Ceylan, Oğuzhan
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Oğuzhan Ceylan
CEYLAN, OĞUZHAN
Ceylan, OĞUZHAN
Ceylan, Oguzhan
CEYLAN, Oğuzhan
Ceylan,Oguzhan
Oğuzhan CEYLAN
OĞUZHAN CEYLAN
C., Oguzhan
Ceylan,O.
C.,Oguzhan
Oguzhan, Ceylan
C., Oğuzhan
Ceylan, Oğuzhan
Ceylan O.
Ceylan, O.
O. Ceylan
Ceylan, Oğuzhan
Ceylan, O?uzhan
Oguzhan, C.
CEYLAN, OĞUZHAN
Ceylan, OĞUZHAN
Ceylan, Oguzhan
CEYLAN, Oğuzhan
Ceylan,Oguzhan
Oğuzhan CEYLAN
OĞUZHAN CEYLAN
C., Oguzhan
Ceylan,O.
C.,Oguzhan
Oguzhan, Ceylan
C., Oğuzhan
Ceylan, Oğuzhan
Ceylan O.
Ceylan, O.
O. Ceylan
Ceylan, Oğuzhan
Ceylan, O?uzhan
Oguzhan, C.
Job Title
Doç. Dr.
Email Address
Main Affiliation
Management Information Systems
Management Information Systems
03. Faculty of Economics, Administrative and Social Sciences
01. Kadir Has University
Management Information Systems
03. Faculty of Economics, Administrative and Social Sciences
01. Kadir Has University
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
7
AFFORDABLE AND CLEAN ENERGY
37
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
2
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
1
Research Products
13
CLIMATE ACTION
1
Research Products
15
LIFE ON LAND
1
Research Products
17
PARTNERSHIPS FOR THE GOALS
1
Research Products
Documents
107
Citations
1054
h-index
16
This researcher does not have a WoS ID.
Scholarly Output
78
Articles
23
Views / Downloads
461/3620
Supervised MSc Theses
3
Supervised PhD Theses
0
WoS Citation Count
437
Scopus Citation Count
694
WoS h-index
9
Scopus h-index
13
Patents
0
Projects
0
WoS Citations per Publication
5.60
Scopus Citations per Publication
8.90
Open Access Source
20
Supervised Theses
3
Google Analytics Visitor Traffic
| Journal | Count |
|---|---|
| 2021 56th International Universities Power Engineering Conference (Upec 2021): Powering Net Zero Emissions | 4 |
| 2019 54th International Universities Power Engineering Conference (UPEC) | 3 |
| 2018 53rd International Universities Power Engineering Conference (UPEC) | 3 |
| 2020 55th International Universities Power Engineering Conference (UPEC) | 2 |
| 59th International Universities Power Engineering Conference -- SEP 02-06, 2024 -- Cardiff, ENGLAND | 2 |
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Scholarly Output Search Results
Now showing 1 - 10 of 78
Conference Object Data-Driven Local Control Design for Dead Band Control of Load Tap Changers(IEEE, 2024) Savasci, Alper; Ceylan, Oguzhan; Paudyal, SumitThis study presents an off-line optimization-guided machine learning approach for coordinating the local control rules of on-load tap changers (OLTCs) and step-voltage regulators (SVRs). Based on a bang-bang control rule, these legacy devices autonomously regulate the feeder voltage around the nominal level by varying the tap position in the lower or raise direction. The characterizing parameter of the local control rule is the dead band, which affects the number of tap switching in operation and is directly related to the economical use life of the equipment. The bandwidth is typically set within a standard voltage range and is generally kept constant in daily operation. However, adjusting the bandwidth dynamically can prevent excessive tap switching while maintaining satisfactory voltage regulation for varying loading and distributed generation conditions. Our approach aims to set the bandwidth parameter systematically and efficiently through a machine learning-based scheme, which is trained with a dataset formed by solving the distribution network optimal power flow (DOPF) problem. The performance of learning the bandwidth parameter is demonstrated on the modified 33-node feeder, which is promising for integrated voltage control schemes.Conference Object Citation - WoS: 1Citation - Scopus: 3Feature Selection Using Self Organizing Map Oriented Evolutionary Approach(Ieee, 2021) Ceylan, Oguzhan; Taskin, GulsenHyperspectral images are the multidimensional matrices consisting of hundreds of spectral feature vectors. Thanks to these large number of features, the objects on the Earth having similar spectral characteristics can easily be distinguished from each other. However, the high correlation and the noise between these features cause a significant decrease in the classification performances, especially in the supervised classification tasks. In order to overcome these problems, which is known in the literature as Hughes's effects or curse of dimensionality, dimensionality reduction techniques have frequently been used. Feature selection and feature extraction methods are the ones used for this purpose. The feature selection methods aim to remove the features, including high correlation and noise, out of the original feature set. In other words, a subset of relevant features that have the ability to distinguish the objects is determined. The feature extraction methods project the high dimensional space into a lower-dimensional feature space based on some optimization criterion, and hence they distort the original characteristic of the dataset. Therefore, the feature selection methods are more preferred than the feature extraction methods since they preserve the originality of the dataset. Based on this motivation, an evolutionary based optimization algorithm utilizing self organizing map was accordingly modified to provide a new feature selection method for the classification of hyperspectral images. The proposed method was compared to well-known feature selection methods in the classification of two hyperspectral datasets: Botswana and Indian Pines. According to the preliminary results, the proposed method achieves higher performance over other feature selection methods with a very less number of features.Conference Object Citation - Scopus: 1Semi-Centralized Control of Distributed Generation in Smart Grids(IEEE, 2018) Ceylan, Oğuzhan; Pisica, Ioana; Paudyal, SumitThis paper proposes a semi-centralized intelligent control approach for voltage regulation in distribution grids based on sensitivity calculations. The model checks the voltage magnitudes of each end of each lateral in the system one by one then if any of these violates the allowed voltage magnitudes each node in a single lateral sends its reactive power capability and sensitivity information to the sensor located at the beginning node of that lateral. This information is sorted at the sensor and required voltage is computed and assigned to the bids one by one. This paper tests this approach on a modified 33 Node Distribution Test system with several renewable energy sources: photovoltaics (PVs) and wind turbines (WTs) and presents the numerical results based on a 15 minute resolution load data PV outputs and WT outputs.Conference Object Citation - WoS: 2Citation - Scopus: 3Active 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.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.Article Armoni Araması Yöntemi ile Elektrik Dağıtım Sistemlerinin Yeniden Yapılandırılması: Elektrikli Araçların Etkisi(2019) Ceylan, OğuzhanBilindiği 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.Article Citation - Scopus: 2Optimization of Mode in Distribution Electrical Grid by Using Renewable Energy Sources for Rural Energy Supply(IAEME Publication, 2018) Shokolakova, Shinar K.; Keshuov, Seitkazy A.; Saukhimov, Almaz A.; Tokhtibakiev, Karmel K.; Ceylan, Oğuzhan; Shuvalova, JelenaKazakhstan plans to support integration of renewable energy sources (RES). For instance according to [12] until 2020 it is planned to connect 53 RES with a total value of 2000 MW. From those 53 RES most of them will be located in rural areas and will be connected to electrical power distribution grid. Power losses is an important problem in Kazakhstan power systems and largest share of power losses are related to distribution system losses and are approximately 65 %. Using RES as distributed generators (DGs) in near future in order to reduce power losses may be one of the important tasks of Distribution System Operators (DSOs) of Kazakhstan. Approach of minimizing power losses may be applied by changing the injected/absorbed active and reactive powers at the points of DG connection [12]. This paper models the power losses optimization problem by using a recently developed heuristics based optimization model: Moth Flame Optimization (MFO). It solves the power loss minimization problem on a modified 33 bus electrical grid with DGS. © IAEME PublicationConference Object Citation - Scopus: 5Impacts of Load and Generation Volatilities on the Voltage Profiles Improved by Distributed Energy Resources(Institute of Electrical and Electronics Engineers Inc., 2020) Ahmedi, Bahman; Ceylan, Oğuzhan; Özdemir, AydoğanWeather-dependent distributed renewable energy sources such as photovoltaics (PVs) and wind turbines (WT) are increasingly being connected to distribution networks (DNs). Increased penetration of these intermittent sources brought the necessity of using energy storage systems (ESSs) to achieve the intended benefits. This study presents an optimization process to determine optimal numbers, sizes, locations and distributed energy resources (DERs) as well as to determine the optimal operating strategy of ESSs in a distribution network. The objective is to improve the voltage profile and to minimize the installation costs. The proposed multi-objective formulation problem is solved by using ant lion multi-objective optimization algorithm. At the second part of the study, optimal values are tested with monthly extreme distributions and the impacts of load and distributed generation volatilies on the voltage profiles which were determined by Pareto-optimal solution candidates are analysed. Simulations were performed on 33 bus radial distribution system using Matlab. Finally the benefits obtained by the optimal solutions with less risk are compared.Conference Object Citation - Scopus: 1Power Output Prediction of Wave Farms Using Fully Connected Networks(IEEE, 2021) Burramukku, Bhavana; Ceylan, Oguzhan; Neshat, MehdiOne of the most important factors in the amount of power generated by a wave farm is the Wave Energy Converters (WECs) arrangement along with the usual wave conditions. Therefore, forming an appropriate arrangement of WECs in an array is a significant parameter in maximizing power absorption. This paper focuses on developing a fully connected neural model in order to predict the total power output of a wave farm based on the placement of the converters, derived from the four real wave scenarios on the southern coast of Australia. The applied converter model is a fully submerged three-tether converter called CETO. Data collected from the test sites is used to design a neural model for predicting the wave farm's power output produced. A precise analysis of the WEC placement is investigated to reveal the amount of power generated by the wave farms on the test site. We finally proposed a suitable configuration of a fully connected neural model to forecast the power output with high accuracy.Article Citation - WoS: 3Citation - Scopus: 6Heuristic Optimization Approaches for Capacitor Sizing and Placement: a Case Study in Kazakhstan(Mdpi, 2022) Baimakhanov, Olzhas; Senyuz, Hande; Saukhimov, Almaz; Ceylan, OguzhanTwo methods for estimating the near-optimal positions and sizes of capacitors in radial distribution networks are presented. The first model assumes fixed-size capacitors, while the second model assumes controllable variable-size capacitors by changing the tap positions. In the second model, we limit the number of changes in capacitor size. In both approaches, the models consider many load scenarios and aim to obtain better voltage profiles by minimizing voltage deviations and active power losses. We use two recently developed heuristic algorithms called Salp Swarm Optimization algorithm (SSA) and Dragonfly algorithm (DA) to solve the proposed optimization models. We performed numerical simulations using data by modifying an actual distribution network in Almaty, Kazakhstan. To mimic various load scenarios, we start with the baseline load values and produce random variations. For the first model, the optimization algorithms identify the near-optimal positioning and sizes of fixed-size capacitors. Since the second model assumes variable-size capacitors, the algorithms also decide the tap positions for this case. Comparative analysis of the heuristic algorithms shows that the DA and SSA algorithms give similar results in solving the two optimization models: the former gives a slightly better voltage profile and lower active power losses.Article Citation - WoS: 37Citation - Scopus: 50A Multi-Objective Optimization Evaluation Framework for Integration of Distributed Energy Resources(Elsevier, 2021) Ahmadi, Bahman; Ceylan, Oguzhan; Ozdemir, AydoganRenewable distributed generation and energy storage systems (ESSs) have been a gamechanger for a reliable and sustainable energy supply. However, this new type of generation should be optimally planned and operated to maximize the expected benefits. In this regard, this paper presents a new formulation for optimal allocation and sizing of distributed energy resources and operation of ESSs to improve the voltage profiles and minimize the annual costs. The multi-objective multiverse optimization method (MOMVO) is used as a solution tool. Moreover, the resulting Pareto optimal solution set is minimized under economic concerns and cost sensitivity to provide a decision-support for the utilities. The proposed formulation and solution algorithm are tested for the revised 33-bus and 69-bus test systems where the load and renewable generation characteristics are taken from real Turkish data. When compared with the base case operating conditions, the proposed formulation eliminated all the voltage magnitude violations, and provided almost 50% loss reductions and 20% energy transfers to off-peak hours. Moreover, Pareto fronts of the proposed method are found to better than the ones provided by non dominated sorting genetic algorithm and multi-objective particle swarm optimization, according to two multi-objective optimization metrics.
