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A Comprehensive Research on Ensuring Energy Efficiency in Rail Systems
(Kırıkkale Üniversitesi, 2024) Arıkan, Yağmur; Akkaş, Özge Pinar; Çam, Ertuğrul
Today, the increase in energy needs and the risk of depletion of some energy resources is a worrying situation for sustainable life. Therefore, energy efficiency and prevention of energy losses are crucial. Transportation is one of the sectors where energy is used most intensively. As in every field, it is aimed to prevent the excessive use of energy in this sector. One of the most important activities in this regard is to encourage public transportation, and in this sense, rail systems are frequently preferred in big cities. However, their energy consumption is increasing due to the increasingly widespread network structure of these systems. Therefore, energy efficiency studies on these systems have a significant impact on clean and sustainable life and attract the attention of researchers. Energy efficiency studies in rail systems show a wide variety due to their complicated structure. In this paper, the concepts of energy consumption and efficiency in rail systems, studies on this subject in the literature and the technologies and methods used have been examined. The outputs of the paper have been evaluated in terms of energy efficiency and an assessment have been made for the future.
Actual-time modeling of a subway vehicle and optimal driving management with GA and ABC algorithms
(Academic Publication Council, 2022) Arıkan, Yağmur; Şen, Tolga; Çam, Ertuğrul
The optimization of operations of subway systems has critical importance in terms of energy efficiency and costs. Therefore, driving management of subway vehicles has been gaining more importance day by day. Optimal Driving Management (ODM) is the optimization of the velocity trajectory of a subway vehicle by considering operating conditions and travel time. In this study, the driving of a subway vehicle has been modeled dynamically with all parameters that affect driving. So, a realistic model has been prepared. Then, a new objective function has been proposed to reduce energy consumption by using the subway vehicle's acceleration and braking forces parameters for ODM. The Artificial Bee Colony algorithm (ABC) and Genetic algorithm (GA) have been used on the prepared model to determine the driving dynamics of the subway vehicle. The performance of the algorithms has been evaluated in the real line network, which has multiple stations with different characteristics. The energy consumption has been reduced by 10.47% in GA and 8.92% in ABC compared to the actual driving values. Moreover, the results of the study have been analyzed in terms of passenger comfort, cost, and emission values.
An adaptive control application in a large thermal combined power plant
(Pergamon-Elsevier Science Ltd, 2007) Kocaarslan, İlhan; Çam, Ertuğrul
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.
An Investigation Of Productivity In Boilers Of Thermal Power Plants With Fuzzy Gain Scheduled PI Controller
(Kırıkkale Üniversitesi, 2010) Kocaarslan, İlhan; Çam, Ertuğrul; Tiryaki, Hasan
Power plants need to be controled because of electricity generation cost and to be reduced corrosion of the equipmet used in them. For these reasons, special care has to be taken for their two outputs, settling time and overshoot, and their productivity. In this study, a fuzzy gain scheduled proportional-integral, FGPI, controller was designed to arrange the power and enthalpy outputs in two boilers with different productivity values of a 765 MW coal-fired thermal power plant. The simulation results show that the first boiler model (Model-1, M1) with 95% productivity has better preformance on the settling time of power and enthalpy outputs. As for the overshoots, the second boiler model (Model-2, M2) with 70% productivity has better performance for the two outputs.
An analysis of cracked beam structure using impact echo method
(Elsevier Sci Ltd, 2005) Çam, Ertuğrul; Orhan, Sadettin; Lüy, Murat
Defects influence in a negative way the service life of structures. Thus, detection of them even at a very small size is a very important point of view to guarantee structural safety and to safe costs. The objective of this study is to obtain information about the location and depth of cracks in cracked beams. For this purpose, the vibrations as a result of impact shocks were analyzed. The signals obtained in defect-free and cracked beams were compared in the frequency domain. The results of the study suggest to determine the location and depth of cracks by analyzing the from vibration signals. Experimental results and simulations obtained by the software ANSYS are in good agreement. (c) 2004 Elsevier Ltd. All rights reserved.
The Analysis Of Wind Data With Rayleigh Distribution And Optimum Turbine And Cost Analysis In Elmadağ,Turkey
(2015) Arıkan, Yağmur; Arslan, Özge Pınar; Çam, Ertuğrul
In this study, wind energy potential of Elmadağ region is analyzed statistically by using the data of wind speed that is measured hourly between 2012-2013 years, then economic analysis of wind investment in the region has been studied. Wind turbine parameters and wind speed distribution in the region play an important role to get energy. Therefore, firstly, Rayleigh statistical method is used for the research of region’s wind energy potential. Wind speed data of region, scale parameters value, energy density quantity, the most common wind speed, speed values that have maximum contribution to energy generation are calculated monthly and annually with this method. In the second part of the study, amount of energy generation and capacity factors are calculated annually by using three different turbines. Finally, cost analysis of investment is made by various calculation methods and economic profitability is calculated. According to results, the most convenient and profitable turbine is determined by comparison
Application of fuzzy logic for load frequency control of hydroelectrical power plants
(Pergamon-Elsevier Science Ltd, 2007) Çam, Ertuğrul
The quality of generated electricity in power systems is dependent on the system output, which has to be of constant frequency and must maintain the scheduled power and voltage. Therefore, load frequency control, LFC, is very important for power systems. However, the LFC problem in hydroelectrical power systems has received little attention by researchers so far. In this study, a conventional proportional integral (PI) controller and a fuzzy gain scheduled proportional integral (FGPI) controller have been compared for applying to a single area and a two area hydroelectric power plant, considering that Turkey has several hydro power sources. The comparison study indicated that the proposed FGPI controller has better performance than the conventional PI controller. The study results were compared by simulation. (c) 2006 Elsevier Ltd. All rights reserved.
Bidding and Operating Planning of a Virtual Power Plant in a Day-Ahead Market
(2020) Akkaş, Özge Pınar; Çam, Ertuğrul
In this study, it is aimed to determine the optimum bidding and operating planning of a Virtual Power Plant (VPP) in the energy market to obtain maximum profit. For this purpose, the VPP containing a Wind Power Plant (WPP), a Photovoltaic Power Plant (PVPP), and an Energy Storage System (ESS) is composed on the IEEE 6-bus test system with Distributed Generators (DGs). The bidding planning and operating scheduling of the components of the VPP participating in the Day-ahead Market (DAM) are decided hourly for a day. Thus, SGS is aimed to gain maximum profit. The proposed problem has been modeled as Mixed Integer Linear Programming (MILP) in GAMS software and solved with CPLEX solver to obtain optimum results. The obtained results show that the model is applicable and the method is valid.
Bir Termik Elektrik Santralinde Yapay Sinir Ağları Kontrolörün Etkilerinin İncelenmesi
(Kırıkkale Üniversitesi, 2009) Lüy, Murat; Kocaarslan, İlhan; Çam, Ertuğrul
Günümüzde geleneksel kontrol yöntemleri yerine modern kontrol yöntemleri bir çok güç sisteminin kontrolünde teorik yada pratik olarak uygulanmaktadır. Bu çalısmada, Yapay Sinir Agları (YSA) kontrol teknigi 765 MW’lık bir termik santralin güç ve entalpi çıkıslarını düzenlemek üzere dizayn edilip sisteme uygulanmıstır. Simülasyon sonuçlarına göre YSA kontrolör güç ve entalpi çıkıslarının oturma zamanları ve asma degerlerinde iyi sonuçlar göstermistir.
A classification mechanism for determining average wind speed and power in several regions of Turkey using artificial neural networks
(Pergamon-Elsevier Science Ltd, 2005) Çam, Ertuğrul; Arcaklıoğlu, Erol; Cavuşoğlu, Abdullah; Akbıyık, Bilge
In this paper, average wind speed and wind power values are estimated using artificial neural networks (ANNs) in seven regions of Turkey. To start with, a network has been set up, and trained with the data set obtained from several stations-each station gather data from five different heights-from each region, one randomly selected height value of a station has been used as test data. Wind data readings corresponding to the last 50 years of relevant regions were obtained from the Turkish State Meteorological Service (TSMS). The software has been developed under Matlab 6.0. In the input layer, longitude, latitude, altitude, and height are used, while wind speeds and related power values correspond to output layer. Then we have used the networks to make predictions for varying heights, which are not incorporated to the system at the training stage. The network has successfully predicted the required output values for the test data and the mean error levels for regions differed between 3% and 6%. We believe that using ANNs average wind speed and wind power of a region can be predicted provided with lesser amount of sampling data, that the sampling mechanism is reliable and adequate. (C) 2004 Elsevier Ltd. All rights reserved.
Creating Data Collection Device For Non-Intrusive Device Load Monitoring Method And Demand Side Management In Smart Grids
(Kırıkkale Üniversitesi, 2021) Güngüneş, Ramazan; Çam, Ertuğrul; Ateş, Volkan
In research on smart grids, it is seen that device load monitoring has a great effect on energy efficiency. The continuous increase in the demand for electrical energy, the fact that the use of electrical energy differs from household to household and the type of device used has increased the necessity of monitoring the amount of consumption.It is an important issue to make arrangements that will provide financial benefits in consumption without changing the usage habits of the end user and to offer alternative solutions that will lead the consumer to conscious use. Among these alternative solutions, there may be suggestions such as detailed reporting of consumption amounts and directing them to different tariff transitions.With the help of a data collection device with an optical port and a device connected to the existing electronic electricity meter, the instantaneous electricity consumption data of residential and industrial consumers are collected on a device called a central communication device. The collected data is stored both on a memory card on the device and on a remote server by being associated with the web server. In this way, a data set device was created for artificial intelligence-based decomposition methods to be performed with the non-invasive device load monitoring technique. At the same time, with an HMI screen developed in the study, it is ensured that the end consumer can monitor the amount of energy consumption instantly, and in this way, the ground has been prepared for a structure that will form the basis for consumption control and demand-side management systems with consumer participation.
Design and Real-time Implementation of Cable Fault Detector for Medium Voltage Underground Electricity Networks
(Kırıkkale Üniversitesi, 2022) Kaleli, Ali Rıza; Kılıç, Andaç; Munğan, Mehmet; Ak, Mehmet Akif; Çam, Ertuğrul
In this study, an underground cable fault diagnosis device was designed to detect faults in medium voltage underground cable electrical networks. It is aimed to detected the location of the fault with a pulse generator up to 40 kV by using the Pulse Reflection Method with this device. For this purpose , pulse generator with 2000 Joules pulse generator was designed in range of 0-8 kV, 0-16 kV and 0-32 kV. After the faulty phase is detected, the distance of the fault point too can be determined in meters with the Arc Reflection Method (ARM) with the device. For the pinpoint detection of the faulty place, a domestic and new pulse generator with 0-8 kV, 0-16kV and 0-32kV and 2.000 Joule energy, control unit, software and user interfaces were designed and implemented within the scope of this study. The device realized in the study has been properly placed and operated in a vehicle arranged within the scope of the project.
Detection of defects in a cantilever beam using modal test data
(2004) Çam, Ertuğrul; Lüy, Murat; Orhan, Sadettin
Bu çalışmanın amacı çatlaklı kirişlerde hasar yeri ve derinliği hakkında bilgi edinmektir. Bu amaçla kirişte darbe vuruşu sonucu oluşan titreşimler incelenmiştir. Hasarlı ve hasarsız kirişlerden elde edilen sinyal hem zaman hem de frekans ortamında karşılaştırılmıştır. Bu sonuçlar kullanılarak bir hasarın yeri ve derinliği titreşim sinyallerinden belirlenebilir.
Effects of Zero Velocity Update on Total Displacement for Indoor Inertial Positioning Systems
(2017) Ulamış, Faruk; Lüy, Murat; Çam, Ertuğrul; Uzun, İbrahim
In this paper; the effects of Zero Velocity Update method, which is one of the most important components of indoor inertial positioning systems, on total displacement is studied. For this purpose, acceleration and angular velocity measurements on three-axes are obtained by a low-cost foot-mounted inertial measurement unit while walking. The obtained acceleration values are processed and velocity and total displacement are estimated by using double integration. Velocity and displacement estimations were done at the end of each step with and without ZUPT algorithm and the results have been compared. Furthermore, in order to understand ZUPT algorithm well, a rectangular shape is plotted with the system containing IMU and microprocessor by stopping at every corner. ZUPT algorithm is implemented at each stop on the corners of the rectangular shape. The results are plotted in MATLAB. Effects of the errors on total displacement are pointed out
Electrical Vehicles Charging Coordination by Fuzzy Logical System
(Kırıkkale Üniversitesi, 2018) Kılıçarslan, Meral; Ateş, Volkan; Aydilek, Hüseyin; Çam, Ertuğrul
Today,with the rapid technological development, interest in electric vehicles is alsoincreasing. This raises the question of what the effects of the vehicles on theelectric power network will be. In this article, the adverse effects ofcharging scenarios of electric vehicles' batteries on the electric powernetwork are examined and fuzzy logic based solutions are proposed to prevent orreduce the effects of charging electric vehicles during peak hours. In thisarticle a fuzzy logic system that is providing the cheapest charging prices,also reducing the impact on the load curve of Turkey’s electrical network isprovided.
Elektrik Piyasasında Sanal Güç Santrali İşletiminin Optimizasyonu için Modelleme Önerisi
(Kırıkkale Üniversitesi, 2018) Akkaş, Özge Pinar; Arıkan, Yağmur; Çam, Ertuğrul
Elektrik piyasalarının serbestleşmesi ve çevresel sorunların artması sebebiyle yenilenebilir üretime dayalı dağıtık enerji kaynakları, güç sistemlerinde önemli bir yere sahip olmuştur. Yenilenebilir enerji kaynaklarının (YEK) enerji piyasasında yer alması YEK sahipleri için ciddi bir zorluk oluşturmaktadır. Bunun temel nedeni, yenilenebilir enerji kaynaklarının güç çıkışlarının belirsizliğidir. Örneğin, rüzgâr güç santrallerinin (RGS) güç çıkışı rüzgâr hızına, güneş enerji santrallerinin (GES) güç çıkışı güneş ışınımına ve bulutlanmaya göre değişmektedir. Bu da uzun veya orta vadeli elektrik dağıtım sözleşmelerini yerine getirememe riski taşımaktadır. Bu riski ortadan kaldırmak için, farklı türde yenilenebilen ve yenilenemeyen üretim birimleri ve depolama sistemleri birleştirilerek,elektrik piyasasında tek yönlü bir birim oluşturulur. Bu birim Sanal Güç Santralleri (SGS) olarak tanımlanmaktadır. Bu çalışmada, gün öncesi piyasasında elektrik satarak veya satın alarak faaliyet gösteren bir SGS sahibinin maksimum kâr elde edebilmesi amacıyla saatlik işletim planlaması modellenmiştir. Çalışmada ele alınan SGS, rüzgâr güç santrali, güneş enerji santrali, konvansiyonel güç santrali ve bir enerji depolama sisteminden oluşmaktadır. Problem, karışık tamsayı doğrusal olmayan problem olarak formülleştirilip, 24 saat zaman aralığı için uygulanmıştır ve GAMS yazılımında test edilmiştir. Önerilen yöntemin, gün öncesi piyasasında optimum satım/satın alma tekliflerini nasıl vereceği yönünde SGS sahibine yardımcı olacağı gösterilerek yöntemin uygulanabilirliği kanıtlanmıştır.
Elektrik Piyasasında Sanal Güç Santrali İşletiminin Optimizasyonu için Modelleme Önerisi
(2018) Akkaş, Özge Pınar; Arıkan, Yağmur; Çam, Ertuğrul
Elektrik piyasalarının serbestleşmesi ve çevresel sorunların artması sebebiyle yenilenebilir üretime dayalı dağıtık enerji kaynakları,güç sistemlerinde önemli bir yere sahip olmuştur. Yenilenebilir enerji kaynaklarının (YEK) enerji piyasasında yer alması YEKsahipleri için ciddi bir zorluk oluşturmaktadır. Bunun temel nedeni, yenilenebilir enerji kaynaklarının güç çıkışlarının belirsizliğidir.Örneğin, rüzgâr güç santrallerinin (RGS) güç çıkışı rüzgâr hızına, güneş enerji santrallerinin (GES) güç çıkışı güneş ışınımına vebulutlanmaya göre değişmektedir. Bu da uzun veya orta vadeli elektrik dağıtım sözleşmelerini yerine getirememe riski taşımaktadır.Bu riski ortadan kaldırmak için, farklı türde yenilenebilen ve yenilenemeyen üretim birimleri ve depolama sistemleri birleştirilerek,elektrik piyasasında tek yönlü bir birim oluşturulur. Bu birim Sanal Güç Santralleri (SGS) olarak tanımlanmaktadır. Bu çalışmada,gün öncesi piyasasında elektrik satarak veya satın alarak faaliyet gösteren bir SGS sahibinin maksimum kâr elde edebilmesi amacıylasaatlik işletim planlaması modellenmiştir. Çalışmada ele alınan SGS, rüzgâr güç santrali, güneş enerji santrali, konvansiyonel güçsantrali ve bir enerji depolama sisteminden oluşmaktadır. Problem, karışık tamsayı doğrusal olmayan problem olarak formülleştirilip,24 saat zaman aralığı için uygulanmıştır ve GAMS yazılımında test edilmiştir. Önerilen yöntemin, gün öncesi piyasasında optimumsatım/satın alma tekliflerini nasıl vereceği yönünde SGS sahibine yardımcı olacağı gösterilerek yöntemin uygulanabilirliğikanıtlanmıştır.
Fault Detection and Diagnosis Technic Using Electrical Characteristics of a PV Module and Machine Learning Classifier
(Kırıkkale Üniversitesi, 2020) Raslan, Mouhamed Aghiad; Çam, Ertuğrul
The growth of photovoltaic power plants is continuously rising, this growth would not be possible without safety, monitoring, and fault detection systems. In this paper, the common faults of a typical photovoltaic power plant that may occur in a photovoltaic module are discussed. Also, the paper studies the electrical characteristics of a photovoltaic module operating under several faults’ conditions applied on a specially designed module that measures the output current of each substring by utilizing sensitive Hall Effect sensors. After obtaining the electrical characteristics under faults, using machine learning, two decision trees classifier models are trained, the first classifier is trained to detect and recognize faults. However, this classifier may confuse the partial shading case with several other faults. Hence, the second decision tree classifier is trained to distinguish the exact fault type when the module is operating under partial shading condition by applying a short-circuit test on the photovoltaic module. This design can be achieved by connecting current sensors in the junction box of a typical photovoltaic module.
Fault Detection and Diagnosis Technic Using Electrical Characteristics of a PV Module and Machine Learning Classifier
(2020) Raslan, Mouhamed Aghiad; Çam, Ertuğrul
The growth of photovoltaic power plants is continuously rising, this growth would not be possible without safety, monitoring, and fault detection systems. In this paper, the common faults of a typical photovoltaic power plant that may occur in a photovoltaic module are discussed. Also, the paper studies the electrical characteristics of a photovoltaic module operating under several faults’ conditions applied on a specially designed module that measures the output current of each substring by utilizing sensitive Hall Effect sensors. After obtaining the electrical characteristics under faults, using machine learning, two decision trees classifier models are trained, the first classifier is trained to detect and recognize faults. However, this classifier may confuse the partial shading case with several other faults. Hence, the second decision tree classifier is trained to distinguish the exact fault type when the module is operating under partial shading condition by applying a short-circuit test on the photovoltaic module. This design can be achieved by connecting current sensors in the junction box of a typical photovoltaic module.
A fuzzy gain scheduling PI controller application for an interconnected electrical power system
(Elsevier Science Sa, 2005) Çam, Ertuğrul; Kocaarslan, İlhan
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.

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