LEE- Elektrik Mühendisliği-Yüksek Lisans
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ÖgeÜretim sistemlerinde valf-nokta etkili konveks olmayan dinamik ekonomik yük dağıtımı(Lisansüstü Eğitim Enstitüsü, 2017)Teknolojinin elektrik mühendisliğine sağladığı en büyük getirilerinden biri de dünya üzerinde enerji tüketimi artışıdır. Elektrikli aletlerin sayısında ve kullanım süresinde artışlar yaşandığı gibi daha ileri teknoloji sağlayabilmesi amacıyla tükettiği güçte de artışa gidilmiştir. Bu artışlar ve yazılım sistemlerinin daha çok tercih edilir hale gelmesi fazladan enerji ihtiyacını ortaya çıkarmıştır. Enerji ihtiyacındaki artış elektrik enerjisi üretim sistemlerinin yeterliliğini gün geçtikçe zorlamakta ve bizim daha fazla sayıda ve daha nitelikli elektrik enerjisi üretim santralleri kurmamızı gerektirmektedir. Üretilen elektrik enerjisi miktarındaki artışla birlikte üretimde optimizasyon işlemlerinden biri olan ekonomik yük dağıtımı da daha önemli bir hale gelmişir. Ekonomik yük dağıtımı, üretim sisteminde kullanılan tüm generatörlerin yakıt-güç eğrilerinin toplamından oluşturulan maliyet kullanarak talep edilen enerjiyi minimum yakıt maliyetiyle karşılayabilmek için hangi generatörün ne kadar yükleneceğinin hesaplanmasıdır. Generatörler arasında ekonomik yük dağıtımı yapılmasıyla aynı miktardaki enerji, ekonomik yük dağıtımı yapılmayan tesislere göre daha düşük yakıt maliyetiyle elde edilir. Güç sistemlerinden tüketiciler tarafından talep edilen elektrik enerjisi miktarının gün içersindeki belirli zaman periyotlarında farklılık göstermesi ekonomik yük dağıtım problemlerininin yetersiz kalmasına sebep olmuştur. Değişen talep güç değerlerine göre hangi zaman periyodunda, hangi generatörlerin ne kadar çıkış gücünde üretim yapacağının belirlenmesi amacıyla dinamik ekonomik yük dağtım problemleri oluşturulmuştur.
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ÖgeTrakya bölgesi iletim sisteminde kısa devre arıza akımlarının bara ayırma yöntemiyle sınırlandırılması ve kısıtlılık durumları için sistem gelişiminin incelenmesi(Lisansüstü Eğitim Enstitüsü, 2022-06-01)Çalışmada, güç sistemlerinde yaygın olarak kullanılan Gauss-Seidel, Newton-Raphson ve Fast Decoupled yük akışı analiz yöntemlerinin fonksiyonel denklemleri incelenerek, yöntemler birbirleriyle karşılaştırılmıştır. Trakya bölgesi iletim şebekesi Edirne, Kırklareli, Tekirdağ illeri, İstanbul Avrupa yakası, Çanakkale ilinin Gelibolu ve Eceabat ilçelerini kapsayan, gerilim seviyesi 400 kV ve 154 kV olan iletim sisteminden oluşmaktadır. Bölgede, nüfus ve sanayi yoğunluğunun fazla olması, enerjiye olan talebi de arttırmaktadır. Elektrik tüketiminin günden güne arttığı bölgede, iletim sistemine yeni yatırımların yapılması ve bu yeni projelerle analizler gerçekleştirilerek şebekenin güvenli işletilmesi gerekmektedir. Çalışmada, analizlerin yapılacağı gerçek bir sistem olan Trakya bölgesi iletim sistemi hakkında bilgi verilmiştir. Şebekede bulunan iletim hatlarının gerilim seviyesi, uzunluğu, bölgedeki transformatör ve şönt ekipman sayısı, bölgenin kurulu gücü ve puant yükü gibi Trakya bölgesini tanıtan veriler ele alınmıştır.
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ÖgeParallel evolutionary computation for distribution system planning and operation(Graduate School, 2022-06-14)The purpose of this study is to offer a technique for combining single- and multi-objective optimization algorithms with a parallel computing technique. Different scenarios are created for different numbers of Worker Processors (WPs), each of which is investigated separately and the results are compared. In these cases, a Master-Slave (MSM) calculation approach is used. The workload is distributed evenly across all WPs, and the Master Processor (MP) acts as the observer and executor of this computational approach. By using intelligent interruptions, the main processor receives the results of each WP's calculations and compares them to the results of other WPs, selecting the best solutions and returning them to the WPs. Wind Turbines and solar panels are examples of distributed renewable energy sources in this study
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ÖgeDeep learning for wind energy systems using the hurst exponent and statistical parameters(Graduate School, 2021-08-14)As we all know, energy demand is continuously increasing because of population growth and developing technology. As a result of this increasing demand, energy shortages and environmental pollution will occur. Besides, because of the growing crisis and other critical issues around energy, renewable energy is taking countries' attention and becoming important in various parts of the entire world. Wind energy, solar power, tidal energy, geothermal energy, etc. as renewable energy sources have been used to solve these issues. Among these alternative sources of energy, wind and solar energy have got the most attention recently. Since wind power has less pollution, shorter construction time, less occupation, and flexible investment, it has become one of the most effective sources of energy. And in this study, the information is about wind data. But the wind is unstable and mainly affected by meteorological and navigational conditions and the principle for its implementation changes from one place to another. These changes in the meteorological measurement cause uncertainty in wind farms' generated power that affects power supply and quality. Also, because it is impossible to generate every power amount by wind energy or store electrical energy, there is a limitation on the amount of output power. Therefore, An accurate prediction can cause the cost of power generation reduction, less winding reserve capacity of the grid, and more reliable operation of the grid. Because of aforesaid reasons, prediction in wind energy systems is a very important issue. Nowadays, deep neural networks have been considering for prediction problems. In this study, the convolutional neural network(CNN) as a deep neural network is used to do predictions in wind energy systems based on meteorological data of one station. Since the Hurst exponent H is used to determine the predictability degree of a set of data, it gives some information about data that is useful in developing predictive models both theoretical and computational in nature. We first aim to apply the Hurst exponent method on wind energy data and then execute a deep neural network on data to tarin data through that deep neural network. Work steps: this literature study on the yearly meteorological features of one station applies deep learning methods to it. First of all, we gathered reported data for wind speed, air pressure, and relative humidity as the inputs of one deep neural network to train that network for predicting wind speed data. Since the power of one turbine is related to wind speed value, studying the wind speed behavior of one location leads to the study of the power capacity of that location. Before training a neural network, it is better to study the behavior of wind speed and find its statistical model and predictability degree, so before entering meteorological data into a deep neural network we studied statistical parameters of wind speed and find the probability density of it and then we found Hurst exponent, as the factor for predictability degree, and, then, all data is entered to one CNN to tarin that network and predict wind speed data.
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ÖgeCompensation of dead time caused output voltage distortion in SPWM full bridge inverter(Graduate School, 2022-01-18)Nowadays, inverters have become an indispensable element for many application areas when industrial applications are examined. Inverters are widely used in battery systems, renewable energy systems, control of various electrical machines and power systems. Due to the fact that inverter is often used in industry, studies on inverters have increased recently and inverter technologies are developing gradually. Generally, single-phase or three-phase full bridge voltage source inverters are used in such applications and there are various modulation techniques such as sinusoidal pulse width modulation technique, space vector pulse width modulation technique and etc. to provide voltage and frequency control of these inverters. These various techniques have been developed to minimize switching losses and reduce harmonics in output current and voltage. In real applications, power switches used in power electronics circuits are not ideal. These power switches have turn-on and turn-off time in switching characteristic. Because of this reason, the simultaneous conduction of switches on the same leg causes short circuit in inverter circuit. This situation is undesirable. In order to prevent synchronous conduction of both switches of the same leg at the same time, time delay is inserted to the driving signal of these switches.This time is called as dead time. Although dead time/blanking time has to be used in this circuits as mentioned above, the dead time has a very negative effects in terms of distortion of output waveforms. These problems are distorion of the output voltage and current waveform to contain a significant number of harmonic components at low voltage and high switching frequency. During the dead time, distortion of the voltage and current waveforms can be seen clearly at zero crossings of the current. In literature, this situation is called as zero-current-clamping phenomenon. This effect becomes greater as the switching frequency increases. In order to eliminate or reduce these effects, several approaches have been proposed. These methods can be listed as dead time compensation methods, dead time elimination methods, dead time minimization methods. It is seen that it is necessary to use dead time compensation methods since it is desired that the output voltage of the inverters is close to the sinus form and thus the total harmonic distortion is be reduced to a minimum. In order to provide this, these compensation methods are gradually developed. In this thesis context, time compensation method, which is one of the dead time compensation methods, is used. The turn-on or turn-off time of the power devices are adjusted by changing pulse-width in this method. Pulse-width is increased or decreased at zero crossings of the current. Thus, THD value of output waveforms is decreased by using this method. In this thesis, both simulation and implementation of a voltage source single-phase inverter have been carried out and the sinusoidal pulse width modulation method (SPWM) is used as modulation technique. Digital sinusoidal pulse width modulation is programmed with the help of STM32F407VG microcontroller of STM series. In addition, STM32CubeIDE is used as development tool. SPWM is produced by comparing the sine tables, which is produced by the microcontroller, with the microcontroller counter. This circuit is designed as open-loop system and the modulation index is initially set to a certain value both R and RL loads. While the input voltage of the designed circuit is 400 V, the output voltage is 220Vrms and the switching frequency is 20 kHz. The output power of the designed circuit is between 450 and 480 W at both R and RL loads. In addition, the dead time is 1 µs in all cases. In fixed dead time, output voltage and current for compensated and uncompensated states are obtained by simulation and implementation at R and RL loads. Due to the effect of dead time, harmonic distortions are observed on the output voltage and output current in uncompensated state. In order to minimize this effect, the time compensation method, which is one of the dead time compensation methods, is used within the scope of this thesis as mentioned above. Thus, the harmonic distortion is aimed to be reduced. According to simulation results, while the total harmonic distortion of output voltage is 5.34 at uncompensated state, total harmonic distortion of output voltage is 3.15 at compensated state at R load. On the other hand, while the total harmonic distortion of output voltage is 5.42 at uncompensated state, total harmonic distortion of output voltage is 3.71 at compensated state at RL load. According to experimental results, while the total harmonic distortion of output voltage is 5.89 at uncompensated state, total harmonic distortion of output voltage is 3.86 at compensated state at R load. On the other hand, while the total harmonic distortion of output voltage is 6.02 at uncompensated state, total harmonic distortion of output voltage is 4.50 at compensated state at RL load. According to the results, It has been clearly seen that the applied time compensation method reduces the harmonic distortions on the output voltage caused by the dead time.