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Öğe A COMPREHENSIVE AND COMPARATIVE EXPERIMENTAL ANALYSIS ON THERMAL CONDUCTIVITY OF TiO2-CaCO3/WATER HYBRID NANOFLUID: PROPOSING NEW CORRELATION AND ARTIFICIAL NEURAL NETWORK OPTIMIZATION(Begell House Inc, 2021) Ocal, Sultan; Gokcek, Murat; Colak, Andac Batur; Korkanc, MustafaIn this study, the thermal conductivity of TiO2-CaCO3/water hybrid nanofluid, which was prepared with five different concentrations and two-step method, was experimentally investigated. Thermal conductivity measurements were made using the KD2 Pro device at a temperature range from 10 degrees C to 60 degrees C. Using experimental data, a mathematical correlation and an artificial neural network model was developed in order to predict thermal conductivity depending on concentration and temperature. In the feed-forward back-propagation artificial neural network with 10 neurons in its hidden layer, the multilayer perceptron model was preferred. While the value of the coefficient of determination R for the proposed new mathematical correlation was 0.9999, it was obtained as 0.99913 for the artificial neural network model. The average error rate was calculated as 0.005% for the mathematical model and -0.02% for the artificial neural network.Öğe A techno-economic assessment of landfill gas emissions and energy recovery potential of different landfill areas in Turkey(Elsevier Sci Ltd, 2020) Kale, Cihangir; Gokcek, MuratLandfills are a widespread application for the management of municipal solid waste and the production of energy. However, landfill gas estimations, analysis of its energy capacity, and economic analyses need to be performed properly for a landfill project area. Although there are many gas prediction models in the literature, the default values in the model such as the methane production capacity (L-0) and the methane production rate (k) need to be recalculated according to the climate and waste composition of the region in order to obtain a more accurate gas estimation. Furthermore, the energy project from waste is expected to evaluate the through lifetime with variables (landfill operation, gas collection efficiency, different combustion engines, etc.) for an optimum plant capacity. In this study, it is aimed to investigate the landfill gas and methane production potential that can be obtained in landfill areas in different provinces of Turkey and to determine an optimum plant capacity by performing energy production cost analysis. To achieve this, the LandGEM 3.02 version was used to estimate long-term landfill gas potential in this study. The L-0 value was calculated by using the IPCC (Intergovernmental Panel on Climate Change) methodology, and the k value was determined by considering the meteorological data of the regions (precipitation amount, etc.). The future population of the selected regions was estimated using the arithmetic increase method. According to this estimation, the solid waste quantity to be generated in the future was calculated. Energy capacities of these areas were calculated using internal combustion reciprocating engines with six different capacities. The unit energy production cost was evaluated by employing the levelized cost method. The optimum plant capacity was found by evaluating the energy production costs obtained for each site and six different engines. As a result, it is observed that the energy production plant with the optimum capacity determined from waste is economically and ecologically feasible. (C) 2020 Elsevier Ltd. All rights reserved.Öğe An experimental and new study on thermal conductivity and zeta potential of Fe3O4/water nanofluid: Machine learning modeling and proposing a new correlation(Elsevier, 2023) Sahin, Fevzi; Genc, Omer; Gokcek, Murat; Colak, Andac BaturIt is important to predict the thermophysical properties of nanofluids, which have higher heat transfer perfor-mance compared to the base fluid, without the need for experimental studies. In this study, two different artificial neural networks were created to predict the thermal conductivity and zeta potential of Fe3O4/water nanofluid. The thermal conductivity and zeta potential of the Fe3O4/water nanofluid prepared at three different concen-trations were experimentally measured. An innovative mathematical correlation is proposed to calculate thermal conductivity based on temperature and concentration using the obtained experimental data. Considering that the correlations in the literature can generally be calculated according to concentration, the novelty of the proposed model stands out. The calculated values for thermal conductivity and zeta potential of the created artificial neural network and the new mathematical correlation were compared with the results of the experiments. In addition, a comprehensive performance analysis was made by calculating different performance parameters. The R values of the neural network models were above 0.99 and mean squared error values were obtained as 1.47E-05 and 1.58E-06, respectively. In addition, the mean deviation values calculated for the thermal conductivity of the network model were 0.03%, while it was 0.05% for the new mathematical correlation. The study results showed that ANN models can predict the thermal conductivity and zeta potential of Fe3O4/water nanofluid with high accuracy. The proposed new mathematical correlation was also found to have higher error rates compared to the ANN model, although it was able to calculate thermal conductivity values with high accuracy.Öğe Determining the best model for estimation the monthly mean daily global solar radiation on a horizontal surface - A case study in Nigde, Turkey(EMERALD GROUP PUBLISHING LTD, 2015) Gungor, Afsin; Gokcek, Murat; Yalcin, Fusun; Kocer, Abdulkadir; Yaka, Ismet Faruk; Sardogan, Gozde TugceKnowledge of the local solar radiation is important for many applications of solar energy systems. The global solar radiation on horizontal surface at the location of interest is the most critical input parameter employed in the design and prediction of the performance of solar energy systems. In this study, 3 empirical sunshine based models are compared correlating the monthly mean daily global solar radiation on a horizontal surface with monthly mean sunshine records for Nigde, Turkey. Models are compared using coefficient of determination (R-2), the root mean square error (RMSE), the mean bias error (MBE) and the t-statistic. According to our results, all the models fitted the data adequately and can be used to estimate the specific monthly global solar radiation. The t-statistic was used as the best indicator; this indicator depends on both, and is more effective for determining the model performance. The agreement between the estimated and the measured data were remarkable and the method was recommended for use in Nigde, Turkey.Öğe Efficiency of L-DOPA+TiO2 modified RO membrane on salinity gradient energy generation by pressure retarded osmosis(Pamukkale Univ, 2024) Ates, Nuray; Saki, Seda; Gokcek, Murat; Uzal, NigmetHarvesting energy from the salinity gradient of seawater and river water using pressure retarded osmosis (PRO) has been a major research topic of recent years. However, there is a need for efficient PRO membranes that can generate high power density and are pressure resistant, as the performance of current membranes on the market is poor. In this study, specific energy potential of PRO process using LDOPA+TiO2 modified BW30-LE membrane was evaluated on synthetic and real water samples. Polyamide BW30-LE RO membrane was modified by L-DOPA, L-DOPA+0.5 wt% TiO2 and L-DOPA+1 wt% TiO2. The effect of hydraulic pressure and temperature on generation of power density were evaluated for 5, 10, and 15 bar pressures, as well as 10 degrees C, 20 degrees C, and 30 degrees C degrees. The incorporation of TiO2 nanoparticles with L-DOPA increased the water flux by increasing the surface hydrophilicity and roughness of the membrane surface. The maximum specific power was observed as 1.6 W/m(2) for L-DOPA+1 wt% TiO2 modified BW30-LE membrane at 15 bar pressure. Besides, Mediterranean and Aegean, Black Sea water samples were used as draw solution and Seyhan, Ceyhan, Buyuk Menderes, Gediz, Yesilirmak, and Kizilirmak Rivers were used as feed solution. The highest osmotic power density was obtained by using L-DOPA+1 wt% TiO2 modified BW30-LE membrane with Ceyhan River as feed and Mediterranean Sea water as draw solution, which have the highest differences in salinity. In the mixture of Mediterranean and Ceyhan River, the highest power density was obtained at 10 bar pressure at 30 +/- 5 degrees C with 0.70 W/m(2).Öğe Evaluation of electricity generation and energy cost of wind energy conversion systems (WECSs) in Central Turkey(ELSEVIER SCI LTD, 2009) Gokcek, Murat; Genc, Mustafa SerdarThe negative effects of non-renewable fossil fuels have forced scientists to draw attention to clean energy sources which are both environmentally more suitable and renewable. Although Turkey enjoys fairly high wind energy potential, an investigation and exploitation of this source is still below the desired level. In this study which is a preliminary study on wind energy cost in Central Anatolian-Turkey, the wind energy production using time-series approach and the economic evaluation of various wind energy conversion systems (WECSs) enjoying the 2.5, 5, 10, 20, 30, 50. 100 and 150 kW rated power size using the levelised cost of electricity (LCOE) method for the seven different locations in Central Turkey were estimated. In addition, effects of escalation ratio of operation and maintenance cost and annual mean speed on LCOE are taken into account. The wind speed data for a period between 2000 and 2006 years were taken from Turkish State Meteorological Service (TSMS). According to the result of the calculations, it is shown that the WECS of capacity 150 kW produce the energy output 120,978 kWh per year in the Case-A (Pinarbasi) for hub height 30 m and also the LCOE varies in the range of 0.29-30.0 $/kWh for all WECS considered. (C) 2009 Elsevier Ltd. All rights reserved.Öğe Experimental performance investigation of minichannel water cooled-thermoelectric refrigerator(Elsevier, 2017) Gokcek, Murat; Sahin, FatihAn experimental performance analysis of minichannel water cooled-thermoelectric refrigerator in this study is presented. The cooling system of refrigerator is consists of two thermoelectric modules integrated with the minichannel heat sinks in its hot side and the heat dissipaters in its cold side. The experiments carried out for different system voltages and different flow rates of cooling water in the minichannel. The results show that the inner temperature of water cooled-thermoelectric refrigerator is about 2 degrees C for 0.8 L/min flow rate while it is about -0.1 degrees C for 1.5 L/min flow rate at the end of 2-h experiment. COP value of thermoelectric refrigerator is 0.23 in the flow rate 1.5 L/min while COP is 0.19 in the flow rate 0.8 L/min at the end of 25 min cooling times. When it comes to 8 V system voltages, COP of the thermoelectric refrigerator is about 0.41 at the end of 25 min operating period for the flow rate 1.5 L/min. This study concludes that the performance of minichannel heat sink used in this study has as good as other liquid water cooled systems used to absorb heat from thermoelectric modules hot side.Öğe From experimental data to predictions: Artificial intelligence supported new mathematical approaches for estimating thermal conductivity, viscosity and zeta potential in Fe3O4-water magnetic nanofluids(Elsevier, 2023) Sahin, Fevzi; Genc, Omer; Gokcek, Murat; Colak, Andac BaturMagnetic nanofluids (MNs) are considered advanced heat transfer fluids of the future due to their ability to function as intelligent fluids, with the applied external magnetic field effect being readily manageable. In this study, firstly, the stabilities of Fe3O4-water MNs prepared at 0.1, 0.25, 0.5, 0.75 and 1 mass ratios were determined by zeta potential measurement. The thermal conductivity and viscosities of MNs with appropriate stability were measured at 20-60 degrees C for all mass ratios. Secondly, using experimental data, two different artificial neural network (ANN) models were developed: one for thermal conductivity and viscosity depending on the temperature (20-60 degrees C) and mass ratio values and one for zeta potential depending on pH and mass ratio. Finally, using the obtained ANN data, two new mathematical correlations are proposed to predict thermal conductivity and viscosity. The study's results revealed that the developed ANN model has MSE and R values of 4.51E-06 and 0.99968, respectively, for thermal conductivity and viscosity of Fe3O4-water MNs can be accurately predicted by novel mathematical correlations.Öğe Hydrogen generation from small-scale wind-powered electrolysis system in different power matching modes(PERGAMON-ELSEVIER SCIENCE LTD, 2010) Gokcek, MuratThis study presents a techno-economic evaluation on hydrogen generation from a small-scale wind-powered electrolysis system in different power matching modes. For the analysis, wind speed data, which measured as hourly time series in Kirklareli, Turkey, were used to predict the electrical energy and hydrogen produced by the wind hydrogen energy system and their variation according to the height of the wind turbine. The system considered in this study is primarily consisted of a 6 kW wind-energy conversion system and a 2 kW PEM electrolyzer. The calculation of energy production was made by means of the levelized cost method by considering two different systems that are the grid-independent system and the grid-integrated system. Annual production of electrical energy and hydrogen was calculated as 15,148.26 kWh/year and 102.37 kg/year, respectively. The highest hydrogen production is obtained in January. The analyses showed that both electrical energy and hydrogen production depend strongly on the hub height of wind turbine in addition to the economic indicators. In the grid-integrated system, the calculated levelized cost of hydrogen changes in the range of 0.3485-4.4849 US$/kg for 36 m hub height related to the specific turbine cost. The grid-integrated system can be considered as profitable when the excess electrical energy delivered by system sold to the grid. (C) 2010 Professor T. Nejat Veziroglu. Published by Elsevier Ltd. All rights reserved.Öğe Location-based optimal sizing of hybrid renewable energy systems using deterministic and heuristic algorithms(Wiley, 2021) Demolli, Halil; Dokuz, Ahmet Sakir; Ecemis, Alper; Gokcek, MuratThe application of renewable energy sources in electrical energy generation is becoming widespread due to the decrease of installation costs and the increase of environmental concerns. Hybrid power generation systems are advantageous to meet the load demand, but optimal sizing is the main concern for having a cost-effective system based on given load demand and techno-economic indicators. This paper proposes a deterministic algorithm and utilizes genetic and artificial bee colony (ABC) optimization algorithms for optimal sizing of PV/battery and PV/WT/battery hybrid systems with minimum levelized cost of electricity (LCOE) constraint for two locations, Nigde and Bozcaada, in Turkey. The loss of power supply probability (LPSP) is used to build a reliable system and to make sure that the system produces required energy. Experimental results showed that optimal sizing of each location is different due to different wind and solar characteristics of locations. PV/battery model is more suitable for Nigde location with 1.22% LPSP and 0.1514 [$/kWh] LCOE, while PV/WT/battery model is more cost-efficient for Bozcaada location with 1.952% LPSP and 0.0872 [$/kWh] LCOE. Time performances of the algorithms are also investigated. It has been seen that the ABC algorithm has better performance and less execution time. This study demonstrated that heuristic algorithms are more applicable than deterministic algorithms, due to fast discovery of optimal solutions for hybrid renewable energy systems.Öğe Optimal sizing of off-grid hydrokinetic-based hybrid renewable power systems for a house load demand(Wiley-Hindawi, 2021) Gokcek, Murat; Kale, CihangirThe usage of stand-alone power systems represents an excellent choice for remote communities that are impossible to couple to the electricity distribution network practicably. The current research aims to design a no grid tied hybrid system on the basis of a PV-wind turbine-hydrokinetic turbine and diesel generator, for the purpose of meeting the electricity needs of a house near the Seyhan River, Turkey. A software that performs hybrid optimization of systems that can generate energy using different energy sources was utilized for modeling the operation of systems and identifying the appropriate architecture. In the current research, simulations were carried out for eight different (off-grid) power systems. The best optimized off-grid hybrid power system comprises a photovoltaic array of 7.87 kW, two wind turbines, one hydrokinetic turbine, a diesel generator of 7 kW, lead-acid batteries of 49 kWh, and a converter of 4.95 kW. The results of the present research demonstrated that the total net present cost was $161 327.08, while the levelized cost of electricity was $0.609/kWh for the optimized system. Furthermore, the renewable usage fraction and carbon dioxide emissions are 26.4% and 838.63 kg/year, respectively. In accordance with the simulation findings, the wind-hydrokinetic power system has higher levelized cost of electricity and total net present cost in comparison with other power generation systems.Öğe Optimum sizing of hybrid renewable power systems for on-site hydrogen refuelling stations: Case studies from Türkiye and Spain(Pergamon-Elsevier Science Ltd, 2024) Gokcek, Murat; Paltrinieri, Nicola; Liu, Yiliu; Badia, Eulalia; Dokuz, Ahmet Sakir; Erdogmus, Ayse; Urhan, Baki BarisOne of the main barriers to the adoption of fuel cell vehicles (FCEVs) is the limited availability of hydrogen refuelling stations (HRSs). The presence of these stations is crucial in facilitating the provision of fuel for FCEVs, which rely on hydrogen as a source of power generation. Renewable energy sources offer significant advantages for hydrogen production at these stations, as they are environmentally friendly and can reduce costs. In this study, it is provided a techno-economic analysis of an on -site hydrogen refuelling station powered by a hybrid renewable energy generation system using HOMER software in Nigde, Turkiye, and Zaragoza, Spain. Three different power system scenarios were evaluated to refuel 24 vehicles per day for each region throughout the year. The results of the analysis showed that the most optimal system architecture for Nigde was with a solar panel power generation system, with a levelized cost of hydrogen (LCOH) of 6.15 $/kg and the net present cost (NPC) of $6,832,393. The most optimal system architecture for Zaragoza was a wind turbine -photovoltaic panel power generation system, with an LCOH of 5.83 $/kg and NPC of $6,499,723. The annual amount of CO2 emissions avoided by using renewable resources in hydrogen production was calculated as 2,673,453 kg for Nigde and 2,366,573 kg for Zaragoza. The study also found that the cost of hydrogen production increases with decreasing the HRS production capacity. The use of renewable energy generation systems for hydrogen production will enable countries to achieve net -zero emission targets and reduce the need to import fossil fuels to meet energy demands in the transportation sector. The present study makes several contributions towards the achievement of the United Nations Sustainable Development Goals (3, 7, 11, and 13) and has the potential to facilitate the rapid adoption of FCEVs.Öğe Technical and economic evaluation of freshwater production from a wind-powered small-scale seawater reverse osmosis system (WP-SWRO)(ELSEVIER SCIENCE BV, 2016) Gokcek, Murat; Gokcek, Oznur BegumWind-powered desalination is an attractive and sustainable method for providing potable water in isolated arid and coastal zones and islands. In this study, a techno-economic analysis of a wind-powered small-scale seawater reverse osmosis system (WP-SWRO) is presented. Levelised unit costs for electricity and water (LCOE and LCOW) were estimated for Gokceada Island, Turkey. The energy requirement of the system showed that water can be produced at a cost between US$2.962 and US$6.457 $/m(3) for all wind turbines (with rated capacities ranging from 6 kW to 30 kW) at various discount rates when considering off-grid operations. For a grid connected-wind turbine system, the levelised cost of water was predicted to be in the range from US$0.866 to US$2.846/m(3). The levelised costs of electricity are predicted to be US$0.077 to US$0.155/kWh for an 8% discount rate using a 30-kW wind turbine based on the turbine-specific cost. According to the results from an emission reduction analysis, using a 30-kW wind turbine for a reverse osmosis system permits a reduction of 80.028 tonnes of CO2 annually. The results show that wind-powered potable water production is economically and technically reasonable for the site. (C) 2015 Elsevier B.V. All rights reserved.Öğe Techno-enviro-economic design of small-scale membrane-based seawater desalination systems integrated with hybrid autonomous renewable power systems(Wiley, 2024) Gokcek, Murat; Ozkan, FatmaThis article aims to search the technical, environmental, and economic model of an off-grid hybrid power generation system that supplies electricity to a seawater reverse osmosis (RO) system. Net present cost (NPC) and levelized cost of electricity (LCOE) values were used to determine the optimal system sizing powering a reverse osmosis desalination system for different sites where is located south and west coast of Turkiye. In the proposed power systems, PV panels, wind turbines, diesel generators, lead-acid batteries, and converters were used. In the instance where the lowest LCOE of 0.301$/kWh is calculated, the optimal system comprises of a 25.7 kW PV array, one wind turbine (rated at 10 kW), 152 kWh LA batteries, and a 6.76 kW converter. The levelized cost of water (LCOW) value for this case was calculated as 1.168 $/m(3). The LCOE value was calculated as 0.529 $/kWh for the power system, which is considered as a base case and consists of only a diesel generator, where no renewable energy source is used. For the base case, the carbon footprint of electricity generation is 35,127 kg/year. According to CO2 sequestration analysis result, the number of trees (Pinus Brutia) to be planted was calculated as approximately 164 tree/year over the lifetime of the power system for base case.Öğe Towards a Sustainability Framework for Hydrogen Refuelling Stations: a Risk-Based Multidisciplinary Approach(Italian Association of Chemical Engineering - AIDIC, 2023) Paltrinieri, Nicola; Yamamoto, Toshiyuki; Rusin, Andrzej; Sala, Roser; Liu, Yiliu; Sato, Hitomi; Gokcek, MuratSustainable hydrogen technology is becoming increasingly important as the world moves towards cleaner and more sustainable sources of energy. Hydrogen is a clean and versatile energy carrier that has the potential to play a critical role in the transition to a low-carbon economy. However, to realize this potential, significant technological advancements are needed in the production, storage, and distribution of hydrogen. To achieve these advancements, a multidisciplinary approach is required that involves technical, organizational, social, and economic factors. Sustainable hydrogen technology development is a complex and multifaceted process that requires the integration of various perspectives and expertise. A framework is needed to bring together these perspectives and develop a common approach to assessing risks and opportunities associated with hydrogen technology. This contribution proposes a framework addressing system modelling and analysis issues in clean hydrogen production and storage, with a focus on uncertainties that can impact social, economic, and environmental sustainability of hydrogen production and refueling facilities. By using risk-based performance and degradation models, the framework helps prevent and mitigate accidents and builds organizational safety culture and procedures while better communicating with the public. The framework also identifies optimal operational modes for increasing the feasibility of hydrogen refueling stations, ultimately leading to the development of more efficient, reliable, and lower-cost hydrogen-based technologies. The development of a common risk-based framework promotes sustainable hydrogen technology and identifies new opportunities for growth and collaboration. The framework is developed collaboratively through an international research network. By integrating multiple perspectives and disciplines, the framework can provide a roadmap for the development of sustainable hydrogen technology and create opportunities for future growth and development in the field. Copyright © 2023, AIDIC Servizi S.r.l.Öğe Wind power forecasting based on daily wind speed data using machine learning algorithms(Pergamon-Elsevier Science Ltd, 2019) Demolli, Halil; Dokuz, Ahmet Sakir; Ecemis, Alper; Gokcek, MuratWind energy is a significant and eligible source that has the potential for producing energy in a continuous and sustainable manner among renewable energy sources. However, wind energy has several challenges, such as initial investment costs, the stationary property of wind plants, and the difficulty in finding wind-efficient energy areas. In this study, long-term wind power forecasting was performed based on daily wind speed data using five machine learning algorithms. We proposed a method based on machine learning algorithms to forecast wind power values efficiently. We conducted several case studies to reveal performances of machine learning algorithms. The results showed that machine learning algorithms could be used for forecasting long-term wind power values with respect to historical wind speed data. Furthermore, the results showed that machine learning-based models could be applied to a location different from model-trained locations. This study demonstrated that machine learning algorithms could be successfully used before the establishment of wind plants in an unknown geographical location whether it is logical by using the model of a base location.
