Yazar "Kilic, Ulas" seçeneğine göre listele

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    Applications of Novel Heuristic Algorithms in Design Optimization of Energy-Efficient Distribution Transformer
    (Ieee-Inst Electrical Electronics Engineers Inc, 2023) Hashemi, Mohammad Hassan; Kilic, Ulas; Dikmen, Selim
    Transformers are crucial and expensive assets of power grids. Reducing power losses in power and distribution transformers is important because it increases the efficiency of the transformer, which in turn reduces the costs for the utility company and consumers. Losses in the transformer generate heat, which can reduce the lifespan of the transformer and require additional cooling. Additionally, reducing losses can help to decrease greenhouse gas emissions associated with the generation of electricity. This study presents an optimization method for transformer design problem using variables that have a great impact on the performance of a transformer. Due to the non-convex nature of the transformer design problems, the empirical methods fail to find the optimal solution and the design process is very tedious and time-consuming. Considering No Free Lunch (NFL) theorem, the design problem is solved using four novel heuristic optimization algorithms, the Firefly Optimization Algorithm (FA), Arithmetic Optimization Algorithm (AOA), Grey Wolf Optimization Algorithm (GWO), and Artificial Gorilla Troops Optimizer Algorithm (GTO) and the results are compared to an already manufactured 1000 kVA eco-friendly distribution transformer using the empirical methods. The outcome of the optimization shows that the suggested method along with the algorithms mentioned leads to a notable decrease in power losses by up to 3.5%, and a reduction in transformer weight by up to 8.3%. This leads to an increase in efficiency, decreased costs for materials, longer lifespan and a reduction in emissions. The developed model is capable of optimally designing oil-immersed distribution transformers with different power ratings and voltage levels.
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    The artificial neural network modelling of the piezoelectric actuator vibrations using laser displacement sensor
    (Slovak Univ Technology, 2017) Parali, Levent; Sari, Ali; Kilic, Ulas; Sahin, Ozge; Pechousek, Jiri
    We report an improvement of the artificial neural network (ANN) modelling of a piezoelectric actuator vibration based on the experimental data. The controlled vibrations of an actuator were obtained by utilizing the swept-sine signal excitation. The peak value in the displacement signal response was measured by a laser displacement sensor. The piezoelectric actuator was modelled in both linear and nonlinear operating range. A consistency from 90.3 up to 98.9% of ANN modelled output values and experimental ones was reached. The obtained results clearly demonstrate exact linear relationship between the ANN model and experimental values.
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    Multi-objective design optimization of hermetically sealed core-type distribution transformer considering current harmonics of power grid using NSGA III
    (Elsevier - Division Reed Elsevier India Pvt Ltd, 2024) Hashemi, Mohammad Hassan; Kilic, Ulas
    In this paper, the design optimization of hermetically sealed oil-immersed distribution transformers is studied. For the first time in the design of this type of transformer, harmonics of the power grid affecting the transformer design, along with all design variables, are included, and their boundaries suitable for the production line are determined. The design probability (search space) for a total of 21 design variables is 1.32x . 32x 10 25 . The Brute Force method is not a time-efficient approach to finding the optimal result in this search space. Due to the mixed integer nonlinear programming (MINLP) nature of the transformer design problem, heuristic optimization algorithms are selected because of their shorter solution time and near-optimal results. Considering the principle of the No Free Lunchtheorem, extensive evaluations were conducted on various heuristic algorithms to identify the most effective ones for addressing the transformer design problem. The most successful algorithms for solving the problem were identified after thorough evaluation, considering three distinct scenarios within a multi-objective optimization framework. These algorithms are namely MOEA/D, MOGWO, MOWOA, and NSGA III. In this study, an optimization tool is developed for the design optimization of hermetically sealed distribution transformers, covering a range from 50 kVA to 3150 kVA and encompassing all design variables. The developed optimization program is fully compatible with the production line and can be easily adjusted to meet all national and international standards, such as IEC and IEEE, as well as customer specifications.
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    Multi-objective optimization of a small turbojet engine energetic performance
    (Pergamon-Elsevier Science Ltd, 2023) Aygun, Hakan; Kirmizi, Mehmet; Kilic, Ulas; Turan, Onder
    Application fields of small turbojet engines (STJE) have been increasing day by day due to their superior features such as high power to weight ratio and reliability. In this study, parametric cycle analysis peculiar to STJE is implemented for different design variables such as compressor pressure ratio (CPR), turbine inlet temperature (TIT) as well as ambient temperature (T0). Based on these evaluations, several performance metrics of STJE are dealt with together by applying three different methods such as multi-objective genetic algorithm (MOGA), particle swarm optimization (MOPSO) and grey wolf optimization (MOGWO) under five analyses. According to performance analyses, net thrust of the STJE has improvement from 3.2 kN to 5.41 kN due to the increased TIT whereas it deteriorates from 4.87 kN to 4.67 kN due to the elevated CPR. However, with effect of the higher TIT, specific fuel consumption (SFC) of the STJE ascends from 42.96 g/kNs to 49.04 g/kNs while it diminishes from 39.57 g/kNs to 31.5 g/kNs owing to the higher CPR. The higher T0 leads net thrust to lower but the higher SFC. According to optimization findings at fourth analysis, the lower SFC is obtained with 31.51 g/kNs by MOGA than the other methods where SFC is 33.11 g/kNs whereas the higher net thrust is obtained with 6.209 kN by both MOPSO and MOGWO than the findings of MOGA where net thrust is 4.68 kN. When considering five optimization analyses, the findings of MOGA, MOGWO and MOPSO could be utilized depending on aircraft mission that turbojet engine requires to perform. It is thought that performing of multi-objective optimization could help in designing turbojet engines to the engineers.
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    A new approach for optimal reactive power flow of MTDC systems using the ABC algorithm
    (Tubitak Scientific & Technical Research Council Turkey, 2017) Kilic, Ulas; Ayan, Kursat
    This paper presents a new approach to optimize reactive power ow of multiterminal high voltage direct current (HVDC) systems. Successful application of two-terminal DC systems worldwide makes the use of multiterminal direct current (MTDC) systems more attractive. Due to the economic and technical advantages of HVDC technology, MTDC systems have been used extensively in recent years. In this study, the artificial bee colony (ABC) algorithm is used for solution of the optimal reactive power ow problem of MTDC systems. In opposition to the current-balancing method used in the literature, this study represents a new approach for DC system power ow calculations. The proposed approach is tested on a sample IEEE MTDC test system. The results by the proposed approach are compared with those reported in the literature. Thus, the applicability and the efficiency of this approach used together with the ABC algorithm are shown.
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    Optimal reactive power flow of power systems with two-terminal HVDC and multi distributed generations using backtracking search algorithm
    (Elsevier Sci Ltd, 2021) Fadel, Waleed; Kilic, Ulas; Ayan, Kursat
    This paper deals with optimal reactive power flow (ORPF) of power systems with two-terminal high voltage direct current (HVDC) and multi distributed generations (DGs) using backtracking search algorithm (BSA). For the first time with this study, the power system is modeled closest to the real world and the power loss of both test systems are minimized by BSA, while DGs and HVDC links are existing simultaneously in the power systems. Although simulations on modified IEEE 30-bus and modified IEEE 57-bus test systems have given successful results by using BSA, genetic algorithm (GA) was also used to compare the outcomes of different algorithms. This study was performed for five and three different cases of the modified 30-bus and modified 57-bus test systems, respectively. The obtained results show that although the power loss does not vary much according to the connection points of HVDC link, the optimal replacement of the DGs to the power system reduces the power loss considerably. in addition to this, when the obtained results are compared with those in the literature, it is seen that the proposed algorithm is better than the other algorithms in terms of performance and effectiveness.
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    Placement of Dg, Cb, and Tcsc in radial distribution system for power loss minimization using back-tracking search algorithm
    (Springer, 2017) Fadel, Waleed; Kilic, Ulas; Taskin, Sezai
    The back-tracking search algorithm (BSA) is a new heuristic algorithm. BSA has two especially important properties: it is not sensitive to the initial value and has a single control parameter. This study presents the BSA-based optimal sizing and placement of distributed generations (DGs), capacitor banks (CBs), and thyristor-controlled series compensator (TCSC) in a radial distribution system (RDS). These elements are integrated separately and simultaneously in RDS. The objective function is power loss. The BSA is executed on IEEE 33 bus RDS. The obtained results are compared to a genetic algorithm (GA) and other algorithms in the literature. The results demonstrate that the BSA is more efficient and has the potential to find optimal solutions with less power loss. In this paper, optimal placement and sizing of DGs, TCSC, and CBs in a RDS is solved simultaneously using BSA for the first time.