Oğuzhan Ceylan

Ceylan, Oğuzhan

Name Variants

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

Job Title

Doç. Dr.

Email Address

oguzhan.ceylan@khas.edu.tr

ORCID ID

0000-0002-0892-6380

Scopus Author ID

26665865200

Full item page

Scholarly Output

64

Articles

19

Citation Count

362

Supervised Theses

1 Scholarly Output Search Results

Now showing 1 - 10 of 58

Citation Count: 6
Comparative Study of Active Power Curtailment Methods of PVs for Preventing Overvoltage on Distribution Feeders
(IEEE, 2018) Ceylan, Oğuzhan; Bhattarai, Bishnu P.; Tonkoski, Reinaldo; Dahal, Sudarshan; Ceylan, Oğuzhan
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 Count: 4
Cuckoo search algorithm for optimal siting and sizing of multiple distributed generators in distribution grids
(IEEE, 2019) Ceylan, Oğuzhan; Ceylan, Oguzhan; Ozdemir, Aydogan
Distribution networks (DNs) are facing numerous challenges such as variability of demands, environmental issues, high power losses, and fluctuating v oltage p rofiles. Distributed energy resources (DERs) are becoming more important due to their economic and environmental impacts. This paper presents optimal siting and sizing of the Photovoltaics (PVs) and Wind Turbines (WTs) to improve the voltage magnitude profiles. This planning problem is formulated using DER generation and load profiles of the three representative days, one for each season. The resulting constrained optimization problem is solved using Cuckoo Search Algorithm (CSA). The proposed solution approach is applied to the 33 bus and 69 bus radial distribution networks. Several simulations are performed for the performance analysis of the methods and the results are compared to several available ones.
Citation Count: 2
Recycling Newton-Krylov algorithm for efficient solution of large scale power systems
(Elsevier Sci Ltd, 2023) Ceylan, Oğuzhan; Ceylan, Oguzhan
Power flow calculations are crucial for the study of power systems, as they can be used to calculate bus voltage magnitudes and phase angles, as well as active and reactive power flows on lines. In this paper, a new approach, the Recycling Newton-Krylov (ReNK) algorithm, is proposed to solve the linear systems of equations in Newton-Raphson iterations. The proposed method uses the Generalized Conjugate Residuals with inner orthogonalization and deflated restarting (GCRO-DR) method within the Newton-Raphson algorithm and reuses the Krylov subspace information generated in previous Newton runs. We evaluate the performance of the proposed method over the traditional direct solver (LU) and iterative solvers (Generalized Minimal Residual Method (GMRES), the Biconjugate Gradient Stabilized Method (Bi-CGSTAB) and Quasi-Minimal Residual Method (QMR)) as the inner linear solver of the Newton-Raphson method. We use different test systems with a number of busses ranging from 300 to 70000 and compare the number of iterations of the inner linear solver (for iterative solvers) and the CPU times (for both direct and iterative solvers). We also test the performance of the ReNK algorithm for contingency analysis and for different load conditions to simulate optimization problems and observe possible performance gains.
Citation Count: 0
Graph optimized locality preserving projection via heuristic optimization algorithms
(Institute of Electrical and Electronics Engineers Inc., 2019) Ceylan, Oğuzhan; Taşkin, G.
Dimensionality reduction has been an active research topic in hyperspectral image analysis due to complexity and nonlinearity 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. © 2019 IEEE.
Citation Count: 0
Parallel Contingency Analysis Using Differential Evolution Based Solution For Branch Outage Problem
(IEEE, 2010) Dağ, Hasan; Ceylan, Oğuzhan; Özdemir, Aydoğan
Contingency analysis is one of the most fundamental work an electricity management center operator has to perform regularly. If both bus voltage magnitudes and reactive power flowing on the branches during any type of outages are within the acceptable limits the system is called secure. In this paper we solve the contingency problem using a recently developed local constrained optimization based branch outage problem. The optimization problem resulted from the formulation of branch outage is solved by differential evolution method. Using Matlab's parallel computing toolbox contingency analysis for IEEE 300 test system is performed and the results are presented. The study shows that it is straight forward to implement contingency analysis on the Matlab's parallel environment and obtain near linear speedups.
Citation Count: 0
Optimization of Graph Affinity Matrix with Heuristic Methods in Dimensionality Reduction of Hypespectral Images
(IEEE, 2019) Ceylan, Oğuzhan; Taşkın, Gülşen
Hyperspectral images include hundreds of spectral bands, adjacent ones of which are often highly correlated and noisy, leading to a decrease in classification performance as well as a high increase in computational time. Dimensionality reduction techniques, especially the nonlinear ones, are very effective tools to solve these issues. Locality preserving projection (LPP) is one of those graph based methods providing a better representation of the high dimensional data in the low-dimensional space compared to linear methods. However, its performance heavily depends on the parameters of the affinity matrix, that are k-nearest neighbor and heat kernel parameters. Using simple methods like grid-search, optimization of these parameters becomes very computationally demanding process especially when considering a generalized heat kernel, including an exclusive parameter per feature in the high dimensional space. The aim of this paper is to show the effectiveness of the heuristic methods, including harmony search (HS) and particle swarm optimization (PSO), in graph affinity optimization constructed with a generalized heat kernel. 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 heat kernel with a single parameter.
Citation Count: 8
Voltage Profile Improving and Peak Shaving Using Multi-type Distributed Generators and Battery Energy Storage Systems in Distribution Networks
(Institute of Electrical and Electronics Engineers Inc., 2020) Ceylan, Oğuzhan; Ceylan, Oğuzhan; Özdemir, Aydoğan
Optimal sizing and siting of distributed generation (DG) units play an important role for improving voltage profile and reducing power losses. Moreover, battery energy storage system (BESS) units may help peak shaving. This paper presents a two stage approach, first of which aims optimal DG unit allocation, and second aims to determine optimal location and operation of BESS units. The problem formulation adopted due to the regulations in Turkey that supports DG units (Photovoltaics-PVs and Wind Turbines-WTs) with maximum unit size of 1 MW. A recently developed heuristic optimization method named as Harris hawks optimization (HHO) algorithm is used for obtaining near optimal solutions. We tested the developed model by using 33 and 141 bus distribution test systems.
Smart methods in electrical distribution systems: Minimization of voltage deviations
(Kadir Has Üniversitesi, 2021) Ceylan, Oğuzhan; Ceylan, Oğuzhan
Mevcut elektrik dağıtım sistemlerini, günümüzde artan enerji ihtiyacı doğrultusunda daha verimli hale getirmek amacıyla akıllı dağıtım sistemleri kavramı ortaya çıkmıştır. Bu tezde, elektrik dağıtım sistemlerinde voltage sapmasını sezgisel algoritmalar kullanarak en küçükleştirmeye çalışan çalışmalar incelenmiştir. Literatürde de kullanılan, Gri Kurt Optimizasyon algoritması (GWO), Balina Optimizasyon algoritması (WOA) ve Karınca Aslanı Optimizasyon (ALO) algoritmaları kullanılarak yük akış testleri 33 baralı, 69 baralı ve 141 baralı test sistemlerinde çalıştırılmış ve gerilim değerlerinde iyileşmeler görülmüştür. Bu tezin amacı, elektrik dağıtım sistemlerindeki gerilim sapmalarını en aza indirme problemi için meta-sezgisel algoritmalar kullanan açık kaynaklı bir yazılım aracı geliştirmektir. Yazılımın kullanıcısı, gerilim sapmalarını en küçükleştirmek için iki seçeneğe sahiptir, bunlardan ilkinde dağıtık üretim kaynakları ve kademe değiştiriciler kullanılır, ikincisinde ise bataryalar ve kademe değiştiriciler kullanılır. Kullanıcı optimizasyon öncesinde 33 bus, 69 bus ve 141 bus test sistemlerinden birini ve GWO, WOA ve ALO algoritmalarından birini seçebilir. Kullanıcı kendi yük profilini yükleyebilir. Sistemdeki dağıtık üretim kaynaklarının, bataryaların ve kademe değiştiricilerin adetleri program üzerinden ayarlanabilir. Optimizasyonun kaç iterasyon ve tur süreceği de ayarlanabilmektedir. Optimizasyon sonucunda kullanıcıya ana durum ve optimize edilmiş durum arasındaki değişim, bataryalardaki 24 saatlik güç durum değişimi, 24 saatlik kademe değiştirici değerleri değişimi grafikleri gösterilir.
Citation Count: 2
Energy Loss Minimization with Parallel Implementation of Marine Predators Algorithm
(Institute of Electrical and Electronics Engineers Inc., 2021) Ceylan, Oğuzhan; Ahmadi, B.; Ceylan, O.; Ozdemir, A.
Distribution network (DN) service continuity is one of the significant issues in today's power systems. This paper aims to put a strategy for supplying loads with less discontinuity and affordable energy-consuming. The energy loss in distribution grids causes many problems for the producer and consumer; hence, it needs to be improved to increase supply efficiency accordingly. For this aim a model aiming to minimize power losses by allocating and sizing distributed generators (DGs) is solved using recently developed Marine Predators Algorithm (MPA). Since the proposed method is a time-intensive process due to the vast computations, parallel computation is implemented into MPA to increase computation speed. The proposed formulation and parallel computation are tested for 69-bus radial distribution system. The results are discussed in terms of computational accuracy and solution efficiency. Moreover, the convergence characteristics of MPA are compared with some other heuristic methods. © 2021 Chamber of Turkish Electrical Engineers.
Citation Count: 97
Coordinated Electric Vehicle Charging With Reactive Power Support to Distribution Grids
(IEEE, 2019) Ceylan, Oğuzhan; Bharati, Guna R.; Paudyal, Sumit; Ceylan, Oğuzhan; Bhattarai, Bishnu P.; Myers, Kurt S.
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.