Browsing by Author "Ceylan, Oğuzhan"

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Citation - WoS: 2
Citation - Scopus: 3
Active and Reactive Power Load Profiling Using Dimensionality Reduction Techniques and Clustering
(Institute of Electrical and Electronics Engineers Inc., 2019) Yetkin, E. Fatih; Ceylan, Oğuzhan; Papadopoulos, Theofilos A.; Kazaki, Anastasia G.; Barzegkar-Ntovom, Georgios A.; Business Administration; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
This paper proposes a methodology to characterize active and reactive power load profiles. Specifically, the approach makes use of fast Fourier Transform for conversion into frequency domain, principle component analysis to reduce the dimension and K-means++ to determine the representative load profiles. The data set consists of five-year measurements taken from the Democritus University of Thrace Campus. Test days were also classified as working and non-working. From the results it is observed that the proposed methodology determines representative load profiles effectively both regarding active and reactive power.
Citation - WoS: 6
Citation - Scopus: 10
An Adaptive Affinity Matrix Optimization for Locality Preserving Projection Via Heuristic Methods for Hyperspectral Image Analysis
(IEEE-Inst Electrıcal Electronıcs Engıneers Inc, 2019) Taşkın, Gülşen; Ceylan, Oğuzhan; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Locality preserving projection (LPP) has been often used as a dimensionality reduction tool for hyperspectral image analysis especially in the context of classification since it provides a projection matrix for embedding test samples to low dimensional space. However, the performance of LPP heavily depends on the optimization of two parameters of the graph affinity matrix: k-nearest neighbor and heat kernel width, when one considers an isotropic kernel. These two parameters might be optimally chosen simply based on a grid search. In case of using a generalized heat kernel where each feature is separately weighted by a kernel width, the number of parameters that need to be optimized is related to the number of features of the dataset, which might not be very easy to tune. Therefore, in this article, we propose to use heuristic methods, including genetic algorithm (GA), harmony search (HS), and particle swarm optimization (PSO), to explore the effects of the heat kernel parameters aiming to analyze the embedding quality of LPP's projection in terms of various aspects, including 1-NN classification accuracy, locality preserving power, and quality of the graph affinity matrix. The results obtained with the experiments on three hyperspectral datasets show that HS performs better than GA and PSO in optimizing the parameters of the affinity matrix, and the generalized heat kernel achieves better performance than the isotropic kernel. Additionally, a feature selection application is performed by using the kernel width of the generalized heat kernel for each heuristic method. The results show that very promising results are obtained in comparison with the state-of-the-art feature selection methods.
Akıllı Şebekeler ve Akıllı Toplum İçin Gelişmiş Evrimsel Hesaplamalar
(2020) Özdemir, Aydoğan; Ahmadı, Bahman; Ceylan, Oğuzhan; Younesı, Soheıl; 01. Kadir Has University
Elektrik ve enformasyon altyapılarının birleşimi ile oluşan akıllı şebekelerin (AŞ), geleceğin elektrik üretim, iletim ve dağıtım sistemlerinin, daha az karbon salınımı ile daha ekonomik ve güvenilir bir hizmet sağlamasında kilit rol oynaması beklenmektedir. Diğer yandan, dağılmış enerji kaynaklarının (DEK) yaygın bir şekilde elektrik dağıtım sistemlerine bağlanması ve serbestleştirme olguları, yeni işletim ve kontrol felsefeleri geliştirilmesini zorunlu kılmıştır. Bu projenin amacı, AŞ?nin belirtilen hesaplama ihtiyacını karşılamak üzere, gelişmiş evrimsel algoritma tabanlı çözümler sunmaktır. Bu kapsamda, iki temel göreve odaklanılması düşünülmüştür. ? Dağıtık enerji ve depolama kaynakları ve talep gelişimi dikkate alınarak dağıtım şebekesi geliştirme ve genişleme planları, ? Dağıtık enerji kaynakları ve depolama birimleri dikkate alınarak bara gerilim profillerinin iyileştirilmesi, yatırım ve işletme giderlerinin minimizasyonu, dağıtım şebeke kayıplarının azaltılması, güvenilirliğin arttırılması, gerilim ve reaktif güç kontrolü, uzun süreli arıza sonrası yeniden yapılandırma ve şebeke restorasyonu. Yukarıda belirtilen problemler, uygun amaç fonksiyonları ile modellenerek birer eniyileme (optimizasyon) problemi olarak ifade edilerek, çeşitli gelişmiş evrimsel algoritmalarla çözülmüşlerdir. Burada önerilen gelişmiş evrimsel hesaplamaların, alışılagelmiş çözüm tekniklerine göre şu temel farklılıkları içermektedir. ? Bu projede henüz daha çok yeni geliştirilen evrimsel algoritmalar ve bunların gelişmiş halleri olup, yerel arama destekleri ile birlikte, hızla ve yeteri doğrulukta çözüm veren tekniklerdir. ? Söz konusu algoritmalar, tüm yarı-optimal çözüm seçeneklerini veren güvenilir çözümler sağlamaktadır. ? Paralel/dağıtık hesaplama teknikleri ve/veya karma (memtic) algoritmalarla birlikte uygulanarak, gelişmiş evrimsel algoritma tabanlı çözümleri gerçekleşmiştir. Geliştirilen algoritmaların performansı, 33 bara, 69 bara ve 141 baralı test sisteminde denenmiş; fakat pandemi dönemi kısıtları nedeniyle BEDAŞ Elektrik şebekesinde uygulaması henüz tamamlanamamıştır.
Armoni Araması Yöntemi ile Elektrik Dağıtım Sistemlerinin Yeniden Yapılandırılması: Elektrikli Araçların Etkisi
(2019) Ceylan, Oğuzhan; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Bilindiği üzere son yirmi yılda elektrik güç sistemleri yoğun değişimler yaşamıştır. Elektrik piyasalarının yapısı değişmiş, tüm dünyada elektrik dağıtım sistemlerinde yenilenebilir enerji kaynaklarının ve elektrikli araçların (𝐸𝐴) kullanımı gün geçtikçe artmıştır. Pek çok ekonomik ve çevresel getirisi bulunan 𝐸𝐴’ların menzillerinin sınırlı olması, neredeyse her gün şarj edilmelerini gerektirmekte ve bu da elektrik güç sistemine ek yük getirmektedir. Bu çalışmada elektrik dağıtım sistemlerinde çok sayıda 𝐸𝐴 olması durumunda karşılaşılan gerilim problemleri ve kayıpları minimize etmek için yeniden yapılandırma yaklaşımı incelenmektedir. Eniyileme probleminin çözümü için armoni araması yöntemi (𝐴𝐴𝑌) kullanılmaktadır. Ortaya konan yaklaşımla, sistemde farklı sayıda 𝐸𝐴 ve dağıtık generatör olması durumları dikkate alınarak IEEE 33 bara test sisteminde çözülmekte ve ardından sonuçlara yer verilmektedir.
Citation - WoS: 6
Citation - Scopus: 9
Assessment of Harmonic Distortion on Distribution Feeders With Electric Vehicles and Residential Pvs
(IEEE, 2017) Ceylan, Oğuzhan; Paudyal, Sumit; Dahal, Sudarshan; Karki, Nava R.; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Power-electronic interfacing based devices such as photovoltaic (PV) panels and electric vehicles (EVs) cause voltage/current harmonic distortions on the power grid. The harmonic current profiles from EVs and PVs depend on the design of the controllers integrated to the PV inverters and EV chargers. Similarly the voltage and current harmonic distortions on a grid change throughout the day as the PV output power number of grid connected EVs and the other load pattern change. In this context we present harmonic assessment to demonstrate cumulative effect of large number of EVs and PVs on a medium voltage distribution grid. We will demonstrate the case studies on the IEEE 123-node distribution feeder with 20% 50% and 100% PV and EV penetrations based on time series simulations carried out for an entire day.
Blockchain Applications on Smart Grid a Review
(Kadir Has Üniversitesi, 2019) Koyunoğlu, Ali Sinan; Ceylan, Oğuzhan; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
In this study, energy transmission systems that are used from today's energy systems, ie non-renewable energy sources, transmission and distribution channels used in the process from the production of electric energy to consumption, the use of renewable energy sources and the use of smart network applications, in addition to these, the use of blockchain technology in these networks are mentioned. Along with the blockchain subarea, changes in the electricity market are described. In the energy market with Blockchain; consumers will be able to exchange energy between themselves and there will be no need for a third party, centralized structure. Therefore, the cost of energy distribution and transmission will be reduced. Blockchain technology will provide security in this market which will be formed by cheaper energy. In this study, these security measures based on criterion and hash system are mentioned. Furthermore, it is examined how the producers and consumers coming out of the market would affect the market price, when the Blockchain and smart grid systems are installed.Harmony search algorithm is used for to find optimal prices in the market when producers and consumers came out of the market. In addition, smart home and smart network applications are combined with other technologies in the near future, and new innovations are likely to arise
Citation - WoS: 2
Citation - Scopus: 6
Branch Outage Simulation Based Contingency Screening by Gravitational Search Algorithm
(Praise Worthy Prize Srl, 2012) Ceylan, Oğuzhan; Özdemir, Aydoğan; Dağ, Hasan; Advertising; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 04. Faculty of Communication; 01. Kadir Has University
Power systems contingency analysis is an important issue for electric power system operators. This paper performs branch outage simulation based contingency screening using a bounded network approach. Local constrained optimization problem representing the branch outage phenomena is solved by the gravitational search algorithm. The proposed method is applied to IEEE 14 30 57 and 118 Bus Test systems and its performance from the point of capturing violations is evaluated. In addition false alarms and the computational accuracy of the proposed method are also analyzed by using scattering diagrams. Finally the proposed gravitational search based contingency screening is compared with full AC load flow solutions from the point of computational speed. Copyright (C) 2012 Praise Worthy Prize S.r.l. - All rights reserved.
Citation - Scopus: 15
Branch outage solution using particle swarm optimization
(2008) Ceylan, Oğuzhan; Ozdemir, Aydogan; Dağ, Hasan; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
For post outage MW line flows and voltage magnitude calculations most of the methods use linear methods because of their simplicity. Especially for reactive power flow calculations one can face high errors. In this paper we use a minimization method that minimizes the errors resulting from the linear system model implementation. We solve the optimization problem using particle swarm optimization. We give some outage examples using IEEE 14 bus IEEE 30 bus and IEEE 57 bus data and compare the results with full ac load flow calculation. © 2008 Australasian Universities Power Engineering Conference (AUPEC'08).
Citation - WoS: 7
Citation - Scopus: 12
Comparative Study of Active Power Curtailment Methods of Pvs for Preventing Overvoltage on Distribution Feeders
(IEEE, 2018) Paudyal, Sumit; Bhattarai, Bishnu P.; Tonkoski, Reinaldo; Dahal, Sudarshan; Ceylan, Oğuzhan; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Overvoltage is one of the major issues on distribution grids with high penetration of photovoltaic (PV) generation. Overvoltage could be prevented through the control of active/reactive power of PVs. However given the high R/X ratio of low voltage feeders voltage control by using reactive power would not be as effective as using active power. Therefore active power curtailment (APC) of PVs though not desirable becomes necessary at times to prevent the overvoltage issues. Existing literature is rich in centralized and droop-based methods for APC and/or reactive power control of PVs to prevent overvoltage issues. In this context this paper revisits the most popular existing methods and evaluates the performance of droop-based and centralized methods using a typical North American 240 V low voltage feeder with 24 residential homes. In this work our key findings are: a) droop-based methods provided conservative solutions or did not eliminate the overvoltages completely b) power flow sensitivity based droop approach led to 13% more curtailment than the centralized approaches c) centralized approach had 40% less energy curtailed compared with standard droop while no overvoltages were observed and d) operating PVs at non-unity power factor in centralized approach led to 5% less energy curtailment.
Citation - WoS: 21
Citation - Scopus: 24
A Comparative Study of Metaheuristic Algorithms for Wave Energy Converter Power Take-Off Optimisation: A Case Study for Eastern Australia
(MDPI, 2021) Amini, Erfan; Golbaz, Danial; Asadi, Rojin; Nasiri, Mandieh; Ceylan, Oğuzhan; Nezhad, Meysam Majidi; Neshat, Mehdi; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
One of the most encouraging sorts of renewable energy is ocean wave energy. In spite of a large number of investigations in this field during the last decade, wave energy technologies are recognised as neither mature nor broadly commercialised compared to other renewable energy technologies. In this paper, we develop and optimise Power Take-off (PTO) configurations of a well-known wave energy converter (WEC) called a point absorber. This WEC is a fully submerged buoy with three tethers, which was proposed and developed by Carnegie Clean Energy Company in Australia. Optimising the WEC's PTO parameters is a challenging engineering problem due to the high dimensionality and complexity of the search space. This research compares the performance of five state-of-the-art metaheuristics (including Covariance Matrix Adaptation Evolution Strategy, Gray Wolf optimiser, Harris Hawks optimisation, and Grasshopper Optimisation Algorithm) based on the real wave scenario in Sydney sea state. The experimental achievements show that the Multiverse optimisation (MVO) algorithm performs better than the other metaheuristics applied in this work.
Citation - Scopus: 2
A Comparative Study of Surrogate Based Learning Methods in Solving Power Flow Problem
(IEEE, 2020) Ceylan, Oğuzhan; Taşkın, Gülsen; Paudyal, Sumit; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Due to increasing volume of measurements in smart grids, surrogate based learning approaches for modeling the power grids are becoming popular. This paper uses regression based models to find the unknown state variables on power systems. Generally, to determine these states, nonlinear systems of power flow equations are solved iteratively. This study considers that the power flow problem can be modeled as an data driven type of a model. Then, the state variables, i.e., voltage magnitudes and phase angles are obtained using machine learning based approaches, namely, Extreme Learning Machine (ELM), Gaussian Process Regression (GPR), and Support Vector Regression (SVR). Several simulations are performed on the IEEE 14 and 30-Bus test systems to validate surrogate based learning based models. Moreover, input data was modified with noise to simulate measurement errors. Numerical results showed that all three models can find state variables reasonably well even with measurement noise.
Citation - Scopus: 12
Comparison of Post Outage Bus Voltage Magnitudes Estimated by Harmony Search and Differential Evolution Methods
(2009) Ceylan, Oğuzhan; Özdemir, Aydoğan; Dağ, Hasan; Advertising; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 04. Faculty of Communication; 01. Kadir Has University
Contingency studies are indispensable tools of both the power system planning and operational studies. Real time implementation of operational problems makes necessary the use of high speed computational methods while requiring reasonable accuracies. On the other hand, accuracy of the results and the speed of calculation depend on branch outage modeling as well as solution algorithm used. This paper presents a comparison of post outage bus voltage magnitudes calculated by two meta-heuristic approaches; namely differential evolution (DE) and harmony search (HS) methods. The methods are tested on IEEE 14, IEEE 30, IEEE 57, and IEEE 118 bus test systems and the results are compared both in terms of accuracy and calculation speed.
Citation - WoS: 134
Citation - Scopus: 174
Coordinated Electric Vehicle Charging With Reactive Power Support To Distribution Grids
(IEEE, 2019) Wang, Jingyuan; Bharati, Guna R.; Paudyal, Sumit; Ceylan, Oğuzhan; Bhattarai, Bishnu P.; Myers, Kurt S.; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
We develop hierarchical coordination frameworks to optimally manage active and reactive power dispatch of number of spatially distributed electric vehicles (EVs) incorporating distribution grid level constraints. The frameworks consist of detailed mathematical models which can benefit the operation of both entities involved i.e. the grid operations and EV charging. The first model comprises of a comprehensive optimal power flow model at the distribution grid level while the second model represents detailed optimal EV charging with reactive power support to the grid. We demonstrate benefits of coordinated dispatch of active and reactive power from EVs using a 33-node distribution feeder with large number of EVs (more than 5000). Case studies demonstrate that in constrained distribution grids coordinated charging reduces the average cost of EV charging if the charging takes place at nonunity power factor mode compared to unity power factor. Similarly the results also demonstrate that distribution grids can accommodate charging of increased number of EVs if EV charging takes place at nonunity power factor mode compared to unity power factor.
Citation - Scopus: 5
Double Branch Outage Modeling and Its Solution Using Differential Evolution Method
(2011) Ceylan, Oğuzhan; Ozdemir, Aydogan; Dağ, Hasan; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Power system operators need to check the system security by contingency analysis which requires power flow solutions repeatedly. AC power flow is computationally slow even for a moderately sized system. Thus fast and accurate outage models and approximated solutions have been developed. This paper adopts a single branch outage model to a double branch outage one. The final constrained optimization problem resulted from modeling is then solved by using differential evolution method. Simulation results for IEEE 30 and 118 bus test systems are presented and compared to those of full AC load flow in terms of solution accuracy. © 2011 IEEE.
Citation - WoS: 2
Citation - Scopus: 2
Double Branch Outage Modeling and Simulation: Bounded Network Approach
(Elsevier Science, 2015) Ceylan, Oğuzhan; Özdemir, Aydoğan; Dağ, Hasan; Advertising; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 04. Faculty of Communication; 01. Kadir Has University
Energy management system operators perform regular outage simulations in order to ensure secure operation of power systems. AC power flow based outage simulations are not preferred because of insufficient computational speed. Hence several outage models and computational methods providing acceptable accuracy have been developed. On the other hand double branch outages are critical rare events which can result in cascading outages and system collapse. This paper presents a double branch outage model and formulation of the phenomena as a constrained optimization problem. Optimization problem is then solved by using differential evolution method and particle swarm optimization algorithm. The proposed algorithm is applied to IEEE test systems. Computational accuracies of differential evolution based solutions and particle swarm optimization based solutions are discussed for IEEE 30 Bus Test System and IEEE 118 Bus Test System applications. IEEE 14 Bus Test System IEEE 30 Bus Test System IEEE 57 Bus Test System IEEE 118 Bus Test System and IEEE 300 Bus Test System simulation results are compared to AC load flows in terms of computational speed. Finally the performance of the proposed method is analyzed for different outage configurations. (C) 2015 Elsevier Ltd. All rights reserved.
Citation - WoS: 4
Citation - Scopus: 5
Generic Dynamic Load Modelling Using Cluster Analysis
(IEEE, 2018) Barzegkar-Ntovom, Georgios A.; Ceylan, Oğuzhan; Papadopoulos, Theofilos A.; Yetkin, E. Fatih; Business Administration; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
In this paper a new generic load modelling procedure is proposed based on the application of cluster analysis on load model parameters identified from measured dynamic responses. The performance of the proposed approach is assessed using measurements obtained from a low-voltage laboratory scale test configuration. In order to develop robust generalized load models applicable to a wide range of operating conditions different load compositions operating conditions and voltage disturbances are considered in the analysis. The findings of this paper verify the validity of the proposed generic modelling procedure and indicate robust results using the proposed methodology.
Graph Optimized Locality Preserving Projection Via Heuristic Optimization Algorithms
(IEEE, 2019) Ceylan, Oğuzhan; Taşkın, Gülşen; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Dimensionality reduction has been an active research topic in hyperspectral image analysis due to complexity and non-linearity of the hundreds of the spectral bands. Locality preserving projection (LPP) is a linear extension of the manifold learning and has been very effective in dimensionality reduction compared to linear methods. However, its performance heavily depends on construction of the graph affinity matrix, which has two parameters need to be optimized: k-nearest neighbor parameter and heat kernel parameter. These two parameters might be optimally chosen simply based on a grid search when using only one representative kernel parameter for all the features, but this solution is not feasible when considering a generalized heat kernel in construction the affinity matrix. In this paper, we propose to use heuristic methods, including harmony search (HS) and particle swarm optimization (PSO), in exploring the effects of the heat kernel parameters on embedding quality in terms of classification accuracy. The preliminary results obtained with the experiments on the hyperspectral images showed that HS performs better than PSO, and the heat kernel with multiple parameters achieves better performance than the isotropic kernel with single parameter.
Citation - Scopus: 25
Gravitational Search Algorithm for Post-Outage Bus Voltage Magnitude Calculations
(2010) Ceylan, Oğuzhan; Ozdemir, Aydogan; Dağ, Hasan; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Branch outage problem is one of the key problems in power system security analysis. This paper solves branch outage problem using a bounded approach. Local constrained optimization problem in the bounded approach is solved by the gravitational search algorithm. Test results of IEEE 14 30 and 118 bus systems are compared to those of ac load flow method in terms of both accuracy and speed.
Citation - WoS: 22
Citation - Scopus: 34
Grey Wolf Optimizer for Allocation and Sizing of Distributed Renewable Generation
(Institute of Electrical and Electronics Engineers Inc., 2019) Ahmadi, Bahman; Ceylan, Oğuzhan; Özdemir, Aydoğan; Advertising; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 04. Faculty of Communication; 01. Kadir Has University
Increasing penetration of distributed energy resources (DERs) have brought operational and control philosophy changes in Smart Grids (SGs). Renewable energy based technologies are becoming more important due to their economic and environmental impacts. Distributed generations (DGs) in the form of small renewable energy resources such as solar photovoltaics (PVs) and Wind Turbines (WTs) are connected in radial distribution networks near to the loads. This paper presents optimal siting and sizing of distributed renewable energy resource to maintain voltage magnitude profiles. Bus voltage magnitude differences for each hour in a day of a distribution system are formulated as an objective function. Three consecutive days are taken into account representing the three seasons of a year. A new nature inspired algorithm Grey Wolf Optimizer (GWO) is used as a solution tool. The proposed formulation is applied to 33 bus and 69 bus radial distribution networks. MATLAB simulations are performed to validate the performance of the approach. Simulation results are discussed and compared with of the several available ones'.
Citation - WoS: 4
Citation - Scopus: 6
Harmony Search Algorithm Based Management of Distributed Energy Resources and Storage Systems in Microgrids
(MDPI, 2020) Ceylan, Oğuzhan; Sezgin, Mustafa Erdem; Goel, Murat; Verga, Maurizio; Lazzari, Riccardo; Kwaye, Marcel Pendieu; Sandroni, Carlo; Management Information Systems; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
Microgrids are composed of distributed energy resources (DERs), storage devices, electric vehicles, flexible loads and so on. They may either operate connected to the main electricity grid (on-grid operation) or separated from the grid (islanded operation). The outputs of the renewable energy sources may fluctuate and thus can cause deviations in the voltage magnitudes especially at islanded mode. This may affect the stability of the microgrids. This paper proposes an optimization model to efficiently manage controllable devices in microgrids aiming to minimize the voltage deviations both in on-grid and islanded operation modes. RSE Distributed Energy Resources Test Facility (DER-TF), which is a low voltage microgrid system in Italy, is used to verify the algorithm. The test system's data is taken through an online software system (REDIS) and a harmony search based optimization algorithm is applied to control the device parameters. The experimental results show that the harmony search based optimization approach successfully finds the control parameters, and can help the system to obtain a better voltage profile.