Search

The ever-growing battery electric vehicle market (BEV) have reached several millions of sales annually, as a result of significant electrification of transport efforts globally. Accurate estimation of energy consumed by BEVs is of major importance especially for charging station selection, route planning and development of energy-efficient driving strategies in both manual and autonomous driving. One of the ways of achieving this is to conduct experiments on real BEVs, which is costly and labor intensive. An alternative to real life experimentation is to design high-fidelity mathematical models for energy consumption of BEVs and feed this model with experimental standardized driving cycles. This study develops and investigates the capabilities and advantages of a generic, detailed, modular BEV model. The effects of wide range of parameters on energy consumption of a BEV are analyzed comprehensively. The study is concluded by discussing the promising potential areas of use of the developed model.

Enerji kalitesi elektrik güç sistemlerine bağlı ekipmanların verimi veperformansı için gerekmektedir. Enerji kalitesinin ana hedefi yüke ulaşangerilim ve akım sinyalinin en iyi derecede sinusoidal dalga şekline sahipolmasıdır. Sistemde nonlineer devre elemanlarının varlığı harmoniklerinüretilmesine neden olmaktadır. Harmonikler enerji kalitesini olumsuzetkileyerek sistem performansını düşürmektedir. DC beslemeli raylı sistemlernonlineer elemanlardan oluştuğu için sistemde harmonikler oluşmaktadır. Buçalışmada 1500 V DC Beslemeli Raylı Sistemlerde Gerilim Harmoniği ProblemininAGT (Anlık Güç Teorisi) Tabanlı Paralel Aktif Güç Fitresi ile Çözümüyapılmıştır. AGT ile zamanda oluşabilecek gecikmelerin önüne geçilebilmesihedeflenmiştir. Aktif filtre ile klasik filtreleme yöntemleri karşılaştırılaraksonuçlar elde edilmiştir. Sistem analiz edilerek elde edilen sonuçlar grafiklerüzerinden verilmiştir. Devre filtreli ve filtresiz olarak çalıştırılarak eldeedilen sonuçlar karşılaştırmalı olarak verilmiştir. Her iki duruma ait gerilimTHD (Toplam harmonik distorsiyon) değeri hesaplanarak elde edilen iyileştirmeortaya konulmuştur., Energy quality is required for the efficiency and performance ofequipment connected to electrical power systems. The main objective of theenergy quality is that the voltage and current signal reaching the load has thebest sinusoidal waveform. The presence of nonlinear circuit elements in thesystem leads to the generation of harmonics. Harmonics adversely affect energyquality and reduce system performance. Since DC powered rail systems consist ofnonlinear elements, harmonics are formed in the system. In this study, voltageharmonic problem in 1500 V DC supply rail systems is solved with IPT(Instantaneous Power Theory) based parallel active power filter. With the AGT,it is aimed to prevent delays in time. The results were compared with activefilter and classical filtering methods. The results obtained by analyzing thesystem are given on the graphs. The results obtained by operating the circuitwith and without filter are given comparatively. The voltage THD (Totalharmonic distortion) value of both cases was calculated and the improvementobtained was demonstrated.

In DC railways, the traction power supplyvoltage provided by the electrification system gives the power it needs. Energyis aimed to be of high quality while providing this power. The vehicle’sperformance is influenced when the voltage supplied for the vehicle performanceis in certain limits. This value is affected by voltage drop on the line. Inthis study, the determination of the minimum vehicle voltage in a railway linewith 1500 V DC supply in relation to the vehicle performance data wasinvestigated. .The artificial intelligence methods adaptive neuro-fuzzyinference system (ANFIS) and support vector machines (SVM) were applied. Theperformance data of Sultangazi-Arnavutkoy metro line were used in the study.Ideal results were obtained with the calculations., DCbeslemeli metro hatlarında elektrifikasyon sistemi tarafından sağlanan cer gücübesleme gerilimi vasıtasıyla aracın ihtiyacı olan güç sağlanmaktadır. Güç teminisağlanırken enerjinin kaliteli olması hedeflenir. Hat için sağlanan geriliminbelirli sınırlar dahilinde olması aracın performansını etkilemektedir. Hattaoluşan gerilim düşümüne bağlı olarak bu değer etkilenmektedir. Bu çalışmada1500 V DC beslemeli bir metro hattında minimum araç geriliminin araç performansverilerine bağlı olarak belirlenmesi incelenmiştir. Çalışma için yapay zekatekniklerinden olan Uyarlamalı Sinirsel Bulanık Çıkarım Sistemi (ANFIS) veDestek Vektör Makinaları (SVM) yöntemleri tercih edilmiştir. Çalışma için Sultangazi-Arnavutköy hattına aitbir grup performans verisi kullanılmıştır. Yapılan hesaplamalarla idealsonuçlar elde edilmiştir.

This paper presents average sliding current controller (ASCC) for the proton membrane exchange fuel cell (PEMFC)-based DC-DC cascade boost converter under different source and load conditions. PEMFC which has variable voltage and current can be used in a lot of applications with a wide operating range in low temperatures. However, as the PEMFC produces low nonlinear voltage, this lower nonlinear voltage value needs to be increased as a linear voltage with an appropriate power electronics converter. Therefore, this paper proposes DC-DC cascade boost converter which has a higher voltage gain for PEMFC stack. First, a classical PI controller was applied to regulate the output voltage. Then, the current of the PEMFC-based DC-DC cascade boost converter was controlled via ASCC by using output of the voltage controller. After analyzing the dynamic model of the PEMFC-based DC-DC cascade boost converter via MATLAB/Simulink program, the experimental results of the controlled PEMFC-based DC-DC cascade boost converter are observed and discussed.

Ulaşım sistemleri içinde elektrik beslemeli demiryolları yatırım tercihi olarak yüksek bir orana sahiptir. Elektrikli demiryollarında ise elektrifikasyon sisteminin elektrik verme görevini kusursuz olarak yerine getirebilmesi işletme sürekliliği için esastır. Tasarım öncesinde elektrifikasyon sistemi benzetimi yapılarak sisteme ait kapasite, performans ve arıza durumları test edilmektedir. İşletme sürekliliği için arıza durumlarının analizi ve olası tedbirlerin alınması büyük önem taşımaktadır. Bu çalışmada dinamik bir model oluşturularak 1500 V DC beslemeli bir şehiriçi metro hattının benzetimi yapılmıştır. Dinamik yapı için geliştirilen algoritma anlatılarak benzetim sonuçları verilmiştir. Çalışma için katener sisteminde olası bir kısa devre durumunun analizi araştırılmıştır. 7 trafo merkezi bulunan bir raylı sistem hattına ait veriler kullanılarak kısa devre durumunun olası etkileri grafikler üzerinden değerlendirilmiştir. Elde edilen sonuçlar üzerinden alınması gereken tedbirler verilmiştir.

Guc sistemlerinde gerilim kararliligi cok onemlidir. Tek fazli ve cok fazli elektrik sistemlerinde olusabilecek herhangi bir ariza durumu ya da gerilim duzensizligine neden olabilecek baska bir durum guc kalitesini olumsuz etkilemektedir. Demiryollarinda gerilim kararliligi isletme surekliliginin saglanmasi acisindan kritiktir. DC beslemeli rayli sistemlerde, DC gerilim trafo merkezlerinde bulunan AC sebeke geriliminden elde edildigi icin AC bolumde olusabilecek herhangi bir olumsuz durum DC gerilimi de etkilemektedir. Bu calismada 750 V DC beslemeli bir demiryolu hattinda olusabilecek guc kalitesi probleminin UVDGM (Uzay Vektor Darbe Genislik Modulasyonu) bazli Dstatkom (Dagitim Sistemi Statik Senkron Kompanzator) ile cozulmesi arastirilmistir. Calisma icin trafo merkezinde olusabilecek ariza durumunun benzetimi yapilarak gerilim duzensizligi problemi Dstatkom ile ortadan kaldirilmistir. Benzetim sonuclari ile ilgili olarak AC ve DC gerilimlere ait analiz sonuclari karsilastirmali olarak verilerek saglanan iyilestirme durumu ortaya konulmustur.

In this study, the determination of the maximum value of the voltage drop created by the traction force was performed for a 1500 V DC-fed rail system by means of the artificial neural networks (ANN) and support vector machines (SVM). The voltage drop occurring on the line was calculated with regard to the operating parameters by means of the ANN and SVM. The ANN and SVM were explained and a comparison was made. The Levenberg-Marquardt (LM) algorithm was used for the ANN model. The Levenberg-Marquardt algorithm was preferred due to the speed and stability it provides for the training of artificial neural networks. The electrification system in the rail systems is designed with regard to the operating data and design parameters. The minimum voltage rating that the traction force requires during the operation needs to be provided in the electrification system. The highest value of the voltage drop on the line determines the lowest value of the traction force voltage. This value must be in certain limits for the continuity of the operation. The created datas regarding one-way and two-way supply conditions were examined for simulation. In this way railway electrification traction power simulation was done by artificial intelligence methods and traction power simulation results were predicted without doing traction simulation. With the designed system, the success rate is over %95.

Railway electrification systems are designed with regard to the operating data and design parameters. The minimum voltage rating required by traction during the operation should be provided. The maximum voltage drop on a line determines the minimum traction voltage. This voltage should be maintened within certain limits for the continuity of operation. In this study, the maximum voltage drop generated via traction was determined using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for a 25-kV AC-supplied railway. The voltage drop on line was calculated with regard to the operating data using ANN and ANFIS. ANN and ANFIS were explained, and the results were compared. The Levenberg–Marquardt (LM) algorithm was used for the ANN model. The LM algorithm is preferred because of the speed and stability it provides for the training of ANNs. The data created for one-way supply status were examined for simulation.

In this study, the simulation of an electrification system and traction power system of a 25 kV AC feed railway line was performed with all its subcomponents using MATLAB/Simulink. The power flow theory was used while modeling the railway electrification system. The transformer substation, catenary, rail, and vehicle were modeled together with the operational data. This model is used in order to determine the number of transformers, the distance of feeding centers, and the frequency of trips. The optimum design of electrification projects depends on these criteria. A dynamic structure was created with a new algorithm developed for vehicle load characteristics. The simulation of the electrification system and traction power system is performed before the analysis stage, together with the vehicle and other design parameters. This analysis is performed for the best performance of the systems. In this study, the power simulation of the railway was conducted for three different operation scenarios using MATLAB/Simulink.

In this study, the determination of the rail voltage for a 1500 V DC-fed rail system by means of the adaptive neuro-fuzzy inference system (ANFIS), support vector machines (SVM) and artificial neural networks (ANN). The distance occurring on the line was calculated with regard to the operating parameters by means of the ANFIS, SVM and ANN. The ANFIS, SVM and ANN were explained and a comparison was made. The electrification system in the rail systems is designed with regard to the operating data and design parameters. While the electrification system is formed, the maximum rail voltage needs to be provided in the limits of the touch voltage limits during the operation. The highest value of the rail voltage occurring on the line determined by the line characteristic properties. This value needs to be kept within certain limits for the continuity of the operation. The data created regarding one-way and two-way supply conditions were examined for simulation.

Bu calismada 4 farkli tip enerji uretim santrali barindiran bir yuk tevzii merkezi olusturulmus ve soz konusu santrallerin her birinin uretim set degerlerini belirleyebilmek amaciyla karisik tamsayi programlama algoritmasindan yararlanilarak bir optimizasyon yazilimi olusturularak benzetim yapilmistir. Soz konusu 4 santralin bir tanesi Dogalgaz Kombine Cevrim Santrali, bir tanesi Gaz Turbini Santrali, bir tanesi Fuel-Oil Turbini Santrali ve bir tanesi de Komur Yakitli Termik Elektrik Santralidir. Bu santrallerde toplam 15 adet unite bulunmaktadir. Cesitliligi arttirabilmek ve daha kullanisli bir metodoloji olusturabilmek icin gerceklestirilen optimizasyonda uniteler baz alinmistir. Turkiye kosullarini yansitan bu optimizasyon yazilimina ileride kullanilmak uzere alternatif olarak karbon salinimlarini da gozeten bir bolum eklenmistir. Boylelikle karbon salinimlarinin dikkate alinmasinin elektrik uretim set degerlerinde yaptigi etki net olarak gozlenebilmistir.

The electrification system in rail systems is designed with regard to the operating data and design parameters. While the electrification system is formed, the minimum voltage rating that the traction force requires during the operation needs to be provided. The highest value of the voltage drop occurring on the line is determined by the distance between power centers. This value needs to be kept within certain limits for the continuity of operation. In this study, the determination of the distance between DC traction power centers for a 1500-V DC-fed rail system is done by means of the adaptive neuro-fuzzy inference system (ANFIS), support vector machines (SVMs), and artificial neural networks (ANNs). The distance occurring on the line is calculated with regard to the operating parameters by means of the ANFIS, SVMs, and ANNs. The ANFIS, SVMs, and ANNs are explained and a comparison is made. The data created regarding one-way and two-way supply conditions are examined for simulation. The main contribution of this paper is the determination of the distance between railway traction power centers with artificial intelligence methods.

This study extensively presents the Automatic Generation Control (AGC) application of Artificial Bee Colony (ABC) algorithm. This algorithm is one of the new population based optimization algorithms which have been developed since 2005. In this study, the algorithm is applied to the interconnected reheat thermal power system in order to tune the parameters of PI and PID controllers which are used for AGC. The tuning performance of the algorithm is compared with that of Particle Swarm Optimization (PSO) algorithm through transient response analysis method. in addition to these, the robustness analysis is applied to the power system which is optimized by ABC algorithm so as to determine its response towards changing in the load and the system parameters, varied in the range of +/- 50%. The behavior of the system is also investigated with this analysis towards the different cost functions such as integral of absolute error (IAE), integral of squared error (ISE), integral of time weighted squared error (ITSE) and integral of time multiplied absolute error (ITAE). At the end of the study, it is seen that the ABC algorithm is successfully applied to the AGC in the application of interconnected reheat thermal power system, and it shows better tuning capability than the other similar population based optimization algorithm. Furthermore, it is also seen that the proposed system is robust and is not affected by changing in the load, the power system parameters and the cost functions. (c) 2012 Elsevier Ltd. All rights reserved.

Cam, Ertugrul/0000-0001-6491-9225 WOS: 000244495000011 This study presents a typical industrial plant whose performance is severely affected by disturbances, particularly by changes in the operating point. This is typically the case for power plants, which can be treated as multi-variable dynamic systems. Measurements were made in the power plant for four different operating points in order to build a model to describe the dynamic behaviour. The dynamic model for these operating conditions of the multi-variable plant has been developed by application of parameter estimation methods. Based on these multi-variable models, two different types of adaptive control schemes have been tested by extended simulation studies. Because of the very promising results, preparations for practical application of the simulation results in the plant are now Linder work. (c) 2006 Elsevier Ltd. All rights reserved.

This study presents a fuzzy logic based control technique to regulate the power and enthalpy outputs in a boiler of a 765 MW coal fired thermal power plant. An approximate mathematical model of the thermal power plant was developed by using real time data on Computer Aided Design and Control (CADACS) software. Conventional proportional, integral and derivative (PID), fuzzy logic (FL) and fuzzy gain scheduled proportional and integral (FGPI) controllers have been applied to the power plant model. The simulation results show that the FGPI controller developed in this study performs better than the rest of the controllers on the settling time and overshoot of power and enthalpy outputs. © 2005 Elsevier Ltd. All rights reserved.

Cam, Ertugrul/0000-0001-6491-9225 WOS: 000233328300002 This study presents an application of a fuzzy gain scheduled proportional and integral (FGPI) controller for load-frequency control of a two-area electrical interconnected power system. Model simulations of the power system show that the proposed FGPI controller is effective and suitable for damping out oscillations resulted from load perturbations. The current FGPI results were compared against those from a conventional proportional and integral (PI) controller, a fuzzy logic controller and a FGPI controller proposed by Chang and Fu (Chang C. S., Fu W. Area load-frequency control using fuzzy gain scheduling of PI controllers. Electr Power syst Res 1997; 42: pp. 145-152). Two performance criteria were utilized for the comparison: settling times and overshoots of the frequency deviation and absolute error integral. The comparison study indicated that the proposed FGPI controller has better performance than the other three controllers. (c) 2005 Elsevier Ltd. All rights reserved.

This paper presents real-time application adaptive control concept of a typical industrial plant whose performance is severely affected by disturbances and in particular by changes in the operating point. This is typically the case for large coal fired power plants which canbe treated as multivariable dynamic system. A short description of the power plant is given. For this power plant, a reduced mathematical model is developed. The results of experimental modelling will be shortly discussed. The conventional control of this power plant is investigated and described. The design of the adaptive model-refence controller used in the power plant for real-time control is presented in theory. Realization of the use of the adaptive control is shown and the results of a three-month installation of a decentralized adaptive control algorithm for electrical power and enthalpy control of a 750 MW power plant are discussed and compared with those of the conventional PID control.

Cam, Ertugrul/0000-0001-6491-9225 WOS: 000242103800020 In this paper, an adaptive controller was applied to a 765 MW large thermal power plant to decrease operating costs, increase quality of generated electricity and satisfy environmental concerns. Since power plants may present several operating problems such as disturbances and severe effects at operating points, design of their controllers needs to be carried out adequately. For these reasons, first, a reduced mathematical model was developed under Computer Aided Analysis and Design Package for Control, (CADACS), so that the results of the experimental model have briefly been discussed. Second, conventional PID and adaptive controllers were designed and implemented under the real-time environment of the CADACS software. Additionally, the design of the adaptive model-reference and conventional PID controllers used in the power plant for real-time control were theoretically presented. All processes were realized in real-time. Due to safety restrictions, a direct connection to the sensors and actuators of the plant was not allowed. Insted a coupling to the control system was realized. This offers, in addition, the usage of the supervisiory functions of an industrial process computer system. Application of the controllers indicated that the proposed adaptive controller has better performances for rise and settling times of electrical power, and enthalpy outputs than the conventional PID controller does. (c) 2006 Elsevier Ltd. All rights reserved.

Cam, Ertugrul/0000-0001-6491-9225 WOS: 000224606300005 This paper presents a fuzzy application to the area of load-frequency control (LFC) using fuzzy gain scheduling of PI controllers. The study has been designed for a two area interconnected power system. Using variable values for the proportional and integral gains in the controller unit, the dynamic performance of the system is improved. A comparison among a conventional PI controller, some other fuzzy gain scheduling controllers and the proposed fuzzy gain scheduling of PI (FGPI) controller is presented and it has been shown that the proposed FGPI controller can generate the best dynamic response following a step load change. (C) 2004 Elsevier Ltd. All rights reserved.

Cam, Ertugrul/0000-0001-6491-9225 WOS: 000226888800003 In this study, a fuzzy gain scheduled proportional and integral (FGPI) controller was developed to regulate and to improve the frequency deviation in a two-area electrical interconnected power system. Also, a conventional integral (I), a conventional proportional and integral (PI), and a fuzzy logic (FL), controllers were used to control the same power system for the performance comparison. Two performance criteria were utulized for the comparison. First, settling times and overshoots of the frequency deviation were compared. Later, the absolute error integral analysis method was calculated to compare all the controllers. All the models were simulated by Matlab 6.0-Simulink software. The simulation results show that the FGPI controller developed in this study performs better than the other controllers with respect to the settling time and overshoot, and absolute error integral of the frequency deviation. (C) 2004 Elsevier B.V. All rights reserved.

Fuzzy gain scheduling of proportional-integral (PI) controller are proposed for the area load-frequency control problem. Comparison study of conventional PI controller with proposed controller show that proposed controller can yield the best dynamic responses following a step load change.

This paper presents real-time application fuzzy control concept of a typical industrial plant whose performance is severally affected by disturbances and in particullar by changes in the operating point. This is typically the case for large coal fired power plants which can be treated as multivariable dynamic system. A short description of the power plant is given. For this power plant, a reduced matematical model is developped. The result of experimental modelling will be shortly discussed. The conventional control of this power plant is investigated and descirebed. Design of the fuzzy model-refence model controller used in the power plant for real time control is presented in theory. Realisation of the use of the fuzzy control is shown and the results of a three mounth plot installation of a decentralization fuzzy control algorithm for electrical power and enthalpy control of a 750 MW power plant are discussed and compared with those of the conventinal PID control.

This paper presents the reduced mathematical model for the power generation of a steam power plant. Plant measurements have been made for four different operating points. The dynamic model for these operating conditions of the multivariable plant have been developed by application of parameter estimation methods. Based on these multivariable models, three different types of adaptive control schemes as well as a conventional PID-control structure have been tested by extended simulation studies. Due to the very promising results, preparations for the practical application of the simulation results in the plant are now under work.

This paper describes the optimal tuning for the parameters of the power system stabilizer (PSS), which can improve the system damping performance within a wide region of operation conditions to enhance power system stability using artificial bee colony algorithm (ABC) based PSS instead of a conventional PSS and particle swarm optimization (PSO) based PSS. The parameters of the optimized PSS are obtained by minimizing a performance index based on integral of the absolute error (IAE) that shows steady state stability of power system. Single machine infinite bus (SMIB) system and two types of excitation system were used for the present work. The simulation results demonstrate that the proposed ABC based PSS performs well in damping and quicker response when compared with the other two PSSs.