Elektrik ve Enerji Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12514/174

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Analysis of solar inverter THD according to PWM’s carrier frequency
(ICRERA, 2015) Adak, Süleyman; Adak, Süleyman
Solar PV systems are usually used in the generation of power systems. Electricity produced in Photovoltaic systems in the form of direct current. In order to convert direct current to alternating current used converters, which are harmonic source. In this thesis study, output distortion currents of solar inverter t are analyzed for various PWM’s carrier frequency. Analytical expressions related to obtained numerical results, which was found by curve fitting method. Simulations are implemented in MATLAB and Simulink software. R-L inductive load is implemented in hardware to show the effectiveness of the proposed system.
Classification and analysis of epileptic EEG recordings using convolutional neural network and class activation mapping
(2021) Yildiz, Abdulnasir; Zan, Hasan; Said, Sherif; Zan, Hasan
Electrical bio-signals have the potential to be used in different applications due to their hidden nature and their ability to facilitate liveness detection. This paper investigates the feasibility of using the Convolutional Neural Network (CNN) to classify and analyze electroencephalogram (EEG) data with their time-frequency representations and class activation mapping (CAM) to detect epilepsy disease. Several types of pre-trained CNNs are employed for a multi-class classification task (AlexNet, GoogLeNet, ResNet-18, and ResNet-50) and their results are compared. Also, a novel convolutional neural network architecture comprised of two horizontally concatenated GoogLeNets is proposed with two inputs scalograms and spectrogram of the eplictic EEG signal. Four segment lengths (4097, 2048, 1024, and 512 sampling points) with three time-frequency representations (short-time Fourier, Wavelet, and Hilbert-Huang transform) are statistically evaluated. The dataset used in this research is collected at the University of Bonn. The dataset is reorganized as normal, interictal, and ictal. The maximum achieved accuracies for 4097, 2048, 1024, and 512 sampling points are 100 %, 100 %, 100 %, and 99.5 % respectively. The CAM method is used to analyze discriminative regions of time-frequency representations of EEG segments and networks' decisions. This method showed CNN models used different time and frequency regions of input images for each class with correct and incorrect predictions.
Developed analytical expression for current harmonic distortion of the PV system’s inverter in relation to the solar irradiance and temperature
(Electrical Engineering, 2021) Adak, Süleyman; Adak, Süleyman; Cangi, Hasan; Eid, Bilal; Serdar Yılmaz, Ahmet
This paper deals with modeling and simulation of the total harmonic distortion of the current (THDI) dispatched from the inverter and connected to nonlinear load. The change of THDI was examined in relation to the ambient temperature (T) and solar irradiance (G).The developed model is being used to extract parameters for a given THDI as a function of temperature and solar radiation. This study outlines the working principle of photovoltaic (PV) panel as well as PV array. Off-grid PV system is modeled by using Matlab/Simulink program, and detailed analytical study has been carried out in this work. The design, modeling and simulation of this study are performed from 50 up to 988 W/m2 for solar irradiance. Harmonic components have negative effects on the steady-voltage stability of the PV system. Therefore, analytical expression is needed for steady-state stability analysis in order to reduce negative effects. Hence, two analytical expressions of THDI were obtained by two new different methods which are statistical package for the social sciences program and genetic expression programming. Eventually, two different methods have been verified by the Matlab/Simulink program in order to find out THDI and demonstrated the effectiveness of the proposed strategy. As a result of this study, it is observed that input current THDI of nonlinear load is too high at low irradiance. It is suggested that active harmonic filters should be used at low irradiance in order to produce better quality energy and avoid damages in the PV system.
Development software program for extraction of photovoltaic cell equivalent circuit model parameters based on the Newton–Raphson method
(SpringerLink, 2022) Adak, Süleyman; Cangi, Hasan; Yılmaz, Ahmet Serdar; Arifoğlu, Uğur
Finding the equivalent circuit parameters for photovoltaic (PV) cells is crucial as they are used in the modeling and analysis of PV arrays. PV cells are made of silicon. These materials have a nonlinear characteristic. This distorts the sinusoidal waveform of the current and voltage. As a result, harmonic components are formed in the system. The PV cell is the smallest building block of the PV system and produces voltages between 0.5 V and 0.7 V. It serves as a source of current. The amount of radiation hitting the cell determines how much current it produces. In an ideal case, a diode and a parallel current source make up the equivalent circuit of the PV cell. In practice, the addition of a series and parallel resistor is made to the ideal equivalent circuit. There are many equivalent circuits in the literature on modeling the equivalent circuit of a PV cell. The PV cell single–diode model is the most used model due to its ease of analysis. In this study, the iterative method by Newton–Raphson was used to find the equivalent circuit parameters of a PV cell. This method is one of the most widely used methods for determining the roots of nonlinear equations in numerical analysis. In this study, five unknown parameters (Iph, Io, Rs, Rsh and m) of the PV cell equivalent circuit were quickly discovered with the software program prepared based on the Newton–Raphson method in MATLAB
Development software program for finding photovoltaic cell open-circuit voltage and fill factor based on the photovoltaic cell one-diode equivalent circuit model
(Springer, 2024) Adak, Süleyman; Cangi, Hasan
The photovoltaic (PV) cell is the smallest building block of the PV solar system and produces voltages between 0.5 and 0.7 V. It acts as a current source in the equivalent circuit. The amount of radiation hitting the cell determines how much current it produces. The equivalent circuit of an ideal PV cell consists of a diode and a parallel current source. In order to express losses in applications, series and parallel resistance are added to the ideal equivalent circuit of the PV cell. There are many equivalent circuits in the literature for modeling the equivalent circuit of a PV cell. The single-diode equivalent circuit is the most widely used model because of its simplicity and ease of analysis. There are several methods available to estimate and analyze the parameters of PV cell models, such as Newton Raphson method, Lambert-W function, etc. In this study, the Newton Raphson method was used to find the equivalent circuit parameters of a PV cell. Fill factor is used to determine the quality of electricity generated by the photovoltaic cell. Open-circuit voltage is the maximum voltage value that the PV cell can transmit. The analysis of PV cell fill factor and open-circuit voltage was carried out using the developed software program. Then, the open-circuit voltage and fill factor were found using the software program prepared in MATLAB and given in Appendix.
Effects of distributed generations' integration to the distribution networks case study of solar power plant
(İlhami Çolak, 2017) Shobole, Abdulfetah; Baysal, Mustafa; Wadi, Mohammed; Tur, Mehmet Rida
All over the world, the Distributed Generations (DGs) integration to power system has increased in the recent years due to economic, environmental and technical advantages. Turkey which has the huge solar potential has focused on integrating both licensed and unlicensed solar power plants by providing 10 years of purchasing guarantee as an incentive for the electricity producers from solar energy. However, the integration of DGs has several negative effects on the distribution networks (DNs). This work is concerned with investigating the possible challenges that may arise due to integration of PV based DGs on the existing distribution networks. Short circuit current level with respect to variation in MW integration is studied for the case the utility network is weak and strong. When the utility network is strong, the integration effect of inverter based DGs like solar power plants were observed insignificant. However, for the weak utility networks, the integration of inverter based DGs has been observed to have significant influence. Finally, directly integrated DGs (without inverter) are considered to reveal its difference with the non-inverter based DGs. As the case study, the distribution network integration of a solar power project, which is found in the Antalya region of Turkey, is investigated. This is 12 MW solar power plant designed to be connected to the local distribution network in Antalya. It is concluded that the effects of directly integrated DGs are observed more prominent compared to the inverter based DGs. DigSILENT Power Factory simulation tool is used for the study.
Effects of Electric Vehicles and Charging Stations on Microgrid Power Quality
(Gazi University Journal of Science Part A: Engineering and Innovation, 2022) Adak, Süleyman; Kaya, Rıdvan; Kaya, Rıdvan; Yılmaz, Ahmet Serdar
In this study, integration of renewable energy sources and Electric Vehicles (EVs) into a micro-grid was modeled and analyzed. The microgrid is divided into four important parts; a diesel generator, acting as the base power generator; a photovoltaic (PV) farm combined with a wind farm, to produce electrical energy; a vehicle to grid (V2G) system installed next to the last part of the microgrid which is the load of the microgrid. The size of the microgrid represents approximately a community of a thousand households during a low consumption day in spring or fall. There are 100 electric vehicles in the base model which means that there is a 1:10 ratio between the cars and the households. This is a possible scenario in a foreseeable future. The continuous increase in their rate in energy production makes micro-grids important. Microgrids can be designed to meet the energy needs of hospitals, universities or charging stations of electric cars, as well as to meet the energy needs of a district, village or industrial site. Charging stations are needed to charge the electric vehicle battery. In this study, the effects of electric vehicles on the microgrid network are analyzed. Electric vehicles have non-linear circuit elements in their structures. Therefore, they are a source of harmonic current in the microgrid. They negatively affect the power quality of the microgrid. The battery in electric vehicles is charged with direct current. The alternating current from the microgrid needs to be converted to direct current.
Harmonics Mitigation of Stand‑Alone Photovoltaic System Using LC Passive Filter
(Journal of Electrical Engineering & Technology, 2021) Adak, Süleyman
This article investigates modeling and simulation of the of-grid photovoltaic (PV) system, and elimination of harmonic components using an LC passive flter. Pulse width modulation (PWM) inverter is used to convert the direct current to alternating current. It is very important in terms of energy quality that the inverter output current total harmonic distortion (THDI) is below the value given by standards. Harmonic components have negatively efect on of-grid PV power system. THDI should be kept below a certain level in order to prevent damage to the equipment in the of-grid system and to ensure a higher quality energy fow to reduce the total harmonic distortion (THD) of the solar inverter output current; LC passive flter must be connected to the output of the PWM inverter. There are many types of passive flters for solar inverters. One of the most widely used flter types is the LC flter. LC flters are used in of-grid systems. LC flter is smaller in size and lower cost than other flters. But it is more complicated to determine the parameters of the LC flter. Therefore, in order for the system to remain in a steady state, the parameters must be accurately calculated and analyzed. In this study, the output power of the solar inverter, switching frequency, bus voltage etc. values were determined and LC flter parameters were calculated. Since high inductance values are used in LC flters, the voltage drop increases in these flters. To reduce the voltage drop, the DC bus voltage must be increased, which increases the switching losses. LC flter is connected between the inverter and the nonlinear load to flter the harmonic components produced by the DC/DC boost converter, DC/AC inverter and non-linear load. Matlab/Simulink program was used in Simulation and analysis of of-grid solar system. Solar inverter output current THD was measured as 91.55%. After the LC flter is connected to the system, this value has dropped to 2.62%.
Harmonics Mitigation of Stand-Alone Photovoltaic System Using LC Passive Filter
(Journal of Electrical Engineering and Technology, 2021) Adak, Süleyman
This article investigates modeling and simulation of the off-grid photovoltaic (PV) system, and elimination of harmonic components using an LC passive filter. Pulse width modulation (PWM) inverter is used to convert the direct current to alternating current. It is very important in terms of energy quality that the inverter output current total harmonic distortion (THDI) is below the value given by standards. Harmonic components have negatively effect on off-grid PV power system. THDI should be kept below a certain level in order to prevent damage to the equipment in the off-grid system and to ensure a higher quality energy flow to reduce the total harmonic distortion (THD) of the solar inverter output current; LC passive filter must be connected to the output of the PWM inverter. There are many types of passive filters for solar inverters. One of the most widely used filter types is the LC filter. LC filters are used in off-grid systems. LC filter is smaller in size and lower cost than other filters. But it is more complicated to determine the parameters of the LC filter. Therefore, in order for the system to remain in a steady state, the parameters must be accurately calculated and analyzed. In this study, the output power of the solar inverter, switching frequency, bus voltage etc. values were determined and LC filter parameters were calculated. Since high inductance values are used in LC filters, the voltage drop increases in these filters. To reduce the voltage drop, the DC bus voltage must be increased, which increases the switching losses. LC filter is connected between the inverter and the nonlinear load to filter the harmonic components produced by the DC/DC boost converter, DC/AC inverter and non-linear load. Matlab/Simulink program was used in Simulation and analysis of off-grid solar system. Solar inverter output current THD was measured as 91.55%. After the LC filter is connected to the system, this value has dropped to 2.62%.
Local Pattern Transformation-Based convolutional neural network for sleep stage scoring
(2023) Zan, Hasan; Yıldız, Abdulnasır; Zan, Hasan
Sleep stage scoring is essential for the diagnosis and treatment of sleep disorders. However, manual sleep scoring is a tedious, time-consuming, and subjective task. Therefore, this paper proposes a novel framework based on local pattern transformation (LPT) methods and convolutional neural networks for automatic sleep stage scoring. Unlike in previous works in other fields, these methods were not employed for manual feature extraction, which requires expert knowledge and the pipeline behind it might bias results. The transformed signals were directly fed into a CNN model (called EpochNet) that can accept multiple successive epochs. The model learns features from multiple input epochs and considers inter-epoch context during classification. To evaluate and validate the effectiveness of the proposed approach, we conducted several experiments on the Sleep-EDF dataset. Four LPT methods, including One-dimensional Local Binary Pattern (1D-LBP), Local Neighbor Descriptive Pattern (LNDP), Local Gradient Pattern (LGP), and Local Neighbor Gradient Pattern (LNGP), and different polysomnography (PSG) signals were analyzed as sequence length (number of input epochs) increased from one to five. 1D-LBP and LNDP achieved similar performances, outperforming other LPT methods that are less sensitive to local variations. The best performance was achieved when an input sequence containing five epochs of PSG signals transformed by 1D-LBP was employed. The best accuracy, F1 score, and Kohen's kappa coefficient were 0.848, 0.782, and 0.790, respectively. The results showed that our approach can achieve comparable performance to other state-of-the-art methods while occupying fewer computing resources because of the compact size of EpochNet.
Local Pattern Transformation-Based convolutional neural network for sleep stage scoring
(ScienceDirect, 2023) Zan, Hasan; Yildiz, Abdulnasır; Zan, Hasan
Sleep stage scoring is essential for the diagnosis and treatment of sleep disorders. However, manual sleep scoring is a tedious, time-consuming, and subjective task. Therefore, this paper proposes a novel framework based on local pattern transformation (LPT) methods and convolutional neural networks for automatic sleep stage scoring. Unlike in previous works in other fields, these methods were not employed for manual feature extraction, which requires expert knowledge and the pipeline behind it might bias results. The transformed signals were directly fed into a CNN model (called EpochNet) that can accept multiple successive epochs. The model learns features from multiple input epochs and considers inter-epoch context during classification. To evaluate and validate the effectiveness of the proposed approach, we conducted several experiments on the Sleep-EDF dataset. Four LPT methods, including One-dimensional Local Binary Pattern (1D-LBP), Local Neighbor Descriptive Pattern (LNDP), Local Gradient Pattern (LGP), and Local Neighbor Gradient Pattern (LNGP), and different polysomnography (PSG) signals were analyzed as sequence length (number of input epochs) increased from one to five. 1D-LBP and LNDP achieved similar performances, outperforming other LPT methods that are less sensitive to local variations. The best performance was achieved when an input sequence containing five epochs of PSG signals transformed by 1D-LBP was employed. The best accuracy, F1 score, and Kohen’s kappa coefficient were 0.848, 0.782, and 0.790, respectively. The results showed that our approach can achieve comparable performance to other state-ofthe-art methods while occupying fewer computing resources because of the compact size of EpochNet.
Multi-task learning for arousal and sleep stage detection using fully convolutional networks
(IOP Publishing, 2023) Zan, Hasan; Yıldız, Abdulnasir; Zan, Hasan
Objective: Sleep is a critical physiological process that plays a vital role in maintaining physical and mental health. Accurate detection of arousals and sleep stages is essential for the diagnosis of sleep disorders, as frequent and excessive occurrences of arousals disrupt sleep stage patterns and lead to poor sleep quality, negatively impacting physical and mental health. Polysomnography is a traditional method for arousal and sleep stage detection that is time-consuming and prone to high variability among experts. Approach: In this paper, we propose a novel multi-task learning approach for arousal and sleep stage detection using fully convolutional neural networks. Our model, FullSleepNet, accepts a full-night single-channel EEG signal as input and produces segmentation masks for arousal and sleep stage labels. FullSleepNet comprises four modules: a convolutional module to extract local features, a recurrent module to capture long-range dependencies, an attention mechanism to focus on relevant parts of the input, and a segmentation module to output final predictions. Main results: By unifying the two interrelated tasks as segmentation problems and employing a multi-task learning approach, FullSleepNet achieves state-of-the-art performance for arousal detection with an area under the precision-recall curve of 0.70 on Sleep Heart Health Study and Multi-Ethnic Study of Atherosclerosis datasets. For sleep stage classification, FullSleepNet obtains comparable performance on both datasets, achieving an accuracy of 0.88 and an F1-score of 0.80 on the former and an accuracy of 0.83 and an F1-score of 0.76 on the latter. Significance: Our results demonstrate that FullSleepNet offers improved practicality, efficiency, and accuracy for the detection of arousal and classification of sleep stages using raw EEG signals as input.
Multi-task learning for arousal and sleep stage detection using fully convolutional networks
(2023) Zan, Hasan; Yıldız, Abdulnasır; Zan, Hasan
Objective. Sleep is a critical physiological process that plays a vital role in maintaining physical and mental health. Accurate detection of arousals and sleep stages is essential for the diagnosis of sleep disorders, as frequent and excessive occurrences of arousals disrupt sleep stage patterns and lead to poor sleep quality, negatively impacting physical and mental health. Polysomnography is a traditional method for arousal and sleep stage detection that is time-consuming and prone to high variability among experts. Approach. In this paper, we propose a novel multi-task learning approach for arousal and sleep stage detection using fully convolutional neural networks. Our model, FullSleepNet, accepts a full-night single-channel EEG signal as input and produces segmentation masks for arousal and sleep stage labels. FullSleepNet comprises four modules: a convolutional module to extract local features, a recurrent module to capture long-range dependencies, an attention mechanism to focus on relevant parts of the input, and a segmentation module to output final predictions. Main results. By unifying the two interrelated tasks as segmentation problems and employing a multi-task learning approach, FullSleepNet achieves state-of-the-art performance for arousal detection with an area under the precision-recall curve of 0.70 on Sleep Heart Health Study and Multi-Ethnic Study of Atherosclerosis datasets. For sleep stage classification, FullSleepNet obtains comparable performance on both datasets, achieving an accuracy of 0.88 and an F1-score of 0.80 on the former and an accuracy of 0.83 and an F1-score of 0.76 on the latter. Significance. Our results demonstrate that FullSleepNet offers improved practicality, efficiency, and accuracy for the detection of arousal and classification of sleep stages using raw EEG signals as input.
Physical properties of solution processable n-type Fe and Al co-doped ZnO nanostructured thin films: Role of Al doping levels and annealing
(ELSEVIER, 2018) BOZ, İbrahim; GÖKTAŞ, Abdullah; ASLAN, Ferhat; YEŞİLATA, Bülent
The role of annealing temperature and Fe and Al co-doping on structural, optical, electrical and magnetic properties of solution processable ZnO thin films were investigated. ZnO:Fe thin films fixed with 2% of typical ferrous component were obtained to examine the role of 1–10% Al doping. X-ray diffraction analyses clearly indicates that the films to be polycrystalline and preferentially oriented along the c-axis of the hexagonal wurtzite structure. The film thickness, homogeneous distribution and decreasing/increasing of grain size dependence on Al content/annealing temperature (TA) were assessed by scanning electron microscopy. X-ray photoelectron spectroscopy revealed that Al3+ and Fe2+ ions to substitute for Zn2+ without changing the wurtzite structure. A slight decrease in the optical band gap of ZnO at fixed Fe dopant and a considerable increase of the optical band gap with increased Al doping concentrations and TA were observed. The refractive index increases with the fixed Fe dopant level and then decreases by Al doping levels, whereas the extinction coefficient clearly increases depended on both of Fe and Al concentrations. The refractive index and extinction coefficient both decrease with TA. Hall measurements show n-type conductivity and the increase of charge carrier concentration by Al doping levels and TA. Magnetic studies indicate room temperature ferromagnetism in Al and Fe co-doped ZnO thin films, whereas no room temperature ferromagnetism for the Fe-doped ZnO thin films was observed. An enhanced room temperature ferromagnetism in Al and Fe co-doped ZnO thin films was observed to depend on TA.
THE RELATIONSHIP BETWEEN THE INPUT CURRENT HARMONIC DISTORTION OF ASYNCHRONOUS MOTOR AND THE SWITCHING FREQUENCY IN PHOTOVOLTAIC POWER SYSTEM
(UBAK, 2018) Adak, Süleyman; Cangi Hasan; Yılmaz Ahmet Sedar
This paper deals with the design, modelling, analysis and simulation input current harmonics distortion of induction motor depending on switching frequency (fsw) in off-grid photovoltaic (PV) power system. The proposed solar system is a combination of a boost DC–DC boost converter, DCAC solar inverter;three-phase squirrel cage induction motor.Harmonic currents generated by power electronics based devices, and cause serious power quality problems in off- grid PV systems. Harmonics are being increased day by day in off-grid PV power systems. As a result, heat losses, power bills, and reduction in the efficiency occur in the system. Harmonic components should be measured and calculated correctly in order to solve the energy quality problems.The relationship between carrier frequency of PWM and total harmonic distortion for current (THDI) are examined in this article.The analytical expression between fsw and THDI of induction motor are obtained by using the curve fitting method. It is observed that THDI value decreases as value of fsw increases. The design, modelling and simulation of this topology are performed using Matlab/Simulink program for range of 200 Hz to 51 kHz switching frequency.This shows the satisfactory performance of harmonic distortion mitigation higher than 0, 70 kHz switching frequency of PWM. It is observed that the PWM carrier frequency is inversely proportional changes with load current total harmonic distortion. Inverse proportionality constant is found by curve fitting method.
Sleep arousal detection using one dimensional local binary pattern-based convolutional neural network
(IEEE, 2021) Zan, Hasan; Yıldız, Abdulnasır; Zan, Hasan
Sleep arousal is defined as a shift from deep sleep to light sleep or complete awakening. Arousals cause sleep deprivation by fragmenting sleep, and ultimately, many health problems. Arousals can be induced by well-studied apneas and hypopneas or other sleep orders such as hypoventilation, bruxism, respiratory effort-related arousals. Thus, detection of less-studied non-apnea/hypopnea arousals is important for diagnosis and treatment of sleep disorders. Traditionally, polysomnography (PSG) test that is recording and inspecting overnight physiological signals is used for sleep studies. In this work, a novel method based on one dimensional local binary pattern (1D-LBP) and convolutional neural network (CNN) for automatic arousal detection from polysomnography recordings is proposed. 25 recordings from PhysioNet Challenge 2018 PSG dataset are used for experiments. Each signal in PSG recordings is transformed to a new signal using 1D-LBP, and then segmented using 10-s-long sliding window. The segments are fed to a CNN model formed by stacking 25 layers for classification of non-apnea/hypopnea arousal regions from non-arousal regions. Area under precision-recall curve (AUPRC) and area under receiver operating characteristic curve (AUROC) metrics are used for performance measurement. Experimental results reflect that the proposed method shows a great promise and obtains an AUPRC of 0.934 and an AUROC of 0.866.
The quality problems at low irradiance in the grid-connected photovoltaic systems
(Springer Science and Business Media Deutschland GmbH, 2024) Adak, Süleyman; Cangi, H.
Solar photovoltaic (PV) energy is one of the most prominent topics that have attracted the attention of researchers in recent years. The use of solar energy is increasing rapidly in the world. Although using PV energy has various advantages, it has some disadvantages. Among these disadvantages, power factor (PF) and total harmonic distortion (THD) issues are discussed in this article. When solar PV systems are integrated into the grid, various power quality problems arise. In addition, due to low power quality and high harmonics, power system components overheat and start operating in undesirable regions; causes great damage. The magnitude of PF and THD is dependent on solar irradiation values. In order to determine how the power quality in the grid-connected solar system is affected by changes in solar irradiation (G), results for various irradiation situations are presented and analyzed. In addition, at low irradiance values, the amplitude of harmonic components and reactive power increases, whereas the power factor of the PV system decreases. Low power factor and high amplitude of harmonics cause the efficiency of the solar system to decrease. In this study, PF and THDI values were measured on a particular cloudy day for analysis. An analysis of the solar PV system was conducted using Matlab/simulation program to model the grid-connected PV system. Thus, the analytical expression of the PF and THDI, which are dependent on irradiation, was found with a new method by using the Statistical Package for the Social Sciences (SPSS) program and the curve fitting method. Obtaining the analytical expressions for both solar irradiation (G) and power factor (PF) used the SPSS program and also solar irradiation (G) and total harmonic distortion (THDI) used the MATLAB curve fitting method which contributed to the science comparing to the existing literature. It can be prevented the low power quality by using such these expressions at low solar irradiation cases. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Thevenin Equivalent of Solar PV Cell Model and Maximum Power Transfer
(IEEE, 2021) Adak, Süleyman; Cangi, Hasan; Yılmaz, A. Serdar
Photovoltaic (PV) is the conversion of solar energy into DC electrical energy using PV cells. In addition, solar energy is an important renewable energy source. In this study, it is proposed that Thevenin's equivalent PV cell model produces a voltage-current characteristic that is quite representative of the operation of the PV source. Thevenin's elements depend on ambient temperature conditions, so charging is derived and simplified to construct a model that closely predicts and demonstrates adequate PV cell characteristic for different ambient temperature conditions. This method is very useful for estimating the desired performance and also for examining different Maximum Power Point Tracking (MPPT) algorithms. Theoretically, the simulation was supplemented with test data, then used to develop an equivalent Thevenin model in which the resistance is non-linear and voltage dependent. Thevenin's method and variable pitch is to improve the maximum power transfer to the load by increasing the performance of the PV cell. These methods were modeled and studied in a simulation program.
Zinc Molar Concentration Induced Structural and Optical Properties of Chemically Derived ZnS Thin Films
(2019) BOZ,İbrahim; GÖKTAŞ,Abdullah; TUMBUL,Ahmet; KILIÇ,Ahmet
Chemically derived polycrystalline ZnS thin films have a profound potantial for the optoelectronic and luminescent devices. Regarding this crucial fact that the chemically grown ZnS thin films, prepared at different Zn and S molar ratios, was investigated by X-ray diffraction (XRD), photoluminescence (PL), Fourier transmission infrared (FT-IR) spectrocopy and UV-Vis spectrocopy. The obtained results showed that the ZnS thin films had a hexagonal crystall structure. The crystalline quality of the films was changed depend on the molar ratios. The FT-IR analysis confirmed the formation of Zn-S binding. The PL measurements verified the presence of the main PL emissions of the ZnS structure. The UV-Vis analysis showed the transmittance and absorbance intensity was changed according to the molar ratios as well as the optical band gap of the ZnS thin films

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