Browsing by Author "Ceylan, Ceren"

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Citation - WoS: 86
Citation - Scopus: 105
Design and Simulation of the Pv/Pem Fuel Cell Based Hybrid Energy System Using Matlab/Simulink for Greenhouse Application
(Pergamon-elsevier Science Ltd, 2021) Ceylan, Ceren; Ceylan, Ceren; Devrim, Yilser; Devrim, Yılser; Ceylan, Ceren; Devrim, Yılser; Energy Systems Engineering; Energy Systems Engineering
In this study, design and optimization of the hybrid renewable energy system consisting of Photovoltaic (PV)/Electrolyzer/Proton Exchange Membrane Fuel Cell (PEMFC) was investigated to provide electricity and heat for Greenhouse in Sanhurfa (Turkey). The coupling of a photovoltaic system with PEMFC was preferred to supply continuous production of electric energy throughout the year. Additionally, produced heat from PEMFC was used to heating of the greenhouse by micro cogeneration application. The MATLAB/Simulink was applied to the design and optimization of the proposed hybrid system. In the designed system, solar energy was selected to produce the Hydrogen (H-2) required to run the electrolyzer. In cases where the solar energy is not sufficient and cannot meet the electricity requirement for the electrolyzer; the H-2 requirement for the operation of the PEMFC was met from the H-2 storage tanks and energy continuity was ensured. The electrolyzer was designed for H-2 demand of the 3 kW PEMFC which were met the greenhouse energy requirement. PEMFC based hybrid system has 48% electrical and 45% thermal efficiencies. According to optimization results obtained for the proposed hybrid system, the levelized cost of energy was found 0.117 $/kWh. The obtained results show the proposed PV/Electrolyzer/PEMFC hybrid power system provides an applicable option for powering stand-alone application in a self sustainable expedient. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Citation - WoS: 54
Citation - Scopus: 65
Green Hydrogen Based Off-Grid and On-Grid Hybrid Energy Systems
(Pergamon-elsevier Science Ltd, 2023) Ceylan, Ceren; Devrim, Yilser; Energy Systems Engineering
This study aims to evaluate a green hydrogen (H2) based hybrid energy system (HES) from solar and wind renewable energy sources. The proposed HES contains PV panels, wind turbines and a proton exchange membrane water electrolyzer. Meteorology data such as solar radiation, temperature and wind speed were obtained from Atilim University Incek Campus Meteorology Station (Ankara, Turkey). The designed HES has been examined as both grid-connected and off-grid. In the grid-connected system, the electricity requirement of the load is supplied by the sun and wind, and the surplus energy produced is stored by producing H2 using an electrolyzer. In the off-grid HES, the electricity requirement of the load is completely provided by the proton exchange membrane fuel cell (PEMFC). In this system, the electrolyzer produces the H2 needed by the PEMFC with the energy provided by solar and wind energy. According to the results, 20,186 kWh of energy is produced annually in the on-grid and 3273 sm3 of H2 is stored. The off-grid system is investigated for Design-1 and Design-2 using two different wind turbine (WT) rated power. In Design-1 and Design-2, annually 95,145 kWh and 83,511 kWh of energy are produced annually 17,942 sm3 and 14,370 sm3 H2 are stored, respectively. When the on-grid and off-grid systems are examined; levelized cost of energy (LCOE) was calculated as 0.223 $/kWh for the on-grid system and 0.416 $/kWh and 0.410 $/kWh for Design-1 and Design-2 for off-grid systems, respectively. (c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Güneş Esaslı Hibrit Güç Sistemlerinin Tasarımı ve Optimizasyonu
(2020) Ceylan, Ceren; Ceylan, Ceren; Devrim, Yılser; Ceylan, Ceren; Devrim, Yılser; Devrim, Yılser; Energy Systems Engineering; Energy Systems Engineering
Gelişen teknoloji ve artan Dünya nüfusuyla birlikte enerji talebi de artmaktadır. Fosil yakıtların günden güne tükenmesi nedeniyle, temiz enerji üretmek için yenilenebilir enerji kaynaklarını kullanılmaya başlanmıştır. En çok tercih edilen yenilenebilir enerji kaynağı olan güneş enerjisi bulutlu günlerde ve gecelerde kullanılamaz. Ayrıca güneş enerjisinin en büyük dezavantajı depolanma sorunun olmasıdır. Bu şartlarda enerji ihtiyacını karşılamak ve sürekliliği sağlamak için yakıt pilleri kullanılır. Kısa başlangıç sürelerinin olması ve yüksek verimlilikleri nedeniyle yakıt pilleri popüler hale geldi. Evrende en çok bulunan element olan Hidrojen (H2), yakıt pillerinde yakıt olarak kullanılır. H2 enerji kaynağı değildir ancak çok iyi bir enerji taşıyıcısıdır. Yakıt olarak kullanıldığında su ya da su buharı ortaya çıkar. Enerji üretimi sırasında, çevreyi kirleten ve sera etkisini arttıran kimyasallar ve zararlı gazlar yoktur ve bu da çevre dostu olduğunu kanıtlar. Bu tez çalışmasında, Şanlıurfa'da bulunan bir seranın enerji ihtiyacını karşılamak için günde 5 saat çalıştırılacak olan 2.4 kW Proton Değişim Membran Yakıt Pili (PEMFC) tasarlanmıştır. PEMFC'nin gereksinimi olan H2'yi üretmek için elektrolizör dizayn edilmiş ve elektrolizörün çalışması için gerekli olan elektrik 80 adet fotovoltaik (PV) modülden sağlanmıştır. Sistemde üretilen H2 PEMFC'de kullanılmak üzere tanklarda depolanır. Tasarlanan sistemde bir yılın sonunda toplam 430 kg H2 depolanmıştır. Bunun yanı sıra PEMFC çalışırken ısı ortaya çıkar ve bir günlük çalışmada yaklaşık olarak 20 kW ısı üretilmektedir. Bu ısı PEMFC'nin güvenliği ve yüksek verimliliğin sağlanması için uzaklaştırılmalıdır. Tasarlanan sistemde PEMFC tarafından üretilen ısı bir ısı değiştiricisi yardımıyla uzaklaştırılmaktadır. Bu işlemde ısı uzaklaştırılması ile ısınan PEMFC soğutma suyunun sıcaklığı 34 oC'ye kadar düşerken, seranın ısınması için kullanılacak suyun ısısını 61 oC'ye kadar çıkarılmıştır. Yatırım, işletme ve bakım maliyetinin, hibrit enerji sisteminin çalışma süresince ürettiği enerji miktarına oranı seviyelendirilmiş enerji maliyetini verir. Bu sisteminin seviyelendirilmiş enerji maliyeti 1.77 $/kWh olarak hesaplanmıştır.
Precision Forecasting for Hybrid Energy Systems Using Five Deep Learning Algorithms for Meteorological Parameter Prediction
(Elsevier Sci Ltd, 2025) Ceylan, Ceren; Yumurtaci, Zehra; Energy Systems Engineering
The intermittent nature of renewable energy sources necessitates accurate power production forecasting to ensure system sustainability and balance between energy supply and demand. Although the deep learning-based meteorological forecasting is significantly studied in literature, most of the current literature applies single-algorithm based on each individual energy source and less multi-algorithm based on comparative studies on multiple architectures as applied to integrated hybrid systems. In addition, most of the research uses the same algorithmic solution to all the meteorological parameters without identifying parameter-specific optimization potential, and recent research is verified on actual future time steps instead of historical train-test split. This study presents a comprehensive comparative analysis of five deep learning algorithms, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and CNN-LSTM hybrid, for forecasting critical meteorological parameters (wind speed, ambient temperature, and solar radiation) that determine energy output in a wind and solar-based hybrid energy system (HES). Using five years of Istanbul meteorological data (2018-2022), optimal algorithms were systematically identified for each parameter through rigorous hyperparameter optimization and cross-validation. Key results demonstrate that GRU achieves superior performance in wind speed prediction (RMSE: 0.049 m/s, R2: 0.8634) and solar radiation forecasting (RMSE: 0.146 W/m2, R2: 0.6643), while CNN-LSTM excels in ambient temperature prediction (RMSE: 0.011 degrees C, R2: 0.9976). The integrated approach predicted annual hybrid system energy production with 89 % accuracy, demonstrating 0.48 % deviation from observed values. Most significantly, our framework successfully forecasted sixth year (2023) energy production with 1.55 % error, validating its real-world applicability. This research contributes to the methodological advancement of renewable energy forecasting by systematically identifying optimal algorithmic approaches for different meteorological parameters in hybrid systems, thereby supporting the integration of intermittent renewable sources into sustainable energy infrastructures.