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
Ceylan, Oğuzhan
Ceylan, O?uzhan

Job Title

Doç. Dr.

Email Address

oguzhan.ceylan@khas.edu.tr

Main Affiliation

Management Information Systems

ORCID ID

0000-0002-0892-6380

Scopus Author ID

26665865200

Full item page

Scholarly Output

67

Articles

19

Citation Count

362

Supervised Theses

3 Scholarly Output Search Results

Now showing 1 - 10 of 35

Citation - Scopus: 5
Double Branch Outage Modeling and Its Solution Using Differential Evolution Method
(2011) Ceylan, Oğuzhan; Dağ, Hasan; Ozdemir, Aydogan; Ceylan, Oğuzhan; Dağ, Hasan
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: 0
Citation - Scopus: 1
Power Output Prediction of Wave Farms Using Fully Connected Networks
(IEEE, 2021) Burramukku, Bhavana; Ceylan, Oğuzhan; Ceylan, Oguzhan; Neshat, Mehdi
One 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.
Citation - WoS: 2
Citation - Scopus: 4
Heuristic Optimization Approaches for Capacitor Sizing and Placement: a Case Study in Kazakhstan
(Mdpi, 2022) Baimakhanov, Olzhas; Ceylan, Oğuzhan; Senyuz, Hande; Saukhimov, Almaz; Ceylan, Oguzhan
Two 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.
Citation - WoS: 31
Citation - Scopus: 43
A Multi-Objective Optimization Evaluation Framework for Integration of Distributed Energy Resources
(Elsevier, 2021) Ahmadi, Bahman; Ceylan, Oğuzhan; Ceylan, Oguzhan; Ozdemir, Aydogan
Renewable 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.
Armoni Araması Yöntemi ile Elektrik Dağıtım Sistemlerinin Yeniden Yapılandırılması: Elektrikli Araçların Etkisi
(2019) Ceylan, Oğuzhan
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.
Blockchain Applications on Smart Grid a Review
(Kadir Has Üniversitesi, 2019) Koyunoğlu, Ali Sinan; Ceylan, Oğuzhan; Ceylan, Oğuzhan
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: 0
Citation - Scopus: 0
Optimization of Multilevel Inverters Using Novelty-driven Multi-verse Optimization Algorithm
(IEEE, 2021) Ceylan, Oğuzhan; Neshat, Mehdi; Mirjalili, Seyedali
All over the world, renewable energy technologies which need power electronics based inverters in their designs are becoming more and more popular, thus detailed analysis to test the operational efficiency is required. This paper utilizes a new adaptive Multi-verse Optimization (MVO) Algorithm combined with novelty search method to solve harmonic elimination problem in multilevel inverters. We compare the obtained numerical simulations to those obtained by using the grey wolf optimization and standard MVO algorithm. The numerical simulations are performed on 7, 11, and 15 level inverters with different modulation indexes. From the simulation results, we observe that adaptive novelty search Multi-verse Optimization (MVO) based approach was able to obtain less total harmonic distortion for different modulation indexes.
Citation - WoS: 2
Citation - Scopus: 2
Double Branch Outage Modeling and Simulation: Bounded Network Approach
(Elsevier Science, 2015) Ceylan, Oğuzhan; Dağ, Hasan; Özdemir, Aydoğan; Ceylan, Oğuzhan; Dağ, Hasan; Özdemir, Serpil
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: 6
Citation - Scopus: 9
A Heuristic Methods-Based Power Distribution System Optimization Toolbox
(Mdpi, 2022) Ceylan, Oğuzhan; Baimakhanov, Olzhas; Saukhimov, Almaz; Ceylan, Oguzhan
This paper proposes a toolbox for simulating the effective integration of renewable energy sources into distribution systems. The toolbox uses four heuristic methods: the particle swarm optimization (PSO) method, and three recently developed methods, namely Gray Wolf Optimization (GWO), Ant Lion Optimization (ALO), and Whale Optimization Algorithm (WOA), for the efficient operation of power distribution systems. The toolbox consists of two main functionalities. The first one allows the user to select the test system to be solved (33-, 69-, or 141-bus test systems), the locations of the distributed generators (DGs), and the voltage regulators. In addition, the user selects the daily active power output profiles of the DGs, and the tool solves the voltage deviation problem for the specified time of day. The second functionality involves the simulation of energy storage systems and provides the optimal daily power output of the resources. With this program, a graphical user interface (GUI) allows users to select the test system, the optimization method to be used, the number of DGs and locations, the locations and number of battery energy storage systems (BESSs), and the tap changer locations. With the simple user interface, the user can manage the distribution system simulation and see the results by making appropriate changes to the test systems.
Citation - Scopus: 0
Post-outage state estimations for outage management
(IFAC Secretariat, 2011) Ceylan, Oğuzhan; Dağ, Hasan; Ozdemir, Aydogan; Ceylan, Oğuzhan; Dağ, Hasan
Real time outage information is required to the utility operators for outage management process. In addition to some basic information regarding the outage post-outage system status will help to improve the response to outages and management of system reliability. This paper presents particle swarm optimization based reactive power estimations for branch outages. Post outage voltage magnitudes and reactive power flows results for IEEE 14 and IEEE 30 bus systems are given. Simulation results show that post outage voltage magnitudes and reactive power flows can be computed with a reasonable accuracy. © 2011 IFAC.