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Öğe A Consistent Power Management System Design for Solar and Wind Energy-Based Residential Applications(Institute of Electrical and Electronics Engineers Inc., 2019) Esen, M.; Bayrak, Gökay; Cakmak, O.; Celikdemir, S.; Ozdemir, M.The solar and wind energy-based systems are directly dependent on the weather conditions for power generating. Thus a reliable system that is not affected by environmental conditions is required for residential applications. This study presents designing a consistent power management system (PMS) for solar and wind energy-based residential applications to overcome this problem. The proposed PMS controls a hybrid power generator (HPG) system consisting of a photovoltaic (PV) array and a wind turbine to supply consistent energy to the residential loads without any energy interruption in real-time. The designed PMS checks the demand side power and provides the PV array power to the HPG system in the condition of sufficient solar energy. Unless the PV array does not supply the desired power, the demand side power is supplied by fed by a permanent magnet synchronous generator (PMSG)-based wind turbine and a battery. The required energy is supplied from the grid, in case, the power supplied by the wind turbine and the PV array does not meet the demand. The developed PMS measures the PV panel voltage, battery voltage, and inverter's output voltage in real time and controls the relay circuits by evaluating these electrical parameters. The experimental results obtained from the developed HPG system verify that the proposed PMS is reliable for residential applications, easily implemented, practical, and presents a low-cost solution to the subject. © 2019 IEEE.Öğe A Deep Learning-Based Islanding Detection Approach by Considering the Load Demand of DGs Under Different Grid Conditions(Springer Science and Business Media Deutschland GmbH, 2023) Bayrak, Gökay; Yılmaz, AlperIslanding detection is a very important issue in the integration of renewable energy systems with the grid. In recent years, especially artificial intelligence and deep learning-based islanding detection methods have come to the fore in terms of providing reliable power quality. In this study, a deep learning-based islanding detection approach by considering power quality and load demand problems is proposed. It is aimed to effectively detect the islanding condition which occurs as a result of unintentional disconnection of distributed generation (DG) systems from the grid. In the proposed approach, a deep learning-based islanding detection method is developed, taking into account the faults and power quality events occurring on the load side like considering asynchronous motor startup, capacitor switching, etc., conditions that are not possible to easily detect by conventional islanding detection methods. With the developed method, it is seen that the islanding event can be distinguished from the power quality events that occur on the grid, even under noisy signals. In this way, the power quality of the grid is increased and the performance of the DG in dynamic load behavior is developed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Öğe A Demand Side Management Controller Configuration for Interleaved DC-DC Converters Applicable for Renewable Energy Sources(Wiley, 2021) Ertekin, Davut; Bayrak, Gökay; Subramaniam, UmashankarIn Micro-grid applications, accuracy and sensitivity of the Demand Side Management (DSM) process decrease when the load impedance changes. In this study, the impact of the DSM is analyzed and the interleaved structure is presented for DC-DC converter blocks equipped with adaptive PI controllers. This approach reinforces a same voltage source that can be a serial and parallel connection of Photovoltaic (PV) panels in different power rates as the input voltage source to enhance the voltage to the micro-grid DC level and is modeling the power transmission in Renewable Energy Sources (RESs) that they produce limited amounts of power. For the voltage droop problem, the Power-Voltage (P-V) approach is selected. Since the resistive loads are considered in this study, this approach can control DC currents based and depending on the DC voltages in DC micro-grid applications. For per controller block, different values of the gain coefficients are tested and the optimal droop coefficients are presented. All simulations have been done in MATLAB/SIMULINK and a prototype by power around 1kW is tested. The results of the hardware implementation confirm the theoretical and simulation outcomes.Öğe A low-cost power management system design for residential hydrogen & solar energy based power plants(Pergamon-Elsevier Science Ltd, 2016) Bayrak, Zehra Ural; Bayrak, Gökay; Ozdemir, Mahmut Temel; Gencoglu, Muhsin Tunay; Cebeci, MehmetThis study focuses on developing a low-cost power management system for residential solar hydrogen power plants. The proposed power management system is designed as a hybrid control system consisting of a microcontroller and a Labview data acquisition card. Most of the controllers have some boundaries for power management, and providing a practical solution for hybrid power plants has some limitations. The proposed controller checks the total energy demand of the hybrid power plant in real time and operates the solar/hydrogen energy based power plant for the local load. The implemented electronic control card monitors the hybrid system and operates the related switches to select the proper energy source for the local load. The proposed real-time management system also provides a low-cost power management for the residential power plants, and the experimental results prove that the developed hybrid power management system is easy to implement and is suitable for residential applications. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Öğe A new artificial intelligence-based demand side management method for EV charging stations(Elsevier, 2024) Bayrak, Gökay; Meral, HasanToday, the rapid spread of the use of electric vehicles (EVs), and accordingly EV charging stations will lead to an imbalance between generation and consumption resources. While waiting for the determination of the appropriate charging time and the determination of the suitable charge amount at the EV charging station, the most effective load management should be carried out by obtaining information from the user, including the current charging capacity, the next journey distance, the time the vehicle can stay connected to the charging station, and whether the vehicle has V2G support. In this study, a new approach is based on the ensemble learning classifier method that performs higher performance classification by bringing together the results obtained from multiple classifiers in a system with more than one EV charging station; By evaluating parameters, the system for the charging station that should be used and for how long is decided by the ensemble learning classifier structure. A scenario of the proposed intelligent demand side management (DSM) system for charging stations with multiple charging units is shown in Figure 2.1. The results show that the proposed method can perform DSM with high accuracy of 99.1% for Case-1 and 98.4% for Case-2. © 2024 Elsevier Inc. All rights reserved.Öğe A new signal processing-based islanding detection method using pyramidal algorithm with undecimated wavelet transform for distributed generators of hydrogen energy(PERGAMON-ELSEVIER SCIENCE LTD, 2022) Yılmaz, Alper; Bayrak, GökayMachine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match.(c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.Öğe A Novel Mathematical Analysis for Electrical Specifications of Step-up Converter(Univ Osijek, Tech Fac, 2019) Ghaderi, Davood; Bayrak, GökayThis study presents a unique comprehensive mathematical model for both transient and steady states of the step-up power converter in order to structure physical aspects evaluations. The main disadvantage of different existence mathematical models such as impedance, small signal analysis and steady space average models is that they use numerical analysis methods or simplification solutions that lead to approximate analysis. Therefore, the physical behaviours of the system such as inductor current, output voltage and physical effects of components will not be accurately predictable. This study presents very accurate equations and all aspects of the structure are predictable. In our research, this issue is investigated in Laplace and Z domains using the output-to-input transfer function calculations, and the effect of converter circuit elements is assessed using equations obtained. For extracting the transfer function, initial values are calculated in the Z domain and based on the final value theorem, converter output voltage and input current have been calculated. Effects of converter components on capacitor voltage and input current ripples have been analysed and reported. In the final step, results of the theoretical analysis were confirmed by simulation results obtained in MATLAB/SIMULINK environment and implementation on a prototype in laboratory scales.Öğe A Novel Step-Up Power Converter Configuration for Solar Energy Application(Kaunas Univ Technology, 2019) Ghaderi, Davood; Bayrak, GökayRenewable Energy Sources (RES) including full cells, wind turbines, and photovoltaic panels, widely are spreading. Among all the renewable energy sources, solar power generation system tops the list. The first choice is the boost converter when the voltage step-up is the issue. But the most important subject is applying an efficient structure with high gain, cheap and quick controller circuit. Our proposed cascaded boost converter is one of such converters which consists of several cheap components such as diode, inductor, capacitor and power switch, which has same switching frequency and phase shift in comparison with conventional boost converters. In comparison with the classic cascaded boost converter, the voltage gain for the proposed structure is very high and by forming a preamplifier layer, for a duty cycle of 80 % by adding only two diodes, one inductor, and one capacitor for the second block, voltage gain is increased by 5 times compared to the classic boost converter. The proposed method provides the increased output voltage along with the duty cycle. The projected strategy has been verified with the help of Matlab/Simulink. Also, a hardware implementation of the proposed converter has been done around 200 W by applying a Jiangyin HR-200W-24V type solar panel.Öğe A real-time energy management system design for a developed pv-based distributed generator considering the grid code requirements in Turkey(MDPI, 2021) Bayrak, Gökay; Ertekin, Davut; Alhelou H.H.; Siano P.Each country must determine the Grid Code conditions and apply these criteria to integrate distributed generation (DG) systems into the existing electricity grid and to ensure a stable power system. Thus, experimental studies are required to provide an effective, national, and specific Grid Code. In this study, the Turkish Grid Code’s electrical criteria were examined, and the application of these criteria was carried out on a developed PV-based DG. A real-time energy management system (RTEMS) was proposed in the study. Electrical parameters on the developed DG were monitored in real-time by considering IEEE 1547, IEEE 929–2000, and Turkey’s electrical criteria. A practical grid code study was firstly investigated in detail about the Turkish Grid Code by a developed real-time monitoring-control and protection system. The proposed RTEMS method in the study is implemented as an inverter-resident system; thus, it provides advantages over many energy management systems embedded in the inverter. The degradation in power quality and non-detection zone (NDZ) problems encountered in active and passive island mode detection methods developed embedded in the inverter are eliminated in the proposed method. With the RTEMS method, where under and over-voltage, under and over voltage frequency, and unintentional island mode events can be detected in real-time, both the existing grid-code requirements are met, and the existing power quality and NDZ problem is eliminated with the recommended inverter-independent RTEMS method.Öğe A real-time UWT-based intelligent fault detection method for PV-based microgrids(Elsevier Science Sa, 2019) Yılmaz, Alper; Bayrak, GökayIn this paper, a new un-decimated wavelet transform (UWT)-based fault detection method is proposed to overcome the limitations of WT-based methods in real-time applications. For the first time, UWT method is used to detect power quality disturbances (PQD) in microgrids in real time. UWT reduces the oscillations and noise in the signal and also is useful for selecting threshold values. This method is implemented by using only the voltage signal to detect the PQDs automatically for a PV-based microgrid. The voltage sag/swell, and interruption faults are evaluated in the experimental study by considering the duration and event amplitude of the PQD signal. High accuracy is also provided for detecting PQDs without using any noise filtering process. The results indicate that the proposed technique has a wide application area, fast fault detection time, and it is reliable for microgrids.Öğe A Smart Energy Management System Design for Residential Power Plants(Gazi Univ, 2017) Bayrak, Zehra Ural; Bayrak, GökayIn this study, a solar-hydrogen hybrid power generation system is modeled by developing a smart energy management system (EMS) to sustain a continuous power flow for a local load in a constituted residential hybrid power plant. The developed EMS checks the total energy demand of the hybrid power plant and operates the solar power plant or the hydrogen energy based power plant to provide a sustainable power for the local load. A new control card is developed and a real-time EMS is performed in Labview for controlling and monitoring the hybrid system. The implemented electronic control card manages the active power flow of the hybrid system to provide a sustainable power demand of the local load. The current energy demand of the residential power plants can be viable in the lack of the sun or hydrogen, thanks to the developed EMS. The proposed EMS is modeled in Matlab/Simulink, and verified by the experimental study. The experimental results show that the proposed EMS provides a sustainable energy infrastructure for the residential hybrid power plants, and it is also easy implemented and suitable for residential real system applications.Öğe An improved automated PQD classification method for distributed generators with hybrid SVM-based approach using un-decimated wavelet transform(Elsevier, 2021) Yılmaz, Alper; Kucuker, Ahmet; Bayrak, Gökay; Ertekin, Davut; Shafie-Khah, Miadreza; Guerrero, Josep M.Artificial intelligence (AI) approaches are usually coupled with the wavelet transform (WT) for feature extraction to classify the power quality disturbances (PQDs). Therefore, selecting a useful WT-based signal processing approach is required for a reliable classification, especially in real-time applications. In this study, a new hybrid, un-decimated wavelet-transform (UWT)-based feature extraction method using a support vector machine (SVM) with a "' a trous" algorithm is proposed to classify PQDs in distributed generators (DGs). The proposed method was performed in a real-time application of a DG system to classify PQDs. The derived features were tested on five different machine learning (ML) models by determining the most appropriate classification technique for the proposed UWT-based feature extraction method. An experimental DG system is constituted in the laboratory using a LabVIEW environment, and the proposed method is tested under different grid conditions. Besides, other well-known and studied conventional ML methods were also tested under 25 dB, 30 dB, and 40 dB noise and compared to the developed method. The experimental and simulation results show that the features extracted with the proposed UWT-based method provide much more successful results in classification than the existing wavelet methods in the literature. Furthermore, the proposed method's noise sensitivity performance is much better than other conventional wavelet algorithms, especially in real-time applications.Öğe AN IMPROVED CWT-BASED ISLANDING DETECTION METHOD FOR A DEVELOPED MICROGRID IN REAL-TIME(Muğla Sıtkı Koçman Üniversitesi, 2020) Yılmaz, Alper; Bayrak, GökayThe island mode operation problem is a significant event of deterioration in a power system, and this fault must be detected in the fastest and most accurate way for the reliable operation of the microgrid structure. Recently, numerous islanding detection methods based on signal processing have been proposed in the literature. In this study, an improved, continuous wavelet transform (CWT)-based islanding detection method is proposed for microgrids. Island mode conditions are investigated in the developed PV-based microgrid connected to a low voltage grid. The proposed method uses only the voltage signal on the point of common coupling (PCC). A series of discrete values are selected for scales and shifts of continuous wavelets and then CWT is applied for PCC voltage. In this way, the computational load is minimized. This method has many advantages comparing to conventional methods and has been tested in real-time for a PV-based microgrid prototype. The results show that the developed CWT-based islanding detection method can detect different types of island modes in the developed microgrid. Besides, the islanding detection time of the proposed method varies between 105-110 ms in any island mode operations, and it is faster than the conventional detection methods. None detection zone (NDZ) is also almost zero in the proposed method. Thus, the CWT-based islanding detection method provides both a reliable NDZ and a short detection time for microgrid applications.Öğe An improved step-up converter with a developed real-time fuzzy-based MPPT controller for PV-based residential applications(Wiley, 2019) Bayrak, Gökay; Ghaderi, DavoodResidential photovoltaic power plants (RPVPPs) have a wide area of utilization in PV applications. Thus, low-voltage penetration of these plants to the grid is a crucial issue for the high efficient operation of a photovoltaic (PV) system. The conventional maximum power point tracking (MPPT) methods have some drawbacks. Thus, intelligent MPPT methods are proposed in the literature to achieve these problems. This paper presents a new real-time fuzzy-based MPPT controller design for a new high gain transformer-less and single-switched power boost converter operating with different duty cycles for PV-based residential applications. The proposed structure can ensure an enhancement in voltage gain by eight times for duty cycle of 50% that is much more effective than a conventional boost converter that can gain the input voltage to two times at the output of the converter. The higher amounts of the DC voltage gain are possible by adding the novel and efficient switched capacitor (SC) blocks. The proposed control method uses designed fuzzy-based rules to control the duty cycle of the implemented power boost converter in the real-time domain. A data acquisition card is used to control the duty cycle and monitoring the PV system. The proposed fuzzy-based algorithm is performed in advanced LABVIEW software. The experimental results show that the developed fuzzy-based controller is independent of the circuit parameters and has a more reliable response for changing environmental conditions. The accuracy of the applied fuzzy-based MPPT method in the tested PV system varies between 95.8% and 99.6%.Öğe Analysis of Cutter Wear Conditions in CNC Machine Tools with Wavelet Packet Transform(Institute of Electrical and Electronics Engineers Inc., 2023) Göllü, Mehmet; Yılmaz, Alper; Bayrak, GökayCutter wear and breakages in CNC machines lead to financial losses ranging from 5% to 10% of annual revenue for companies. Especially in the production of automotive and defense industry products, there are high expectations for precision and uninterrupted production within the scope of industry 4.0. Therefore, minimizing cutter breakages and monitoring their conditions in CNC machines is of great importance. In recent years, research using smart methods to solve these problems has increased. In this study, the current of the servo motor operating in a CNC machine is measured during its operation. The obtained current signals are decomposed using the wavelet packet transform (WPT), and an attempt is made to determine the status of the cutter on the relevant axis. The use of WPT is proposed to ensure high noise immunity. The developed system aims to provide operators with real-time notifications about the condition of cutters, enabling rapid intervention. Thus, the goal is to reduce additional costs resulting from cutter breakages and minimize downtime that negatively affects production continuity. The results obtained using WPT are expected to make a significant contribution to increasing efficiency and minimizing errors in the metalworking industry. © 2023 IEEE.Öğe Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants(2019) Bayrak, Gökay; Yılmaz, AlperPower Quality problems, which have become an important consumer issue in recent years, are defined as changes in voltage, current, or frequency in the power system. Among the factors affecting energy quality in grid-connected PV systems are island mode operation, current and voltage harmonics, transients, flicker, interruption, DC offset, notches, frequency changes, voltage sag/swell, voltage imbalances in the system and power factor. Several transmission and distribution losses consist of both the consumers and the generators sides because of the power quality problems. The integration of PV power plants to the main grid will cause several power quality problems so a reliable operation of the grid with PV power plants is a significant issue for a distributed generation. Thus, the first step in preparing a reliable algorithm for detecting power quality events occurring in the current grid is to model a power system in which power quality impairments can be analyzed. In this study, the power quality disturbances that occur in the low-voltage grid that is fed through both the main grid and the gridconnected PV system are modeled and investigated. Developed electric power distribution model includes simulation of voltage sags caused by the three-phase fault, transformer energization and asynchronous motor switching, voltage swells caused by the three-phase fault, transients due to large capacitor bank switching, harmonics and notches caused by the load connected via the power converter. Examination of the power quality disturbances with simulation clearly revealed the resulting waveforms, the response of the electrical power system to the fault conditions. Another advantage of the realized study is that the developed model can be used to measure the performance of the PV connected distributed generation system in fault detection and classification studies.Öğe DEEP LEARNING-BASED BINARY CLASSIFICATION OF ISLANDING CONDITIONS IN A HYDROGEN ENERGY-BASED DISTRIBUTED GENERATION SYSTEM(International Association for Hydrogen Energy, IAHE, 2022) Yılmaz, Alper; Bayrak, GökayThis paper presents a deep long short-term memory (DLSTM) with a binary-label classifier method proposed for binary classification of islanding and non-islanding events in a hydrogen energy-based distributed generator (DG) system. Deep learning (DL)-based method eliminated the lack of performance of conventional intelligent islanding detection methods that uses feature extraction, feature selection, and event classification. Besides, the proposed method has provided the need for a processing-intensive filtering process to reduce noise from the signal. The proposed islanding detection method has a 98.33% accuracy rate under no-noise, and 97.66% high-level noise conditions. In the proposed method, the non-detection zone (NDZ) is almost zero, and the detection time is under the defined IEEE 929-2000 standards. Experimental and simulative data results show that the LSTM-based islanding detection method outperforms the algorithms in recent studies in terms of noise immunity and accuracy. © 2022 Proceedings of WHEC 2022 - 23rd World Hydrogen Energy Conference: Bridging Continents by H2. All rights reserved.Öğe Design and experimental validation of an artificial neural network-SVPWM controller for a novel micro grid-tied fuel cell-based 3-phase boost inverter(Elsevier Ltd, 2024) Baltacı, Kübra; Ertekin, Davut; Bayrak, GökayA grid-tied fuel cell (FC) system demands efficient power conversion, power quality preservation, grid stability, power flow management, renewable energy source (RES) integration, and enhanced grid resilience. Achieving these goals requires a precise inverter circuit switch approach. A boost power converter connected to the FC stack ensures voltage regulation, power conditioning, efficient power transfer, system integration, control, and protection. This enhances FC system adaptability and compatibility across various applications, minimizing input current ripples for prolonged FC lifespan. This study introduces a novel DC-DC boost converter with an artificial neural network (ANN) controller to reduce FC input current ripples and enhance FC stack-generated voltage for grid applications. It also presents a space vector sinusoidal pulse width modulation (SVPWM) technique for FC-based three-phase grid-tied inverters. This offers improved voltage utilization, precise voltage and current control, reduced harmonic distortion, rapid response, flexibility, scalability, reduced total harmonic distortion (THD), and over-modulation capability. The proposed SVPWM technique utilizes a digital signal processing (DSP)-based controller, combining high-speed processing, precision, and real-time capabilities to enhance system performance and efficiency. © 2023 Hydrogen Energy Publications LLCÖğe Design and implementation of a new dual-layer type 2 FLC-based energy management system for a fuel cell electric vehicle(Elsevier Ltd, 2026) Yılmaz, Alper; Toprak, Muhammed Zeyd; Bayrak, GökayThis study presents a new dual-layer energy management strategy (EMS) based on Interval Type-2 Fuzzy Logic Control (IT2 FLC) for a 1 kW PEMFC–ultracapacitor (UC) hybrid fuel cell electric vehicle. The proposed strategy enhances power distribution stability and fuel cell lifespan by leveraging the fast dynamic response of UC to mitigate the slow transient behavior of PEMFCs. A custom-designed full-bridge push-pull converter is developed to regulate power flow between energy sources, ensuring a stable 96V DC output despite variations in input voltage. Experimental validation on a real-scale prototype confirms robust voltage regulation within ±1 V and effective UC participation during transients, with instantaneous support up to 1000 W, thereby reducing fuel cell stress. Under scaled FTP-75 and WLTP Class-1 cycles, the IT2FLC consistently outperforms PID and Type-1 FLC, improving tracking by >80 % versus PID while limiting MAE and RMSE to <0.02 m/s and <0.03 m/s, respectively, with negligible overshoot. © 2026 Hydrogen Energy Publications LLCÖğe Design and Validation of an Effective Temperature Compensated-Based FBG Sensor Package for Air Vehicle Applications(Institute of Electrical and Electronics Engineers Inc., 2021) Arslan, Mehmet Mücahit; Bayrak, GökayThe use of Fiber Bragg Gratings (FBGs) sensors is increasing day by day because of its unique properties such as lightness, immunity to EM and RF signals, minimized harness complexity, and suitability to array manufacturing. Thereby, in the last decades, it has become the first choice in terms of data collection and long-term health monitoring in the aerospace field. On the other hand, like other conventional sensors, Fiber Bragg Grating sensors are also gets affected by the rapid change of environmental conditions such as temperature. In this context, to avoid false alarm situations and compensate for the effect of environmental condition changes, in this study a newly designed temperature compensation metal package structure has been explained and discussed in detail. Obtained results showed that, with the newly designed package structure, the temperature effect had been reduced with success over %95, and the proposed package had been eligible to operate up to 80°C without needing any external reference sensors.
