzed using Wilcoxon signed-rank test. The analysis results show that the FDB-TLABC is a robust and powerful method to solve the introduced OPF problem.
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    On-board hydrogen-rich syngas production via waste heat recovery from compression-ignition engines: maximizing hydrogen content with novel multi-objective algorithms
    (Pergamon-Elsevier Science Ltd, 2025) Agbulut, Umit; Vozka, Petr; Bakir, Huseyin; Brieu, Nathan A.; Polat, Fikret; Saridemir, Suat
    A significant portion of fuel energy in internal combustion engines is lost as waste heat, yet limited efforts have been made to recover it effectively. This research explores the utilization of exhaust heat from a diesel engine to produce H2-rich syngas through the methanol-steam reforming (MSR) process. The engine operates at varying loads (15, 30, 45, and 60 Nm) while maintaining a constant speed of 2000 rpm. Exhaust heat is redirected to an MSR reactor, where the methanol-to-water (MtW) molar ratio is adjusted (0.5, 1, 1.5, and 2). Results reveal that the highest hydrogen content in syngas (70.3 %) is achieved at an engine load of 30 Nm and an MtW ratio of 1. To further optimize hydrogen production, three novel algorithms (DSC-MOPSO, MOSPO, and MOGWO) are applied to key operation parameters. Optimization increases hydrogen content to 72.5 % with DSC-MOPSO, 72.4
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    Optimal Power Flow for Hybrid AC/DC Electrical Networks Configured With VSC-MTDC Transmission Lines and Renewable Energy Sources
    (Ieee-Inst Electrical Electronics Engineers Inc, 2023) Bakir, Huseyin; Guvenc, Ugur; Duman, Serhat; Kahraman, Hamdi Tolga
    This article presents the single objective optimal power flow (OPF) formulation incorporating both renewable energy sources, and voltage source converter-based multiterminal direct current transmission lines, simultaneously. To solve the formulated OPF problem, powerful metaheuristic optimization algorithms including adaptive guided differential evolution, marine predators algorithm, atom search optimization, stochastic fractal search (SFS), and fitness-distance balance-based SFS (FDB-SFS) are employed. The performance of the algorithms is tested for the minimization of fuel cost, pollutant emissions of thermal generators, voltage deviation, and active power loss in a modified IEEE 30-bus power network. The simulation results give that FDB-SFS achieved the best results on the fuel cost (786.5361 $/h), the fuel cost with valve point effect (815.6644 $/h), and the fuel cost with emission-carbon tax (820.5991 $/h). In addition, FDB-SFS reduced voltage deviation and active power loss values by 14.2587% and 6.7438% compared to SFS. The nonparametric Wilcoxon and Friedman statistical test results confirmed that FDB-SFS is an effective and robust algorithm that can be used in the optimization of the introduced OPF problem.