Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - Scopus: 6Wind Turbine Inspection With Drone: Advantages and Disadvantages(Erol Kurt, 2023-03-31) Tanrıverdi, Harun; Karakuş, Güzide; Ulukan, AhmetThe facilities on wind energy generation are increasingly finding usage areas in line with the ecologically friendly energy generation approach. One of the important activities of wind power generation facilities, which have high investment cost, low operating cost and low environmental impact is the maintenance and repair of wind turbines. A preventive maintenance approach is dominant to reduce maintenance times and eliminate lost time in wind turbines. Damage inspection of turbines has been evolved from tower crane access, rope access, camera viewing, and other applications to image with manual drones over the years. However, when these methods are evaluated within the framework of criteria such as cost, performance, occupational safety and data reliability, they are still insufficient and the need for inspection with autonomous drones arises. The advantages and disadvantages of autonomous drones used in the determination of damage in wind turbines are analyzed and the results are considered to contribute to the practitioners operating in the sector and academicians working in the field. © 2023 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 1Citation - Scopus: 8Short Term Electricity Load Forecasting: A Case Study of Electric Utility Market in Turkey(Institute of Electrical and Electronics Engineers Inc., 2015-04) Ishik, Muhammed Yasin; Göze, Tolga; Ozcan, Ihsan; Güngör, Vehbi Çağrı; Aydin, Zafer; Yasin, MuhammedWith the recent developments in energy sector, the pricing of electricity is now governed by the spot market where a variety of market mechanisms are effective. After the new legislation of market liberalization in Turkey, competition-based on hourly price has received a growing interest in the energy market, which necessitated generators and electric utility companies to add new dimensions to their scope of operation: short-term load and price forecasting. The field has several opportunities though not free from challenges. The dynamic behavior of the market price has caused the electric load to become variable and non-stationary. Furthermore, the number of nodes, in which the load must be predicted, is not constant anymore and can no longer be estimated by experts alone. In this competitive scenario, statistical forecasting methods that can automatically and accurately process thousands of data samples are essential. The purpose of this study is to demonstrate the importance of short-term load forecasting, how it has received a growing interest in Turkey and to propose an artificial neural network that can forecast the short term electricity load. Through detailed performance evaluations, we demonstrate that our forecasting method is capable of predicting the hourly load accurately. © 2017 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 3Citation - Scopus: 4Seamless Mobile Data Offloading in Heterogeneous Wireless Networks Based on IEEE 802.21 and User Experience(Institute of Electrical and Electronics Engineers Inc., 2014-04) Tüzünkan, Firat A.; Güngör, Vehbi Çağrı; Zeydan, Engin; Ileri, Ömer; Ergüt, SalihThe increase on smartphone usage has brought the burden of data traffic with it. Operators are looking for cost-effective solutions to overcome the problem of 3G infrastructure for high contention traffic scenarios. Several schemes were offered to save the moment, and they brought some extra costs including deploying femtocell or WiMax, LTE, LTE-Advanced systems along with their expensive equipment. On the other hand, operators are expanding their networks with 802.11 technologies such that they can exploit the free-band communication. Meaning the data traffic can handover between WLAN and UMTS interchangeably. By using NS-2 simulator, we implemented IEEE 802.21 WG's Media Independent Handover (MIH) module by combining with Channel Quality Indicator (CQI) values collected from user equipment (UE) and observed a recovered throughput for both medium. We found that there is a tradeoff among energy efficiency, delay tolerance and cost. Furthermore, in this study, we integrated a Quality of Experience (QoE) metric during real-time handover decision process so that with this type of collaborative solution, an operator will be unique in terms of user happiness and heterogeneous network management. © 2021 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 1Is the Smart Grid a Good Investment(Institute of Electrical and Electronics Engineers Inc., 2015-04) Onen, Ahmet; Broadwater, Robert P.Electric distribution design and operational goals include meeting customer reliability requirements at the lowest cost. Smart Grid investments have the potential for helping meet these goals, and this paper presents a series of analyses that evaluate the incremental economic benefits of smart grid automation investments. Smart Grid investments provide a number of benefits to customers. Here only benefits that can be objectively quantified in terms of economic savings are considered. Smart Grid automation investments in this work include investments in feeder efficiency, automated switches, and coordinated control of capacitor banks, voltage regulators and load tab changers. Benefits that come from these investments are improved efficiency, reduced demand, shortened storm restoration time, and improved performance during reconfiguration events. The analyses used in the evaluation are very detailed, involving hourly, quasi-steady state power flow analysis over a ten year period for calculating energy consumption and costs, and Monte Carlo simulations for six different storm types. The evaluation shows that similar to other industries, an investment in automation can be justified in terms of hard dollars. © 2017 Elsevier B.V., All rights reserved.Book Part Citation - Scopus: 54Energy Harvesting and Battery Technologies for Powering Wireless Sensor Networks(Elsevier Inc., 2016) Tuna, Gürkan; Güngör, Vehbi ÇağrıDue to the advances in wireless sensor networks (WSNs), factory and plant process automation systems are being reinvented. WSN-based industrial applications often cost much less than wired networks in both the short and long terms; automation engineers are empowering existing solutions with the new capabilities of WSNs. On the other hand, since industrial wireless sensor networks (IWSNs) consist of thousands of nodes, the problem of powering the nodes is critical. Power to the nodes is usually provided through primary batteries and this necessitates replacement when the batteries are depleted. However, the replacement may not be cost-effective or even feasible in most industrial applications.Though advancements in integrated circuit technologies help in saving more energy by leading to lower energy consumption levels, they do not eliminate the use of battery power. In this regard, energy harvesting technologies play a key role in extending the battery lifetime of the nodes. Wireless sensor nodes within industrial plants can operate from energy harvested from available energy sources such as heat, mechanical motion or vibration, indoor lighting, electromagnetic fields, and air flow. In this chapter, a review of existing energy storage technologies and various energy-harvesting techniques is given. The chapter then discusses open research issues in these topics. © 2020 Elsevier B.V., All rights reserved.Conference Object Efficiency and Cost Evaluation of Distribution Systems Based on Multiple Time Points(Institute of Electrical and Electronics Engineers Inc., 2015-07) Onen, AhmetPhase balancing can offer planning engineers a lowcost means of reducing operating costs, improving efficiency in electric power systems. In general, utilities make phase balancing based on peak load by thinking that is the worst case scenario, but every time is not the case. In this paper, time varying phase balancing algorithm is proposed to investigate the effect of hourly phase balancing for all year (8760 hour for a year) and also evaluate system efficiency and cost saving for all hours. Additionally, it is important for the planning engineers to estimate losses accurately to make phase moves, and the peak load does not always provide the most efficient phase moves among the hours in year. In this paper, there different scenarios will be compared; base case, phase balancing based on peak load, and hourly time varying phase balancing. These scenarios will be compared based on loss reduction, and cost saving with Locational Marginal Price (LMP) to provide the planning engineers ideas about effective power system planning. © 2017 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 2ATGRUVAE: Reducing Noise and Improving Forecasting Performance in Stock Data(Institute of Electrical and Electronics Engineers Inc., 2024-10-26) Akkaş, Huseyin; Kolukisa, Burak; Bakir-Güngör, BurcuNowadays, to maximize their income, investors and researchers try to predict the future prices of stocks in the market using artificial intelligence algorithms. However, noise in stock price fluctuations negatively a ffects t he accuracy of the forecasts. To this end, Attention Based Variational Autoencoders with Gated Recurrent Units (ATGRUVAE) method is developed to remove the noise in stock price fluctuations a nd compared with variational, basic and noise removing autoencoders. Exper-iments are conducted using historical stock prices of well-known companies such as Apple, Google and Amazon and 9 different indicator values derived from these stock prices. The noise cleaned stocks are then trained and tested on Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM) and Linear Regression (LR) models. The results show that the proposed ATGRUVAE model outperforms all three models and demonstrates its ability to capture complex patterns in stock market data. © 2025 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 2Beyin Dalgalari ve Baş Hareketiyle Gerçek Zamanli Robotik Araba Kontrolü(Institute of Electrical and Electronics Engineers Inc., 2018-11) Oztürk, Nedime; Yilmaz, Bulent; Onver, Ahmet YasinEmotiv Epoc Headset is a portable and low-cost device. In this study, Emotiv Epoc headset was used in order to obtain real-time gyro and EEG signals. The aim of this study was to control a robotic car in real-time by using head movement and opening and closing of the eyes. The maximum and minimum amplitude of the gyro signal, and the ratios of the beta waves of O1 and O2 channel to alpha waves of the same channels were used as threshold values. These threshold values were used to determine the direction of the robotic car. Because of its low-cost and easy implementation, Arduino Uno was used to manage the robotic car. This study has shown that brain waves and head movements can control a device in real time. This system has the potential to be used in neurofeedback and brain-computer interface applications. © 2019 Elsevier B.V., All rights reserved.