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Öğe Assessment of machine learning, time series, response surface methodology and empirical models in prediction of global solar radiation(Elsevier Sci Ltd, 2020) Gurel, Ali Etem; Agbulut, Umit; Bicen, YunusSolar radiation (SR) knowledge plays a vital role in the design, modelling, and operation of solar energy conversion systems and future energy investment policies of the governments. However, these data are not measured for all regions due to the non-availability of SR measurement equipment at the weather stations. Therefore, SR has to be accurately predicted using various prediction models. In this research, four models from different classes are being used to predict monthly average daily global SR data. The models used in this study are based on a machine-learning algorithm (feed-forward neural network), empirical models (3 Angstrom-type models), time series (Holt-Winters), and mathematical model (RSM). As the prediction locations, four provinces (Ankara, Karaman, Kilis, and Sirnak) in Turkey are selected. The dataset including pressure, relative humidity, wind speed, ambient temperature, and sunshine duration is supplied from the Turkish State Meteorological Service and it covers the years 2008-2018. In the study, monthly average daily global SR data for the year 2018 is being predicted, and the performance success of the models is discussed in terms of the following benchmarks R-2, MBE, RMSE, MAPE, and t-stat. In the results, R-2 value for all models is varying between 0.952 and 0.993 and MAPE and RMSE value for all models is smaller than 10% and 2 MJ/m(2)-day, respectively. Evaluation in terms of t-stat value, no models exceed the t-critic limit. Considering all the models together, ANN has presented the best results with an average R-2, MBE, RMSE, MAPE, and t-stat of 0.9911, 0.1323 MJ/m(2)-day, 0.78 MJ/m(2)-day, 4.9263%, and 0.582, respectively. Then Holt-Winters, RSM, and empirical models closely followed it, respectively. (C) 2020 Elsevier Ltd. All rights reserved.Öğe Çimentosuz Kompozitlerde Tahribatlı ve Tahribatsız Testlerin Elektrisksel Direnç ile İlişkilendirilmesi(Düzce Üniversitesi, 2023) Yurt, Ümit; Kır, Barış; Bicen, Yunusİnşaat sektöründe, malzeme özelliklerini belirlemek için basınç dayanımı, yoğunluk, su emme ve prozite gibi testler sıklıkla kullanılmaktadır. Genel olarak deneysel çalışmalar tahribatlı ve tahribatsız muayene yöntemleri olarak iki kategoriye ayrılır. Ortak görüşe göre, tahribatlı muayene yöntemleri tahribatsız muayene yöntemlerine göre daha güvenilir sonuçlar üretir. Ancak tahribatlı testlerde numunelerin tekrar kullanılması mümkün olmamakta ve inşaat süreci tamamlanan binadan numune alınmasında zorluklar yaşanmaktadır. Ayrıca tahribatlı testlerin deneysel olarak uygulanması zaman ve maliyet açısından dezavantajlar doğurmaktadır. Bu çalışma kapsamında, son yıllarda sürdürülebilir çevre dostu kompozit yapı malzemeleri olarak ilgi gören alkali aktivasyonlu beton kompozitler üzerinde tahribatlı ve tahribatsız deneyler yapılmıştır. Basınç dayanımı, yoğunluk, prozite, su emme vb. geleneksel test yöntemleri elektriksel direnç ölçümleriyle ilişkilendirilmiştir. MEGGER ekipmanı ile elektriksel ölçümler alınmış ve direnç değerleri diğer parametrelerle doğrudan ilişkilendirilmiştir. Elde edilen olumlu sonuçlar, inşaat sektöründe kullanılan malzemelerin numune boyutu veya lokalizasyondan bağımsız olarak önerilen yöntemle değerlendirilebileceğini göstermektedir.Öğe Dielectric Resonator Antenna-Based Sensing Technology for Enhanced Insulation Oil Diagnostics(Wiley-V C H Verlag Gmbh, 2025) Duman, Mehmet; Bicen, YunusThe insulating oil in transformers plays a critical role both as a coolant supporting the paper insulation and as an element protecting the dielectric properties of the system. Serious failures may result from changes in the oil's dielectric characteristics brought on by the presence of water and other contaminants. This study assesses the insulation condition of transformer oils by designing and simulating three different dielectric resonator antennas (DRA) in the CST Design Environment. An attempt is made to find the best design by analyzing the effect of variations in dielectric constant on various resonator antenna designs. The resonant frequency range of 1.5-3GHz$1.5 {-}3\;GHz$ and the RT5880 dielectric substrate are chosen. Simulations are carried out to illustrate situations where the epsilon r${\varepsilon _r}$ value of the oil varies between 1$\hskip.001pt 1$ and 5$\hskip.001pt 5$. In general, it is found that as the dielectric constant of the oil (epsilon r${\varepsilon _r}$) increases, the resonant frequency (fr${f_r}$) and the S11${S_{11}}$ parameter decrease. Single DRA-A single SMA port is advised for low-cost and straightforward applications, but Dual DRA can be chosen for investigations needing high sensitivity and double-check. The analysis allows the best approach to be selected based on the requirements of the application by highlighting the advantages and disadvantages of different designs.Öğe Dynamics of liquid and solid dielectrics: Extended lifespan with online dehydration system(Elsevier, 2025) Bicen, YunusThe life of the insulation in oil-immersed transformers is greatly shortened over time by the rise in moisture content if dehydration is not carried out when necessary. This study demonstrates the superior aspects of the online dehydration system in hermetically sealed and free-breathing transformers using Kraft and thermally upgraded Kraft paper as the main insulation material. Twenty separate scenarios have been investigated, each with its own unique combination of insulation type, temperature, moisture, and oxygen level. The results demonstrate that using online dehydration systems can significantly increase life expectancy. The insulation life of hermetically sealed transformers, for instance, is increased by 1.9 times at 110 degrees C and further at lower temperatures. Online methods outperform conventional dehydration systems in terms of prolonging the insulation's lifespan. Theoretically, offline (traditional) dehydration techniques can extend insulation life by 2.5 times, however, online dehydration systems can improve this rate by up to 7.43 times. Dehydration systems have been shown to significantly increase insulating lifespan, particularly in transformers operating at low temperatures. Also, thermally upgraded paper is more sensitive to dehydration processes than Kraft paper. Given all of these results, online dehydration technologies have the potential to significantly improve transformer durability and reliability.Öğe Experimental determination of electrical and thermo-physical characteristics of dielectric nanofluids based on volume fraction change(Elsevier Science Sa, 2023) Karatas, Mehmet; Bicen, YunusDielectric insulating fluids perform critical tasks such as electrical insulation and cooling functions in power system equipment. Improving the thermal properties of insulating fluids extends the service life of power equipment, while improving their dielectric properties ensures a reliable and safe electricity supply. Therefore, studies on enhancing the thermal and dielectric qualities of dielectric fluids using nanoparticles have become more popular in recent years. In this study, the dielectric and thermo-physical properties of mineral oil-based SiO2 nanoparticle suspensions, namely nanofluids, have been investigated. An approximately 25.6% enhance-ment in AC breakdown voltage level has been obtained at a 0.05% critical volume fraction. It has been noted that the level of the AC breakdown voltage decreases when the critical volume fraction is exceeded. The thermal conductivity of the prepared nanofluid has changed logarithmically in the positive direction according to the rising number of nanoparticles per unit volume. Thermal conductivity has increased by around 8.55% for the critical volume fraction value, whereas thermal diffusivity has increased by approximately 22%. Similarly, when the number of particles in the nanofluid rises, the viscosity increases nonlinearly. The viscosity increase, which is undesirable for heat transfer, has been determined to be around 10.64% for the crucial volume fraction. These findings indicate that dielectric nanofluids hold significant potential for the future. The SEM analysis, on the other hand, explains the difficulties of assuring the long-term stability of nanofluids in the volume fraction with the highest AC dielectric breakdown voltage.Öğe Measurements and performance evaluations of natural ester and mineral oil-immersed identical transformers(Elsevier Sci Ltd, 2021) Cilliyuz, Yusuf; Bicen, Yunus; Aras, Faruk; Aydugan, GuzideThe use of natural esters as an insulating liquid has become popular since the early 2000s. Studies in the literature emphasize the superiority of natural esters as compared to mineral oils. In these studies, the prominent properties of natural esters are presented as being environmentally friendly, safe, and delaying the aging of cellulosic insulation material. Although there is no doubt in terms of their characteristics, such as being environmentally and safe, exaggerated comments are made about the delay of aging of the paper material used in the insulation of transformer windings. This is because comparative experimental applications on mineral oil and natural esters are carried out under artificial and equal conditions provided in the laboratory environment. Whereas, performing these experiments on identical transformers will give more realistic results. In this study, two identical transformers were designed and equipped with precision fiber optic temperature sensors. Temperature differences that vary depending on the load between high voltage and low voltage windings were measured with a high degree of accuracy for both identical transformers. Besides these measurements, physical and chemical changes were analyzed on samples taken from insulation liquids. It was observed that the physical and chemical properties of the insulation liquids directly affect the operating performance of the transformers. Thanks to the differences in viscosity of insulating liquids, the heat dissipation due to losses in the windings were different for both transformers. Both heat distribution and temperature differences in the windings varied depending on the loading factors. Considering all these factors together, comprehensively evaluations were made on the aging rate of cellulosic insulation and the service life of the transformers.Öğe Mineral oils modified with CdSeTe QDs for improved stability and dielectric performance in high-voltage applications(Springer, 2025) Bicen, Yunus; Elibol, Erdem; Demirci, TunaThis study explored the application of CdSeTe quantum dots (QDs) in mineral oils for high-voltage applications through a comprehensive approach. CdSeTe QDs were synthesized using an organometallic method and added to mineral oil at concentrations of 1 mg/L (C1), 5 mg/L (C2), and 10 mg/L (C3). The samples' stability condition was monitored for a long period, and physicochemical tests were performed. Experimental results show that QD-modified oils have enhanced electrical properties compared to the base oil. The breakdown voltage was in the range of 17 to 23 kV for the base oil, while the breakdown voltage was in the range of 20 to 39 kV for the QD-modified (C2) insulating fluid sample. Throughout the 25-day monitoring period, the QDs were found to be properly dispersed in oil and free of aggregation in all samples. Values such as density and viscosity remained fairly constant due to the relatively low concentration ratio. However, an increase in total acid number was observed with increasing concentration. These results imply that QD-enhanced insulation oils may have applications in high-voltage applications in the future. The main innovation of this study lies in demonstrating that CdSeTe QDs can significantly enhance the dielectric strength of mineral oils while maintaining their essential physicochemical properties, offering a novel approach for improving insulation performance in high-voltage applications.Öğe Nanoparticle-enhanced dielectric oils for improved electrical insulation: Comparison of MgO, Al2O3, and SiO2-based dielectric nanofluids(Wiley, 2025) Karatas, Mehmet; Bicen, YunusThis study provides comprehensive and quantitative assessments of the electrical insulation, viscosity, thermal conductivity, flash point, acidity, and stability of dielectric nanofluids. In the experiment, naphthenic mineral oil was chosen as the base fluid. MgO, Al2O3, and SiO2 were preferred as nanoparticles. In the dielectric breakdown voltage (BDV) tests performed, increased values were observed at certain concentrations for each nanofluid, with the highest value in the SiO2-based nanofluid being 83.47 kV at a concentration rate of 0.05 g/L. Adding nanoparticles to the base oil increased the viscosity of all suspensions. Except for MgO-based dielectric nanofluid, the flash points of other nanofluids increased as compared to pure oil. Total acid number (TAN) values, on the other hand, increased for SiO2- and Al2O3-based nanofluids but decreased for MgO-based nanofluids. However, all values are quite below the standard limit of 0.25 mgKOH/g. The percentage transmittance values calculated from the ultraviolet and visible light (UV-vis) spectrophotometry results differed for each nanofluid. However, they were all lower than the base oil. In general, the results indicate that the use of dielectric nanofluids in electrical systems will be beneficial, provided that the problem of long-term stabilisation is solved.Öğe Numerical analysis and application of electric field grading device for metal-enclosed switchgear(Springer International Publishing Ag, 2021) Arslan, Serdal; Bicen, Yunus; Binarbasi, OmurElectric field grading devices have great importance for both the electric power transmission and distribution systems. This paper presents an improved electric field grading device used in the medium voltage metal-enclosed switchgear. The solutions have been carried out by using Ansys Maxwell 3D software. The structure of two electrodes designed as cylindrical and elliptical have been compared to determine the electric field grading device to be used in practice. The transient and steady-state analyses have been performed in both designs. The field grading device manufactured for the metal-enclosed switchgear has been tested according to IEC standards in a high voltage laboratory environment. This study revealed that the newly designed field-grading device can be used in the metal-enclosed switchgear more safely. It also encourages researchers to optimize the electric field distribution using different geometric structures and to create running conditions in smaller indoor environments.Öğe Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison(Pergamon-Elsevier Science Ltd, 2021) Agbulut, Umit; Gurel, Ali Etem; Bicen, YunusThe prediction of global solar radiation for the regions is of great importance in terms of giving directions of solar energy conversion systems (design, modeling, and operation), selection of proper regions, and even future investment policies of the decision-makers. With this viewpoint, the objective of this paper is to predict daily global solar radiation data of four provinces (Kirklareli, Tokat, Nevsehir and Karaman) which have different solar radiation distribution in Turkey. In the study, four different machine learning algorithms (support vector machine (SVM), artificial neural network (ANN), kernel and nearest-neighbor (k-NN), and deep learning (DL)) are used. In the training of these algorithms, daily minimum and maximum ambient temperature, cloud cover, daily extraterrestrial solar radiation, day length and solar radiation of these provinces are used. The data is supplied from the Turkish State Meteorological Service and cover the last two years (01.01.2018-31.12.2019). To decide on the success of these algorithms, seven different statistical metrics (R-2, RMSE, rRMSE, MBE, MABE, t-stat, and MAPE) are discussed in the study. The results shows that R2, MABE, and RMSE values of all algorithms are ranging from 0.855 to 0.936, from 1.870 to 2.328 MJ/m(2), from 2.273 to 2.820 MJ/m(2), respectively. At all cases, k-NN exhibited the worst result in terms of R-2, RMSE, and MABE metrics. Of all the models, DL was the only model that exceeded the t-critic value. In conclusion, the present paper is reporting that all machine learning algorithms tested in this study can be used in the prediction of daily global solar radiation data with a high accuracy; however, the ANN algorithm is the best fitting algorithm among all algorithms. Then it is followed by DL, SVM and k-NN, respectively.Öğe Smart asset management system for power transformers coupled with online and offline monitoring technologies(Pergamon-Elsevier Science Ltd, 2023) Bicen, Yunus; Aras, FarukPredictive maintenance strategies have gained popularity in recent years due to the advantages they provide over traditional maintenance strategies. Online monitoring technologies are critical for implementing predictive maintenance strategies. However, in some cases, the information generated by online systems may not be accurate and may need to be verified with offline monitoring technologies. In this study, a fault-sensitive matrix-based smart asset management system that is compatible with both online and offline technologies has been developed for power transformers. The developed system has the ability to assess multi-input parameters simultaneously and holistically. Because of the system's matrix structure, having a large number of input parameters or expanding them later is not an issue. Furthermore, the algorithms that will evaluate the input parameters are independent and distinct from one another. Because of its compatibility with the data acquisition card and its design options for the user interface, LabVIEW has been chosen for the system's development. The functionality of the system has been tested by deliberately generating faults in a test cell. While the high-resolution sensor data obtained and the calculated results are displayed on the interface, the failure probabilities are evaluated and displayed in a separate window. Intentionally generated faults have been diagnosed with high accuracy after going through the online monitoring and offline verification processes.
