Makale Koleksiyonu
Bu koleksiyon için kalıcı URI
Güncel Gönderiler
Öğe An inclusive physico-chemical perspective on food waste: Textural and morphological structure(Elsevier Ltd, 2023) Çelebi, Hakan; Bahadır, Tolga; Bilican, IsmailIn recent years, thanks to their advantages such as low cost, easy availability, reusability as adsorbent materials, and high metal ion removal capacities in aqueous solutions, food waste attract the attention of researchers. In this study, almond shell (AS), peanut shell (PS), walnut shell (WS), and pumpkin seed hull (PSH) were characterized using analytical methods such as Fourier Transform Infrared (FTIR) Spectroscopy, Scanning Electron Microscope (SEM)/Energy dispersed X-ray (EDX), and Brunauer–Emmett–Teller (BET). The surface morphologies, functional groups, surface area, and pore size of AS, PS, WS, and PSH were evaluated together, and their specific properties were revealed. According to EDX analysis, %C and %O content is high for all biosorbents. Using FTIR analysis, carboxylic (–COOH), amines (N–H) and hydroxyl groups (–OH) in the structure of AS, WS, PS, and PSH were determined. Pore morphologies were determined as mesopore (250 nm) for AS, PS, WS, and PSH. Surface areas for AS, PS, WS and PSH were determined as 6.20, 4.12, 3.98 and 2.74 m2/g, respectively. In addition, using the Principal Component Analysis (PCA) model, the effect levels of AS, PS, WS, and PSH on the adsorption process were determined by FTIR and EDX data sets. With the increasing interest in environmental preservation, it is anticipated that low-cost food waste-based biosorbents will be utilized in various applications in the future.Öğe Modeling of Electric Vehicles as A Load of the Distribution Grid(Society of Automotive Engineers Turkey, 2023) Aslan, Nurullah; Kılıç, Erdal; Şekkeli, MustafaElectric vehicles (EVs) are expected to reduce carbon emissions from transportation. For this reason, many vehicle manufacturers, countries and international organizations develop their energy and transportation policies in this direction and also support them with practices. As a result of the policies implemented and developments in battery technologies, serious increases are expected in the sales of the EV sector. However, there should be sufficient charging stations for EV charging. The increase in charging stations is expected to cause some positive and negative effects on the grid. In order for electric vehicles to be more acceptable in terms of power systems, it is necessary to understand what kind of electrical character they show. In this article, EV electrical modeling is performed over a charging period by Monte Carlo Simulation using the actual charging data of some EV models charged in a single phase 7, 2 kW-240 V charger. The generated probabilistic model was validated by comparing it with real data. Thus, a reliable modeling has been presented for EV, which is a new load in power systems.Öğe Adoption of Electric Vehicles: Purchase Intentions and Consumer Behaviors Research in Turkey(SAGE Publications Inc., 2023) Durmuş Şenyapar, Hafize Nurgül; Akıl, Murat; Dokur, EmrahElectric vehicles (EVs) hold promise for attaining sustainable development objectives and mitigating the effects of global climate change due to their substantial benefits, such as high energy efficiency and low carbon emissions. Research on purchase intentions and behaviors may accelerate the adoption of EVs. Considering that the number of studies on EVs increases in tandem with the size of the market and that mutual interaction supports this two-way growth, conducting studies on consumer behavior in this area in countries where the electric vehicle market is developing, such as Turkey, will provide valuable insights for both the industry and the government. In this study, published articles on the consumer behavior of current and potential purchasers of electric vehicles were analyzed on the axis of Turkey, and the trend of academic studies in the literature was systematized from a holistic standpoint. Co-citation, co-keyword, geographical, and thematic analysis were applied to articles about EV consumer behaviors published between 2004 and 2022 in journals indexed by WoS, Scopus, TR Index, and DergiPark. The results of this study can inform numerous inter-disciplinary studies and researchers on the consumer behavior of electric vehicles. The bibliometric analysis of academic studies on electric vehicle consumers not only closes the market’s knowledge gap and accelerates the adoption process by increasing consumer awareness, but also provides industry representatives and policymakers with insights for the expansion of the EV market.Öğe Analysis of Consumer Behavior towards Electric Vehicles: Intentions, Concerns, and Policies(Gazi Üniversitesi, 2023) Durmuş Şenyapar, Hafize Nurgül; Akıl, MuratDespite the acceptance of electric vehicles (EVs) by consumers in developed countries, consumers' intentions towards these smart devices (SD) and the steps that can be taken to expand in this market continue to be investigated in developing countries such as Turkey. In this study, policies and incentives for the purchase of Electric Vehicles in different countries were examined, consumer concerns before the adoption of SDs were evaluated, and then consumer intentions in adopting EVs with models such as reasoned action theory, planned behavior theory, and technology acceptance model were evaluated with bibliometric analysis through conducted studies. Data from 63 publications accessed from Scopus, Web of Science, and DergiPark databases were used in the field mapping process. The results provide insights into increasing the market share of electric vehicles, which are critical in reducing the carbon footprint, by recommending the issues that need to be highlighted to the industry and researchers.Öğe Smart coordination of predictive load balancing for residential electric vehicles based on EMD-Bayesian optimised LSTM(IET - Institution of Engineering and Technology, 2022) Akıl, Murat; Dokur, Emrah; Bayındır, RamazanThe charging load forecasting of residential Electric Vehicles help grid operators make informed decisions in terms of scheduling and managing demand response. The residence can include integrated residential appliances with multi-state and high-frequency features. For this reason, it is difficult to estimate the total load of residence accurately. To overcome this problem, this paper proposes a hybrid forecasting model using the empirical mode decomposition and Bayesian optimised Long Short-Term Memory for load balancing based on residential electricity meter data. The residential electricity meter data includes three datasets as Electric Vehicle, heat pump and photovoltaic system. To decompose of the data characteristics, the empirical mode decomposition method performs to the original data. Then, the Bayesian optimised Long Short-Term Memory is applied to forecast for each sub-component of the data sequentially. The main features of the proposed model include a significant improvement in prediction accuracy and capture the local maximums. The advantage of the proposed method over existing methods are also verified over with experiments of data-driven on the IEEE 33 busbar test system. The result of simulation forecasting model indicates that predict closely the busbar outflow power, voltage drop, transformer loading states and power losses to compare with actual load model.Öğe Modeling and evaluation of SOC-based coordinated EV charging for power management in a distribution system(Türkiye Klinikleri, 2022) Akıl, Murat; Dokur, Emrah; Bayındır, RamazanThe importance of using clean energy in electrical energy generation and transportation network planning has recently increased due to carbon footprint rising. In this direction, the use of electric vehicles (EV), known as ultra-low carbon emission vehicles, has become widespread in addition to renewable energy sources (RES) such as wind and photovoltaic (PV) power generations. The trend of EVs to be preferred the primary means of transport has revealed the effects of charging an additional load on the grid. There is a need to create coordinated charging methods by considering the approaches for real-time charging models of EVs. In this paper, SOC-based EV coordinated charging was proposed for power management to prevent adverse effects including transformer overload, instantaneous peak loading and line overload in the existing distribution network. The proposed coordinated EV charging method was tested on the modified Roy Billinton test system (RBTS) Bus 2 network. AC 11 kW uncoordinated charging units have been respectively 123.76% distribution transformer and 115.16% distribution line overloading for 500 EVs on the grid with 13,9% diversity factor. However, these values that are 72.05% of distribution transformer and 67.01% of distribution grid overloading according to permittable level were decreased by the proposed coordinated charging method. Also, the state of charge (SOC) based coordinated method can increase 3.5% rate the diversity factor of charging capacity at the charging station with PV and battery energy system (BES) while ensured grid stability and energy efficiency.Öğe The soc based dynamic charging coordination of evs in the pv-penetrated distribution network using real-world data(MDPI, 2021) Akil, Murat; Dokur, Emrah; Bayındır, RamazanA successful distribution network can continue to operate despite the uncertainties at the charging station, with appropriate equipment retrofits and upgrades. However, these new investments in the grid can become complex in terms of time and space. In this paper, we propose a dynamic charge coordination (DCC) method based on the battery state of charge (SOC) of electric vehicles (EVs) in line with this purpose. The collective uncoordinated charging profiles of EVs charged at maximum power were investigated based on statistical data for distances of EVs and a real dataset for charging characteristics in the existing grid infrastructure. The proposed strategy was investigated using the modified Roy Billinton Test System (RBTS) performed by DIgSILENT Powerfactory simulation software for a total 50 EVs in 30 different models. Then, the load balancing situations were analyzed with the integration of the photovoltaic (PV) generation and battery energy storage system (BESS) into the bus bars where the EVs were fed into the grid. According to the simulation results, the proposed method dramatically reduces the effects on the grid compared to the uncoordinated charging method. Furthermore, the integration of PV and BESS system, load balancing for EVs was successfully achieved with the proposed approach.
