Elektrik Elektronik Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/411
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Article Citation - Scopus: 4Cost Optimization of Oil Type Distribution Transformer Using Multi-Objective Genetic Algorithm(Erol Kurt, 2024) Iskender, I.; Yükselen, E.; Telli, S.The demand for electrical energy is increasing day by day with the development of technology in the world. Distributing electric energy to all regions that need energy is a principal issue, and this necessitates the use of transformers to convert the voltage to the desired level. Accordingly, the use of transformers, one of the electrical devices converting AC voltage level at a defined frequency has grown significantly. In this study, design parameters of a 25 kVA, 33/0.4 kV, Yzn11, oil-type distribution transformer are optimized using the Multi-Objective Genetic Algorithm (MOGA) technique by decreasing the weight of the significant materials and manufacturing cost. Electromagnetic analysis of the transformer is performed with ANSYS Maxwell based on the design results obtained from the optimization study for validation of the method. The experimental design parameters are also compared with the optimization results. It is observed that optimum results are achieved by using the proposed approach. © 2024 Published by peer-reviewed open access scientific journal, JES at DergiPark (https://dergipark.org.tr/jes)Article Citation - WoS: 4Citation - Scopus: 6Case Study on Thermal Optimization of Oil Immersed Transformer Used in Solar Power Plant Based on Genetic Algorithm and Computational Fluid Dynamics(Vinca inst Nuclear Sci, 2023) Iskender, Ires; Yukselen, EmirTransformers are one of the most capital investments in the solar power generation. Their safe and stable operations in the electrical networks are important. The main failure factor of transformers is the high temperature generated by the losses during operation, which increases the probability of insulation damage that significantly affects the useful life of transformer. Considering the importance of oil temperature and its effects on the life of the transformer, a numerical method is developed in this paper to optimize the cooling system of the transformer. In this regard, genetic algorithm is used as an optimization method to minimize the total cost of the cooling system while maintaining the required thermal conditions of the transformer. A comprehensive parametric study is carried out among the effective cooling geometry parameters using 3-D electromagnetic and thermal models of the photovoltaic transformer to evaluate and analyze the temperature distribution. The accuracy and feasibility of the proposed method is established by comparing the numerical results with those obtained from the experimental test. The results of the proposed method are found to be in a good agreement with the experimental and simulation results.Article Antenna Synthesis by Levin's Method Using Reproducing Kernel Functions(Applied Computational Electromagnetics Soc, 2023) Sener, GokerAn antenna synthesis application is presented by solving a highly oscillatory Fourier integral using a stable and accurate Levin's algorithm. In antenna synthesis, the current distribution is obtained by the inverse Fourier integral of the antenna radiation pattern. Since this integral is highly oscillatory, the Levin method can be used for its solution. However, when the number of nodes or the frequency increases, the Levin method becomes unstable and ineffective due to the large condition number of the interpolation matrix. Thus, an improved scheme of the method is used in an antenna synthesis application in which reproducing kernel functions are used as the basis of the approximation function. The accuracy of the new method is verified by a log-periodic antenna example. The error and stability analysis results show that the new method is more stable and accurate than other well-known kernels, especially for a large number of nodes.Article Citation - WoS: 1Citation - Scopus: 1Sustainable Management of a Renewable Fishery Resource With Depensation Dynamics From a Control Systems Perspective(Gazi Univ, 2022) Cıfdaloz, OguzhanHuman societies are exploiting natural renewable sources such as fisheries, forests, groundwater basins, rivers, and soil at an increasing intensity. Around the world, these resources are being managed by various institutions or governments. One of the challenges faced by institutions is to develop strategies and policies to effectively manage these renewable resources under social and ecological uncertainties, disturbances, policy implementation difficulties, and measurement errors. In this paper, a fishery is considered as an example and the problem of managing a fishery is approached from a control systems perspective. The justification behind this approach is due to the observation that the problem of managing a renewable resource can be posed as a control systems problem and that the discipline of control systems possesses tools and methods to deal with model uncertainties, external disturbances, measurement errors and implementation issues. For the fishery, a depensation type population dynamics model is considered. Depensatory models are used in social/ecological systems in order to model dynamics of certain species of fish populations. An optimal control strategy based on Pontryagin’s Maximum Principle is derived and its sustainability and robustness properties with respect to parametric uncertainties, measurement errors and disturbances are examined. Finally, a sub-optimal but more robust control strategy is proposed and its robustness properties are provided. The main objective of the paper is to show that a control systems engineering approach can be applied to a social-ecological problem and it can provide easy to implement management strategies, insight, and guidance into the management of renewable resources.Conference Object Citation - WoS: 14Citation - Scopus: 20A Machine Learning Study To Enhance Project Cost Forecasting(Elsevier, 2022) Narbaev, Timur; Hazir, Oncu; Inan, TolgaIn project management it is critical to obtain accurate cost forecasts using effective methods. This study presents a Machine Learning model based on Long-Short Term Memory to forecast the project cost. The model uses the seven-dimensional feature vector, including schedule and cost performance factors and their moving averages as a predictor. Based on the cost variation patterns from the training phase, we validate the model using three hundred experiments in the testing phase. Overall, the proposed model produces more accurate cost estimates when compared to the traditional Earned Value Management index-based model. Copyright (C) 2022 The Authors.Editorial Citation - WoS: 1Citation - Scopus: 1Editorial: Optical Wave Propagation and Communication in Turbulent Media(Frontiers Media Sa, 2023) Baykal, YahyaArticle Citation - WoS: 1Citation - Scopus: 1Antenna Synthesis by Levin's Method Using a Novel Optimization Algorithm for Knot Placement(Applied Computational Electromagnetics Soc, 2023) Sener, Goker- Antenna synthesis refers to determining the antenna current distribution by evaluating the inverse Fourier integral of its radiation pattern. Since this inte-gral is highly oscillatory, Levin's method can be used for the solution, providing high accuracy. In Levin's method, the integration domain is divided into equally spaced sub-intervals, and the integrals are solved by transfer-ring them into differential equations. This article uses a new optimization algorithm to determine the location of these interval points (knots) to improve the method's accuracy. Two different antenna design examples are pre-sented to validate the accuracy and efficiency of the pro-posed method for antenna synthesis applications.Article Citation - Scopus: 9Improvement of Underlay Cooperative Cognitive Networks Bandwidth Efficiency Under Interference and Power Constraints(Ksii-kor Soc internet information, 2019) Preveze, Barbaros; Alkhayyat, Ahmed; Al-Mishmish, Hameed R. M.The definition of the bandwidth efficiency (BE) of cognitive cooperative network (CCN) is the ratio between a number of the licensed slot(s) or sub-channel(s) used by the unlicensed users to transmit a single data packet from the unlicensed transmitter to unlicensed destination, and from unlicensed relay(s) to unlicensed destination. This paper analyzes and improves the BE in the underlay CCN with a new reactive relay selection under interference and power constraints. In other words, this paper studies how unlicensed cooperative users use the licensed network slot(s) or sub-channel(s) efficiently. To this end, a reactive relay selection method named as Relay Automatic Repeat Request (RARQ) is proposed and utilized with a CCN under interference and power constraints. It is shown that the BE of CCN is higher than that of cooperative transmission (CT) due to the interference and power constraint. Furthermore, the BE of CCN is affected by the distance of the interference links which are between the unlicensed transmitter to the licensed destination and unlicensed relay to the licensed destination. In addition, the BE for multiple relays selection over a CCN under interference and power constraints is also analyzed and studied, and it is shown that the BE of CCN decreases as the number of relays increases.Article Non-Linear Eddy Current Loss and Thermal Analysis on Transformer Cover(Gazi Univ, 2019) İskender, İres; Zahedı, Mohammad ZiaHigh current conductors of transformers cause to produce losses and thermal problems in theirtank cover. Finite Difference (FD) Method (FDM) magnetic analysis is used to find out an exactestimation of the magnetic field and the losses near the bushings in the transient solution,considering the non-linear magnetic permeability of the cover plate, because FDM is moreflexible to deal with the nonlinear constitutive law and easy-to-be implemented especially in thecase of simple geometry. Finite Element Method (FEM) thermal analysis is used to determinethe plate temperature based on magnetic FD analysis, taking account non-linear heat fluxboundary condition. A calibration procedure is used between the analyses to ensure the precisionof assumptions. The reliability of the technique, confirmed by experimental and FEM results.