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SRMs have high torque ripples. Modifying the stator and rotor shape of SRMs is one of their methods to remove torque ripples. In this study, new rotor and stator geometries have been proposed for SRM. Performance characteristics are obtained and dynamic analyses are carried out for both novel and classical 6/4 SRMs. FFT analyses of the torque characteristics are also performed for the both SRMs. The changes in performance and the FFT results of torque characteristics are determined for both the current-controlled and uncontrolled operations in both SRMs. 23.60% and 15.20% improvements in torque ripples are achieved for the uncontrolled and current-controlled operations in SRMs respectively. When the FFT analyses are applied to the torque characteristics, the THD values are obtained as 21.19% and 8.31% in the uncontrolled and controlled motor current operations respectively. A 122 W three-phase 6/4 SRM simulation based on the MATLAB–SIMULINK environment is performed to validate the improvement of the torque ripple of the proposed model.

Poly(ethylene oxide) (PEO)-based polymer electrolytes are a promising class of materials for use in lithium-ion batteries due to their high ionic conductivity and flexibility. In this study, the effects of polymer architecture including linear, star, and hyperbranched and salt (lithiumbis(trifluoromethanesulfonyl)imide (LiTFSI)) concentration on the glass transition (Tg), microstructure, phase diagram, free volume, and bulk viscosity, all of which play a significant role in determining the ionic conductivity of the electrolyte, have been systematically studied for PEO-based polymer electrolytes. The branching of PEO widens the liquid phase toward lower salt concentrations, suggesting decreased crystallization and improved ion coordination. At high salt loadings, ion clustering is common for all electrolytes, yet the cluster size and distribution appear to be strongly architecture-dependent. Also, the ionic conductivity is maximized at a salt concentration of [Li/EO ≈ 0.085] for all architectures, and the highly branched polymers displayed as much as three times higher ionic conductivity (with respect to the linear analogue) for the same total molar mass. The architecture-dependent ionic conductivity is attributed to the enhanced free volume measured by positron annihilation lifetime spectroscopy. Interestingly, despite the strong architecture dependence of ionic conductivity, the salt addition in the highly branched architectures results in accelerated yet similar monomeric friction coefficients for these polymers, offering significant potential toward decoupling of conductivity from segmental dynamics of polymer electrolytes, leading to outstanding battery performance.

© 2022 The Author(s)Battery energy storage systems (BESS) are essential for flexible and reliable grid performance as the number of renewable energy sources in grids rises. The operational life of the batteries in BESS should be taken into account for maximum cost savings, despite the fact that they are beneficial for economical grid operation. In this context, this paper present a new battery cycle counting perspective for energy management of grid-connected BESS. For this purpose battery\"s one full charge–discharge cycle characteristic is compared with the operating battery charge–discharge cycle every time step. This comparison was explained mathematically and graphically in detail. The results are compared with the rain flow counting method which is the most popular cycle counting algorithm. Consequently, this cycle counting approach successfully counts the battery charge/discharge cycles and it has shown that has an advantage for BESSs due to being specifically developed just for batteries.

The cold filter plugging point (CFPP) value of biodiesel fuel blends need to be improved because of it has been reported that utilizing high concentrations of biodiesel blends in cold climates can cause major issues. Therefore, the main objective of the study is to improve CFPP value of biodiesel blends using ethyl proxitol additive. It is also to examine combustion and emission of the blends behavior. Biodiesel blends were prepared as; 5% ethyl proxitol-10% biodiesel-85% ultra-low sulfur diesel (ULSD) named as E5B10 and 5% ethyl proxitol-20% biodiesel-75% ULSD named as E5B20 fuel. These fuel blends were compared with ULSD fuel in a compression ignition engine at a constant engine speed of 1500 rev/min and four different loads (idle, 1, 2, and 3 bar BMEP) of eddy current dynamometer. The addition of ethyl proxitol led to a decrease in in-cylinder pressure and temperature due to an about 1˚ later SOC and 2˚ earlier EOC compared to ULSD. The pressure rise rate was slightly higher compared to ULSD at both low and high loads, with a difference of about 1 bar per degree. As a result, these blends with improved CFPP value can be used in cold climates.

Fotovoltaik (FV) modüller, üzerine düşen güneş ışınlarından elektrik üretimini sağlayan ve yüzeyinde birden çok FV hücre bulunan yapılardır. FV hücreler, sadece direkt gelen ışınları değil, yüzeye gelen tüm ışığın belirli dalgaboyu aralığını enerji üretimi için kullanabilirler. FV modüller, yapıları gereği sıcaklıkları, ortam sıcaklığına kıyasla daha fazla olmakta ve bu durum FV hücrelerin elektriksel verim ve güç üretim düşümüne neden olmaktadır. Bu sebeple, FV modüllerde depolanan ısı enerjisinin dışarıya transferi konusunda akademik çalışmalar son yıllarda ivme kazanmıştır. Örneğin, FV modüllerden ısı enerjisi elde edilerek sıfır enerji tüketim hedefi altında konutların ısıtma yükü karşılanmakta ve ilerleyen çalışmalar ile birlikte sistem/enerji verimi arttırılmaktadır. Bu çalışma, FV modüllerin ısı iletim performansının geliştirilmesine yönelik polimer esaslı takviye malzemelerin kullanımı ile oluşturulan kompozit yapılar incelenerek, FV modülde depolanan ısı enerjisinin azaltılmasını hedef almıştır. Bu amaçla, takviye malzemeler araştırılmış ve karbon, cam elyaf, aramid (kevlar) takviye malzemelerinin iki farklı parametre altında araştırılması uygun görülmüştür. Bu iki parametre, herbir takviye malzemenin farklı tabaka kalınlıklarındaki ve birbirleri ile oluşturduğu hibrit yapıdaki sahip oldukları ısı iletim performansını araştırmaktadır. Araştırma sonucunda karbon elyaf takviye malzemesi ile oluşturulan yapının 6,51 W/mm2 ısı akısı ile birlikte optimum yapı olduğu elde edilmiştir. Isı iletim performansında karbon elyafı cam elyaf (0,013 W/mm2) ve aramid (4.10-4 W/mm2) takip etmiştir. Bu araştırma polimer kompozit malzemeler ile lamine edilmiş FV modül ve konvansiyonel tip FV modül arasındaki ısı akısı farkını 0,0242 W/mm2 olarak elde ederek FV modüllerden elde edilebilen ısı enerjisinin arttırımına katkıda bulunmuştur., Photovoltaic (PV) modules are structures that produce electricity from the sun's rays falling on them and have more than one PV cell on their surface. PV cells can use not only direct rays, but also a certain wavelength range of all light coming to the surface for energy production. Due to their nature, PV modules have a higher temperature compared to the ambient temperature, which causes a decrease in the electrical efficiency and power generation of the PV cells. For this reason, academic studies on the transfer of heat energy stored in PV modules to outside have gained momentum in recent years. For example, by obtaining heat energy from PV modules, the heating load of the houses is met under the target of zero energy consumption, and the system/energy efficiency is increased with further work. This study aimed to reduce the heat energy stored in the PV module by examining the composite structures formed using polymer-based reinforcement materials to improve the heat conduction performance of PV modules. For this purpose, reinforcement materials were investigated, and it was found appropriate to investigate carbon, glass fiber, aramid (Kevlar) reinforcement materials under two different parameters. These two parameters investigate the heat conduction performance of each reinforcement material in different layer thicknesses and in the hybrid structure formed with each other. As a result of the research, it has been obtained that the structure formed with carbon fiber reinforcement material is the optimum structure with a heat flux of 6.51 W/mm2. In heat conduction performance, carbon fiber was followed by glass fiber (0.013 W/mm2) and aramid (4.10-4 W/mm2). This research contributed to the increase of the heat energy that can be obtained from PV modules by obtaining the heat flux difference between the PV module and the conventional type of PV module laminated with polymer composite materials as 0.0242 W/mm2.

In recent years, higher penetrations of renewable energy generations helped persuade sustainable energy and environmental targets, although their intermittent and fluctuated nature raised technical challenges. However, hybrid power system can minimize these technical issues by integrating flexible generation capable renewable energy sources like biomass. This study deals with optimizing gridintegrated and stand-alone biomass-based hybrid power system for the energy demand of a rural region containing poultry farms. Besides solar and wind energy, energy storage integration is evaluated regarding overall technical-environmental-economic performance, considering the actual manure potential using HOMER Pro. In addition, sensitivity analyses are performed, considering the estimated load and inflations using an artificial neural network method. Using biomass and solar hybrid options offers more autonomous, environmentally friendly, and economic advantages. Biomass-based hybrid power system with solar energy reduced net present cost by around 12% and increased renewable fraction by 7%, and grid-connected options can provide 88.9% renewable fraction. In addition, the energy storage integration increased renewable fraction by around 10% and reduced excess energy by 16%. The proposed biomass-based hybrid power system achieves cost-effective sizing of solar or wind-based hybrid systems, empowers the reliability of renewable energy and presents good consistency of decarbonization targets.

Based on the preliminary evidence of volcanoes, hot springs, and Geysers in parts of Nigeria, it is proposed that deep geothermal wells can be found in Nigeria. This research uses thermal anomalies zones to identify types of geothermal wells in Nigeria, i.e., using remote sensing and modified thermal equations. The remote sensing dataset includes the ground heat flux (GHF) dataset from Modern-Era Retrospective analysis for Research and Applications (MERRA) of 28 years; sediment thickness dataset from EarthData; and surface geology from LANDSAT. The thermal transport model was used to narrow potential locations across Nigeria using the ground heat flux and sediment thickness, while the surface geology was used to confirm the deep geothermal zones. Four GHF patterns were discovered in Nigeria. The research shows that the deep geothermal wells might be located in Plateau, Bauchi, Gombe, Taraba, Ekiti, Kogi, Benue, Nassarawa, and Taraba. Also, the medium-depth geothermal wells may be located in Sokoto, Zamfara, Kastina, Kwara, Oyo, and Jigawa States. It was revealed that the southern parts of Nigeria have lots of shallow geothermal wells. The deep geothermal wells can be found in the Chad Basin and Benue trough, while the medium-depth geothermal wells can be found in the Sokoto basin, Bida basin, and parts of the lower Benue trough. It is recommended that further ground trotting exploration be carried out in the identified geographical locations.

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged in 2019, cut the epoch that will make profound fluctuates in the history of the world in social, economic, and scientific fields. Urgent needs in public health have brought with them innovative approaches, including diagnosis, prevention, and treatment. To exceed the coronavirus disease 2019 (COVID-19) pandemic, various scientific authorities in the world have procreated advances in real time polymerase chain reaction (RT-PCR) based diagnostic tests, rapid diagnostic kits, the development of vaccines for immunization, and the purposing pharmaceuticals for treatment. Diagnosis, treatment, and immunization approaches put forward by scientific communities are cross-fed from the accrued knowledge of multidisciplinary sciences in health biotechnology. So much so that the pandemic, urgently prioritized in the world, is not only viral infections but also has been the pulsion in the development of novel approaches in many fields such as diagnosis, treatment, translational medicine, virology, microbiology, immunology, functional nano- and bio-materials, bioinformatics, molecular biology, genetics, tissue engineering, biomedical devices, and artificial intelligence technologies. In this review, the effects of the COVID-19 pandemic on the development of various scientific areas of health biotechnology are discussed.

The Thrace Basin in northwestern Turkey is a deep Eocene–Oligocene hydrocarbon-bearing sedimentary basin. The basin has potential for geothermal energy utilization in the future due to its favorable geological conditions. In this study, we combined the available bottom hole temperature (BHT) data from 70 points with the thermal conductivity and radiogenic heat productions of the basin formations, and generated a detailed thermal model of the northern part of the basin. For heat flow determinations from the BHT data, we applied Bullard’s thermal resistance method on formation thermal conductivities and thicknesses. The results give an average surface heat flow of 65.8 ± 11.3 mW/m2. We obtained high heat flow values (75–80 mW/m2) in the eastern and western sides, and the central part of the study area. These relatively high heat flow values can be explained by the combined effect of basement topography and the variations in the radiogenic heat production of the basement rocks. The calculated subsurface temperatures in selected hydrocarbon fields vary in the range of 45–64°C at 1km depth, 99–136°C at 3km depth, and 155–208°C at 5km depth as a result of local variations of the surface heat flow and formation thermal resistances. These variations in subsurface temperatures can have significant effects on the cost of geothermal energy production in future.

We synthesized molecular weight-controlled and fluorine-containing PAEs (MWCPAEs) using decafluorobiphenyl (DFBP), 2-bis (4-hydroxyphenyl) propane (Bis A), and 2,2-Bis (4-hydroxyphenyl) hexafluoropropane (Bis AF). Later, commercially available PEEK and the MWCPAEs were sulfonated (SPEEK and SMWCPAE) and blended to fabricate blend membranes (BMs). All BMs have been prepared by solution casting method in 5 wt%-20 wt% concentrations using N,N-dimethylacetamide. The effects of chemical structures, sulfonation levels, MW and compositions on the membrane properties are discussed. We obtained miscible and mechanically compatible BMs. The highest proton conductivity (238.9 mS/cm) was determined for SPEEK70/S-DFBP-Bis-A based blend membrane (Mw: 48.355, 5wt. %). All chemical, mechanical, thermal, and hydrolytic properties of the BMs are comparable with, or better than, that of Nafion. We suggest that designing polymeric structures with desired MWs and sulfonation levels may enable enhanced properties and can help to design materials with on demand properties.

The main outdoor factors that reduce the efficiency of the photovoltaic (PV) panel are the reflection and refraction of light, dirt, dust, and organic waste accumulating on the panel surface. In this article, an antireflection, self-cleaning coating was applied on the PV panel cover glass with a new method. With the coating, the surface has been given a hydrophobic feature. As a coating method, a 3-D printer has not been seen in the literature and used as a new method. The electrospinning method has also been tried as an alternative method. Solutions in different combinations were developed using polylactic acid or polymethylmethacrylate polymer, chloroform ($\text{CHCl}_3$) as a solvent, and silicon dioxide ($\text{SiO}_2$) and titanium dioxide ($\text{TiO}_2$) nanoparticles as primary materials in a modified 3-D printer for bioprinting. Five PV panels were obtained by applying different 3-D parameters from three solutions, which have the best results. Coating thicknesses are in the range of 3.12-8.47 mu m. Coated and uncoated PV panels were tested in outdoor conditions for ten-day periods. The power outputs of the PV panels were measured, and their ten-day average efficiency was presented. According to the results, the highest efficiency increase is 8.7%. The highest light transmittance is 88.2% at 550 nm. In addition, hydrophobic properties were observed on all surfaces and the water contact angle was measured as 96.18 degrees.

Injecting hydrogen into the natural gas network to reduce CO2 emissions in the EU residential sector is considered a critical element of the zero CO2 emissions target for 2050. Burning natural gas and hydrogen mixtures has potential risks, the main one being the flame flashback phenomenon that could occur in home appliances using premixed laminar burners. In the present study, two-dimensional transient computations of laminar CH4- + air and CH4 + H-2 + air flames are performed with the open-source CFD code OpenFOAM. A finite rate chemistry based solver is used to compute reaction rates and the laminar reacting flow. Starting from a flame stabilized at the rim of a cylindrical tube burner, the inlet bulk velocity of the premixture is gradually reduced to observe flashback. The results of the present work concern the effects of wall temperature and hydrogen addition on the flashback propensity of laminar premixed methane-hydrogen-air flames. Complete sequences of flame dynamics with gradual increases of premixture velocity are investigated. At the flame flashback velocities, strong oscillations at the flame leading edge emerge, causing broken flame symmetry and finally flame flashback. The numerical results reveal that flashback tendency increase with increasing wall temperature and hydrogen addition rate. (C) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

© 2023 Elsevier LtdBiomass is the most widespread among renewable energy sources and offers many advantages. However, the heterogeneous structure of biomass brings many disadvantages. Therefore, characterization of thermal degradation of biopolymeric structures in biomass such as hemicellulose (HC), cellulose (CL), and lignin (LN) is very important for the efficiency of any biomass-based thermal process. On the other hand, the characterization of these biopolymers requires various experimental procedures that consume resources and time. Artificial neural networks (ANN) as a machine learning approach provide a remarkable opportunity to identify patterns in the complex structure of biomass fuels and their thermochemical degradation processes. In this study, a new model was developed for the first time to generate differential thermogravimetric analysis (DTG) curves for HC, CL and LN in biomass using proximate analysis results of raw biomass. DTG curves were evaluated using a ANN model developed with the open-source \"TensorFlow\" library in Python software. ANN model performed excellently with R2 values above 0.998. The results show that the newly developed model can estimate the thermal degradation for any temperature, so that biopolymer fractions in the degraded biomass can be calculated immediately, which has not been reported before.

This paper presents a novel optimization approach to find the optimal STATCOM installation in the power system using Mixed Integer Distributed Ant Colony optimization (MIDACO). The proposed method is mathematically formulated based on minimizing the Voltage Deviation Index (VDI) and the installation cost of STATCOM. The ability of STATCOM to provide shunt compensation to maintain bus voltage is exploited here. The proposed approach has been tested on the standard IEEE 14-bus system.

Marine pollution has increased in recent decades, largely due to the proliferation of seafood processing plants and the improper disposal of their associated waste streams. The waste streams consist mainly of shells that are composed of chitin, which is the most abundant aminopolysaccharide biopolymer in nature. Recognizing the value of chitin, the potential for the valorization of crustacean waste for chitin production was explored. In this regard, biogenic crab waste was subjected to chemical-only, enzymatic–chemical, and microbial treatments for chitin production. The results were employed as inputs for process simulation as a precursor to undertaking performance assessments. This study subsequently showed that the net present values (NPVs) of the chemical-only, enzyme–chemical, and microbial chitin production pathways were GBP 118.63 million, GBP 115.67 million, and GBP 132.34 million, respectively, indicating that the microbial chitin production pathway constituted the most appropriate technology for future investment. Employing a cost–benefit (CB) analysis, the CB ratios for the chemical-only, enzymatic–chemical, and microbial approaches were determined to be 7.31, 0.45, and 0.23, respectively. These results reinforced the dominant status of the microbial approach for chitin production from crab waste as the preferred valorization strategy. This study was able to provide information regarding the implications of executing alternative scenarios for crustacean waste.

© 2022 Elsevier LtdIn this study, the use of Deep Cascade Forward Neural Network (DCFNN) was investigated to model both linear and non-linear chaotic relationships in co-composting of dewatered sewage sludge and biomass fly ash (BFA). Model results were evaluated in comparison with RSM, Feed Forward Neural Network (FFNN) and Feed Back Neural Network (FBNN), and Cascade Forward Neural Network (CFNN). DCFNN produced predictive results with MAPE values less than 1% for all datasets in all experimental designs except one with 1.99%. Furthermore, the decision variables were optimized by Genetic Algorithm (GA). The desirability level obtained from the optimization results was found to be 100% in a few designs and above 95% in all other designs. The results showed that DCFNN is a reliable and consistent tool for modeling composting process parameters, also GA is a satisfactory tool for determining which outputs the input parameters will produce in an experimental setup.

In this study, the practices and experiences of the United Kingdom, Germany, the Netherlands, Belgium, Denmark and China, which are the six leading countries in the world in terms of the installation of offshore wind power plants (WPPs), were examined. Policy documents regarding offshore WPP projects, the legal procedures carried out during the realization of the projects, the institutions and organizations taken part in the project development phase and the support mechanisms applied in these countries are explained. The practices of the selected countries were examined comparatively from the regulatory perspective and the applicability of best practices in Turkey was evaluated. Various suggestions have been made regarding the steps to be taken in the upcoming period for the establishment of an offshore WPP in Turkey based on an assessment of the current status and studies conducted so far regarding offshore WPP projects in Turkey., Bu çalışmada, dünyada deniz üstü rüzgâr enerji santrallerinin (RES) kurulumu bakımından önde gelen altı ülke olan Birleşik Krallık, Almanya, Hollanda, Belçika, Danimarka ve Çin’in uygulama ve tecrübeleri incelenmiştir. Deniz üstü RES projelerine ilişkin politika belgeleri, projelerin kurulumu esnasında yürütülen yasal prosedürler, proje geliştirme aşamasında hangi kurum ve kuruluşların görev aldığı ve bu ülkelerde uygulanan destekleme mekanizmaları açıklanmıştır. Seçilen ülkelerin uygulamaları düzenleme bakış açısıyla karşılaştırmalı biçimde incelenmiş ve iyi uygulama örneklerinin Türkiye’de uygulanabilirliği değerlendirilmiştir. Türkiye’de deniz üstü RES projelerine ilişkin mevcut durum ve yapılan çalışmalar değerlendirilerek Türkiye’de deniz üstü rüzgâr santrali kurulumu için önümüzdeki süreçte atılması gerekli adımlara ilişkin çeşitli önerilerde bulunulmuştur.

Fuel cells are electrochemical devices utilized for converting chemical energy to electrical energy. Solid Oxide Fuel Cells (SOFCs) have several advantages over other kinds. For instance, high energy efficiency expanded fuel flexibility, low environmental pollutant emission are the properties of SOFCs that make them superior to other fuel cell types. Due to these special characteristics, SOFCs are gained a great deal of attraction. These fuel cells consist of different main operating parts, a cathode, an anode, and electrolyte which each of them demands special materials to operate with the most efficiency. SOFCs mostly operate in high temperatures (800-1000 ᵒC). Reducing the operating temperature to lower than 600 ᵒC or intermediate temperatures 600-800 ᵒC is one of the methods that can make them more practical devices. Perovskite oxides can be used effectively as all main parts of SOFCs because of their excellent properties like electrical and ionic conductivities, oxygen ion vacancies, great catalytic properties, thermal durability, and chemical stability to decrease the operating temperature. In this review, numerous perovskite-based materials utilized in the anode and the cathode electrodes of SOFCs are investigated in the most recent, advanced, and novel works. The perovskite materials, their properties, and their influence on the fuel cell’s performance, and in some cases the sulfur tolerance of the materials when H2S co-exists in the fuel of the fuel cell are reviewed in this paper Adding different dopants in A-site and B-site of the perovskite oxides is the most effective way to modify the characteristics of the materials. This review can provide great data on the possible perovskite oxides with the capability of enhancing the efficiency of SOFCs by reducing the operating temperature, and their most decisive and significant characteristics, like composition, structure, electrical conductivity, electrochemical and mechanical properties for research groups working on solid oxide fuel cells.

© 2023 by the authors.The important parts of a transformer, such as the core, windings, and insulation materials, are in the oil-filled tank. It is difficult to detect faults in these materials in a closed area. Dissolved Gas Analysis (DGA)-based fault diagnosis methods predict a fault that may occur in the transformer and take the necessary precautions before the fault grows. Although these fault diagnosis methods have an accuracy of over 95%, their validity is controversial since limited data are used in the studies. The success rates and reliability of fault diagnosis methods in transformers, one of the most important pieces of power systems equipment, should be increased. In this study, a hybrid fault diagnosis system is designed using DGA-based methods and Fuzzy Logic. A mathematical approach and support vector machines (SVMs) were used as decision-making methods in the hybrid fault diagnosis systems. The results of tests performed with 317 real fault data sets relating to transformers showed accuracy of 95.58% using a mathematical approach and 96.23% using SVMs.

Enerji; yaşamımızda en çok duyduğumuz ve kullandığımız kavramlardan biri olmakla beraber, günümüzde sosyal, ekonomik, teknolojik ve çevresel yönleriyle ele alınan ve değerlendirilen çok geniş bir kapsama sahiptir. Kavram olarak günlük yaşamda farklı kullanımları ve birçok disiplinde farklı tanımlamaları vardır. Günlük yaşamda kullandığımız enerji kavramı, kullanıma göre farklı büyüklüklerin oluşmasına neden olur. Bu büyüklükleri bilmek ve yaşamımızın içerisinde bilinçli olarak kullanmak, hem topluma hem de bireylere ekonomik ve çevresel faydalar sağlayacağı bir gerçektir. Bu kapsamda toplumun tüm eğitim seviyelerinde okul öncesinden başlayarak, yaşam boyu öğrenme süreci ile enerji okuryazarlığı kavramı ele alınmalı ve geliştirilmelidir. Böylece bireylerin günlük kullanımlarında farklı bakış açıları ve gelişim süreci elde edebilir.Enerji teknolojileri; enerjinin üretiminden tüketimine kadar birçok alt sistem ve bileşeni kapsamaktadır. Çok büyük etki alanına sahip olan enerjinin üretim-tüketim sürecinde sürdürebilir yaşamı desteklemek, ekonomik ve teknolojik olmak gibi birçok ölçüt öne çıkmaktadır. Bu kapsamda enerji teknolojilerinin yenilenmesi, genel olarak mevcut teknolojileri iyileştirmek veya yenilerini oluşturmak olarak ifade edilmektedir. Uzun vadeli olarak enerji teknolojileri üzerine yapılan araştırmalarda ve istihdamda uluslararası literatürdeki çalışmaların kapsamında en önemli üç başlık; enerji verimliliği, enerji depolanması ve yenilenebilir enerji kaynakları olarak ifade edilmektedir. Bu temel alanlar öğrencilerimizin yönlendirilmesi açısından önemlidir.Sunulan bu çalışmayla öğretmenler, enerji teknolojileri başlığı altında öncelikle öğrencilerin enerji kavramından başlayarak, enerji okuryazarlığı ve sürdürülebilir yaşamı destekleme süreçlerini kavramaları hedeflemelidir. Bu çerçevede çalışmada ilk olarak enerji kavramının tanımı, büyüklük olarak anlamı, dönüşümü, enerji verimliliği konuları yer almaktadır. Sonraki aşamada ise, enerji teknolojilerinin üretim süreçleri ele alınmaktadır. Böylece geleneksel ve yenilenebilir enerji kaynakları üzerine enerji teknolojileri ifade edilmektedir. Özellikle çalışmada rüzgâr ve güneş bazlı yenilenebilir enerji üretim teknolojileri detaylı olarak sunulmaktadır. Son olarak, günümüzde enerji teknolojilerinin en önemli parçası haline gelen enerji depolama sistemleri üzerine bir bölüm çalışma içinde bulunmaktadır. Bu çalışma, öğretmenlere \"Dene ve Yap\" öğrenme süreci içerisinde öğrencilerin konuları ele alması yaklaşımıyla oluşturulmuştur. Özellikle deney sürecinde öğrencinin karşılaşacağı sorunlara vereceği çözümler, değişkenlerin belirlemesi ve nasıl değişeceği gibi fikirler, yaparak ve yaşayarak öğrenme sürecini oluşturması bu çalışmanın istenen aşamalarıdır. Enerji teknolojileri başlığı altında verilen bu çalışma diğer Deneyap başlıklarından farklı olarak, konunun içeriği ve farklılığı nedeniyle öğrencilerin en yüksek düzeyde anlama ve kavrama sağlamak hedefi ile 5E öğretim yöntemi kullanılarak tasarlanmıştır. Bu çalışmanın 5E öğrenme döngüsü modeli ile öğrencilerin araştırma sorgulamaya teşvik etmesi hedeflenmektedir.Böylece \"Enerji Teknolojileri\" başlığı altında mühendisliğin temel konularına odaklanılarak, enerji kavramı üzerine açıklama ve tanımlamalar yapılması sağlanacaktır. Analitik bir çerçevede enerji kavramını açık bir şekilde öğretmek, disiplinler arası sorunlar hakkında düşünmesini sağlamak iyi donanımlı yeni nesil bilim insanları ve mühendisler yetiştirmeye yardımcı olacaktır.

Semi-transparent organic photovoltaics (OPVs) are an emerging solar-energy-harvesting technology with promising applications, such as rooftop energy supplies for environmentally friendly greenhouses. However, the poor operational stability of OPVs poses challenges to their feasibility as incessantly serving facilities. Here we report a reductive interlayer structure for semi-transparent OPVs that improves the operational stability of OPVs under continuous solar radiation. The interlayer effectively suppresses the generation of radicals from the electron transport layer under sunlight and prevents the structural decomposition of the organic photoactive layer during operation. The defects that serve as the charge carrier recombination sites are nullified by the electron-donating functional groups of the reduced molecules, which improves photovoltaic performance. The semi-transparent OPVs demonstrate a power conversion efficiency of 13.5% and an average visible transmittance of 21.5%, with remarkable operational stability (84.8% retention after 1,008 h) under continuous illumination. Greenhouse results show that the semi-transparent OPV roof benefits the survival rate and growth of the crops, indicating the importance of our approach in addressing food and energy challenges.

Enerji; yaşamımızda en çok duyduğumuz ve kullandığımız kavramlardan biri olmakla beraber, günümüzde sosyal, ekonomik, teknolojik ve çevresel yönleriyle ele alınan ve değerlendirilen çok geniş bir kapsama sahiptir. Kavram olarak günlük yaşamda farklı kullanımları ve birçok disiplinde farklı tanımlamaları vardır. Günlük yaşamda kullandığımız enerji kavramı, kullanıma göre farklı büyüklüklerin oluşmasına neden olur. Bu büyüklükleri bilmek ve yaşamımızın içerisinde bilinçli olarak kullanmak, hem topluma hem de bireylere ekonomik ve çevresel faydalar sağlayacağı bir gerçektir. Bu kapsamda toplumun tüm eğitim seviyelerinde okul öncesinden başlayarak, yaşam boyu öğrenme süreci ile enerji okuryazarlığı kavramı ele alınmalı ve geliştirilmelidir. Böylece bireylerin günlük kullanımlarında farklı bakış açıları ve gelişim süreci elde edebilir.Enerji teknolojileri; enerjinin üretiminden tüketimine kadar birçok alt sistem ve bileşeni kapsamaktadır. Çok büyük etki alanına sahip olan enerjinin üretim-tüketim sürecinde sürdürebilir yaşamı desteklemek, ekonomik ve teknolojik olmak gibi birçok ölçüt öne çıkmaktadır. Bu kapsamda enerji teknolojilerinin yenilenmesi, genel olarak mevcut teknolojileri iyileştirmek veya yenilerini oluşturmak olarak ifade edilmektedir. Uzun vadeli olarak enerji teknolojileri üzerine yapılan araştırmalarda ve istihdamda uluslararası literatürdeki çalışmaların kapsamında en önemli üç başlık; enerji verimliliği, enerji depolanması ve yenilenebilir enerji kaynakları olarak ifade edilmektedir. Bu temel alanlar öğrencilerimizin yönlendirilmesi açısından önemlidir.Sunulan bu çalışmayla öğretmenler, enerji teknolojileri başlığı altında öncelikle öğrencilerin enerji kavramından başlayarak, enerji okuryazarlığı ve sürdürülebilir yaşamı destekleme süreçlerini kavramaları hedeflemelidir. Bu çerçevede çalışmada ilk olarak enerji kavramının tanımı, büyüklük olarak anlamı, dönüşümü, enerji verimliliği konuları yer almaktadır. Sonraki aşamada ise, enerji teknolojilerinin üretim süreçleri ele alınmaktadır. Böylece geleneksel ve yenilenebilir enerji kaynakları üzerine enerji teknolojileri ifade edilmektedir. Özellikle çalışmada rüzgâr ve güneş bazlı yenilenebilir enerji üretim teknolojileri detaylı olarak sunulmaktadır. Son olarak, günümüzde enerji teknolojilerinin en önemli parçası haline gelen enerji depolama sistemleri üzerine bir bölüm çalışma içinde bulunmaktadır. Bu çalışma, öğretmenlere \"Dene ve Yap\" öğrenme süreci içerisinde öğrencilerin konuları ele alması yaklaşımıyla oluşturulmuştur. Özellikle deney sürecinde öğrencinin karşılaşacağı sorunlara vereceği çözümler, değişkenlerin belirlemesi ve nasıl değişeceği gibi fikirler, yaparak ve yaşayarak öğrenme sürecini oluşturması bu çalışmanın istenen aşamalarıdır. Enerji teknolojileri başlığı altında verilen bu çalışma diğer Deneyap başlıklarından farklı olarak, konunun içeriği ve farklılığı nedeniyle öğrencilerin en yüksek düzeyde anlama ve kavrama sağlamak hedefi ile 5E öğretim yöntemi kullanılarak tasarlanmıştır. Bu çalışmanın 5E öğrenme döngüsü modeli ile öğrencilerin araştırma sorgulamaya teşvik etmesi hedeflenmektedir.Böylece \"Enerji Teknolojileri\" başlığı altında mühendisliğin temel konularına odaklanılarak, enerji kavramı üzerine açıklama ve tanımlamalar yapılması sağlanacaktır. Analitik bir çerçevede enerji kavramını açık bir şekilde öğretmek, disiplinler arası sorunlar hakkında düşünmesini sağlamak iyi donanımlı yeni nesil bilim insanları ve mühendisler yetiştirmeye yardımcı olacaktır.

© 2022 Elsevier LtdIntegrated gasification combined cycle (IGCC) is a power generation technology that partially oxidizes solid feedstocks to produce syngas, drives high-efficiency gas turbines (GT), recovers waste heat and uses it to generate electricity, etc. In this study, a new IGCC model for an entrained bed gasifier/GT/Kalina cycle for CO2 co-gasification was developed for the first time using Aspen HYSYS, and an energy and exergy analysis of this model was performed to provide decision makers with a comprehensive overview of whether the energy conversion system is designed to be sustainable from a variety of perspectives. The newly proposed integrated system was used to study the CO2/air gasification process of the biochar/waste tyre blend. Although entrained bed gasifiers have been modelled using different software and different fuels, no study on the Kalina cycle integrated biochar/waste tyre co-gasification process using Aspen HYSYS has not been reported yet. In addition, most parametric studies on integrated Kalina combined cycles focus on the influence of the Kalina cycle or a few operating factors. However, in this study, the effects of a variety of gasification process operating conditions on the performance of the combined cycle are considered. The equivalence ratio (ER) for a high-efficiency integrated system ranged from 0.23 to 0.25, and the CO2 content in the gasifying agent was in the range of 5–7%. While increasing the waste tyre content in the feedstock enhances H2 production, operating the entrained bed gasifier at relatively low temperature is more efficient. Increasing the ammonia content in the working fluid also improves efficiency, and the inlet pressure of the Kalina turbine should be maintained at 28 bar to maximize performance. While the integration of the GT enables significant power generation, optimizing the operating conditions of the gasifier, which has the highest exergy dissipation, is critical to the performance of the integrated system.

A deliverability test performed in a gas well is one of the fundamental steps to determine the flow potential of the wells in reservoir surveillance. Dynamic reservoir models need robust AOF (Absolute Open Flow), productivity index, permeability for calibration, history matching, and predictions. In this study, a gas well in a Pliocene sandstone gas reservoir was validated using the “Modified Isochronal Testing” method. This study aims to mitigate the efforts done to estimate the phenomenon of flow potential of the gas wells. Hence, the field development activities can be leveraged to a more efficient stage technically and economically. In this study, AOF, Productivity Index (PI), and the permeability of the tested interval were calculated. The validation of the permeability with log and core data increases the confidence level of the work done. AOF is the key performance indicator to define the gas well productivity at zero sand face pressure which is a measure of ranking the production potential of gas wells. The AOF values support the determination of the number of wells to be drilled and the design of the surface facilities. In this study, pressure and time data were obtained and they were analyzed by empirical and theoretical methods. These two methods used in analysis gave very close AOF values; 10.15MMSCF/D (empirical) and10.67 MMSCF/D (theoretical), respectively. The permeability was calculated as 3.42 md, which is in line with the log permeability of 3.70 md and core permeability of 3.40 md.

Bu çalışmada, alan ısıtması için kaynak olarak düşük entalpili jeotermal akışkan ve doğalgaz kullanan ve Türkiye’nin kuzeybatısında bulunan doğalgaz destekli bir jeotermal merkezi ısıtma sisteminin analizi yapılmıştır. Çalışma, sistemin hibrit çalışma şartları altında (1 Ocak 2020’den 31 Mart 2020’ye kadar) enerji, ekserji ve termoekonomik analizden oluşmaktadir. Veriler sistemi kullanan işletmeden toplanmıştır. Isı pompalarına ait kapasite değerleri ise satıcı firmanın İstanbul, Türkiye’deki şubesinden elde edilmiştir ve ‘Hibrit Durum İçin Ortalama Değerler’ tespit edilmiştir. Bu çalışma, söz konusu sistemin tüm aşamalarındaki enerjetik, ekserjetik ve termoekonomik değerlendirmesini kapsamaktadır. Sonuçlar, sistem performansının incelenmesine dayalı olarak bulunmuştur. Tüm sistemin enerji ve ekserji verimi sırasıyla %56,77 ve % 49,93 olarak bulunmuştur. Saatlik ekserji maliyeti ve termoekonomik faktör sırasıyla 411,242 €/h ve %9,8 olarak hesaplanmıştır., In this work, a natural gas assisted geothermal central heating system in northwestern Turkey utilising low enthalpy geothermal fluid and natural gas as the sources for space heating was analyzed.The study comprised energy, exergy and thermoeconomic analyses of the system under hybrid operating conditions (i.e., from 1 January 2020 to 31 March 2020). The data were collected from a basis of the facility which operates the system. The values about the heat pumps were obtained from the department of the sales company in Istanbul, Turkey and the ‘Average Values for Hybrid Case’ were determined. This work covers energetically, exergetically and thermoeconomically assessment of the system in question through its all stages. The results were found with regard to the system performance investigation. The whole system efficiencies of energy and exergy were found as 56.77% and 49.93% respectively. The exergy cost value per hour and the thermoeconomic factor were calculated as 411.242 €/h and 9.8% respectively.

The energy crisis in Europe has increased the importance of energy alternatives to hydrocarbons. For example, geothermal resources have long been proven to be very efficient heat sources for conventional power cycles. To get the maximum benefit from such a system, it is essential to carefully optimize the system parameters. On the other hand, the topology and nonlinear nature of the system prevent it from being expressed as an analytical function and being differentiable. Thus, derivative-based deterministic optimization methods are difficult to apply. In this study, it is proposed to model a geothermal-based dual-flash combined heat and power system in a process simulator and use it as a black-box function generator to calculate the values of the objective and constraint functions. The system parameters that will provide the maximum combined heat and power efficiency are determined by the Genetic Algorithm. Accordingly, with the optimum system design, the total net turbine power is 132.78 kW. The amount of heat utilized is 15020.10 kW.

The use of fossil fuels in IC engines in vehicles and industries has been identified as the leading cause of pollution, especially in urban areas where the traffic is usually heavy and industries are situated. In addition to air pollution which has its attendant health risks, the emission of greenhouse gases from the combustion of fossil fuels has been identified as one of the leading causes of climate change. The aforementioned reasons coupled with the fact that fossil fuels are exhaustible resources have necessitated the search for alternative eco-friendlier and sustainable fuels. The utilization of agricultural waste such as (mango and orange) peels to produce bioethanol proves to be a better alternative than the use of food crops. In this research, enzymatic scarification of yeast (Saccharomyces cerevisiae) was used to produce bioethanol from samples of mango and orange peels and their properties were compared with those of standard pure (98%) anhydrous ethanol. ASTM standards were used as comparative measures of the fuel properties that derived from bioethanol. It was found that the bioethanol concentration for the two samples were 19.98% for sample A and 19.17% for sample B and the results also show a good agreement as analysed by (ANOVA).

Gıda ürünlerinin tüketilmesinde, ürünün besin ve kalite özelliklerini yitirmeden raf ömürlerinin uzatılması için bazı işlemler uygulanmaktadır. Bu işlemlerin başında kurutma uygulamaları gelmektedir. Ürünlere kurutma uygulama yapılmasındaki amaç ürün içerisindeki su aktivitesinin azaltılarak nem içeriğinin düşürülmesidir. Bu çalışmada, armut kurutma uygulamalarının yapıldığı kurutma sistemlerinin karşılaştırılması amacıyla Antalya ilinde kurutma denemeleri yapılmıştır. Geleneksel kurutma sistemi ve tasarımı yapılan güneş enerjili kurutma sistemlerinde armut dilimleri numuneleri eş zamanlı şekilde kurutulmuştur. Tasarımı yapılan sistemin etkinliği ve kurutma kalitesi üzerindeki etkileri irdelenmiştir.

© 2022 Elsevier LtdThe problems of foreign dependency in energy and the orientation towards national/international environmental policies encourage investments in renewable energy systems. In renewable energy systems (RES), photovoltaic (PV) systems based on solar energy are increasing every year. This situation reveals the need for qualified employees whose working area is photovoltaic systems. This study has conducted a literature search on occupational health and safety (OHS) issues in PV power systems. At the same time, field studies and expert interviews were conducted to examine the OHS practices and training received in the work areas. In this direction, the importance of OHS requirements and training for OHS success in PV power systems has been emphasized. The importance of training has been expressed to increase OHS\"s performance and success in the PV power system fields. In this study, sample gamification scenarios were created for two different activities in working at height during the installation of the PV. Algorithms have been developed for improving VR/AR applications in OHS training with the sample gamification scenarios created and to support the dissemination of these training applications. In this way, it is aimed to explain the necessary information for VR/AR technologies at an academic level and to contribute to content developers, researchers, relevant institutions and organizations from a sustainability perspective.

© 2022 The Authors. Published by American Chemical Society.Catalysts based on metal-free conjugated porous polymers (CPPs) are still rare for electrochemical oxygen reduction reactions (ORR). In this study, a conjugated porous polymer, TT-TPB, based on thieno[3,2-b]thiophene (TT) and triphenylbenzene (TPB), was synthesized applying palladium(0) catalyzed Suzuki coupling reaction and its ORR activity was investigated in alkaline condition. It demonstrated comparable electrocatalytic performance of ≈0.89-0.9 V Eonset vs RHE with the commercially available Pt/C. Density-functional theory (DFT) calculations revealed that TT-TPB featured efficient electrocatalytic active sites derived from volumetric, areal, and O2 adsorbing calculations, which were in line with the experimental results. Moreover, semiconducting and surface properties of TT-TPB were investigated in detail using electrochemical and spectrophotometric techniques. This work shows the potential application of thienothiophene-based metal-free CPP in the electrochemical conversion process.

© 2022 Wiley-VCH GmbH.We demonstrate a BODIPY-based small molecule photopatterned surface by thiol-ene click chemistry at room temperature utilizing only 366 nm UV light. The resulting cross-linked polymer exhibits porous surfaces according to AFM and TEM results. A dramatic blue shift occurred in absorption spectra and the photoluminescence was also intensified as a result of crosslinking. Optical and electrochemical results are compatible with the DFT calculations. The obtained results prove that the photopatterned BODIPY-based material can be easily and inexpensively applied in multilayer optoelectronic devices.

The importance of energy which has a significant role in socio-economic development of countries is increasing because of a fast-growing population and industrialization. The fact that the fossil resources are insufficient to meet the demand if new reserves cannot be found in the near future and the threat to human and environmental health lead the countries to seek renewable clean energy resources. Turkey, which is dependent on foreign energy due to being poor in terms of fossil fuels as a country, has high solar energy potential but cannot utilize this potential fully. In this paper, the importance and potential of solar energy in Turkey, the problems encountered in utilizing solar energy have been studied. In this study, semi-structured interview was used as qualitative data collection technique. The experts to be interviewed were selected from people with at least five years of academic or sector experience in solar energy. As a result of the research, it was reached by all experts interviewed that Turkey need to increase the benefit from solar energy for Turkey's social and economic development and there are various obstacles in front of utilizing this benefit. However, it is seen that expert opinions vary in terms of solutions.

In this paper, the effect of the different parameters such as solar radiation, and ambient temperature on thermodynamic performance of a Water-in-glass evacuated tube heat pipe (ETHP) is studied, including energy, exergy, environmental, economic analysis, and sustainability index. The ETHP system is evaluated under the 4E criteria; energy, exergy, economic, and environment. The energy, exergy, environmental, enviroeconomic, exergoenvironmental, exergoenviroeconomical analysis and sustainability index of the ETHP system is calculated. There are 4 collectors each collector 57 pipes as a total of 108 pieces pipes, a hot water tank, a heat exchanger, and a pump in the system. The water is used as a working fluid due to economic, and common use in the system. In the result of this experimental study, we calculated energy and exergy efficiencies of the EHTP system as %60.74 and %40.72, respectively. In addition, the environmental, exergoenviromental, enviroeconomic, and exergoenviroeconomic values of the EHTP system are found 5958.01 kgCO2/day, 5564.72 kgCO2/day, 0.7448 $/day and 0.6958 $/day, respectively. Also, the sustainability index of the system is found as 1.687.

© 2022 Elsevier LtdStudies on developing strategies to predict the stability and performance of the composting process have increased in recent years. Machine learning (ML) has focused on process optimization, prediction of missing data, detection of non-conformities, and managing complex variables. This review investigates the perspectives and challenges of ML and its important algorithms such as Artificial Neural Networks (ANNs), Random Forest (RF), Adaptive-network-based fuzzy inference systems (ANFIS), Support Vector Machines (SVMs), and Deep Neural Networks (DNNs) used in the composting process. In addition, the individual shortcomings and inadequacies of the metrics, which were used as error or performance criteria in the studies, were emphasized. Except for a few studies, it was concluded that Artificial Intelligence (AI) algorithms such as Genetic algorithm (GA), Differential Evaluation Algorithm (DEA), and Particle Swarm Optimization (PSO) were not used in the optimization of the model parameters, but in the optimization of the parameters of the ML algorithms.

© 2022 IEEE.Businesses are concerned about energy losses. Electronic gadgets have become more prevalent as a result of their adoption. The frequency with which home electricity usage data is collected has grown, allowing for sophisticated data analysis that was previously unavailable. Indeed, adopting Smart Grid (SG) networks, which are freshly improved networks of linked devices, may considerably enhance the existing energy infrastructure\"s dependability, economy, and durability. The SG involves sharing a lot of data, including information on specific users\" power use. And using this information, machine learning and deep learning algorithms may be able to detect power theft users reliably. This paper presented a Convolutional Neural Network (CNN)-based model for automated network-based vulnerability scanning that has excellent classification performance in many categories. Testing from iteration two to four iterations, this study examines research to discover the ideal configuration of the sequential model (SM) for categorization. The method is validated using a two-layer design, including an efficiency of 0.92, the whole first layer is composed of 128 nodes while the second level consists of 64 nodes. This allows for the development of a higher-level classifier for electrical signals, which may be employed in a number of applications. CNN was used to create electrical signal detectors, and SM was used to extract data from an electricity usage dataset. Furthermore, the number of features in the data set can be reduced using the Blue Monkey (BM) approach, and these results are then used to develop high-performance models. In this regard, the focus of this study has been on lowering the amount of needed features in the dataset in order to establish a rising classification algorithm for electrical signals. Experiments have applied the proposed systems\" fantastic performance, with just 666 characteristics required to combine the CNN and BM methods. Comparative to 1035 traits when CNN was used alone. This shows that the CNN and BM models are better than the CNN model in terms of lowering sufficient know while maintaining the same reliability.

© 2022 IEEE.Deep transfer learning is one of the common techniques used to classify different types of cancer. The goal of this research is to focus on and adopt a fast, accurate, suitable, and reliable for classification of colorectal cancer. Digital histology images are adjustable to the application of convolutional neural networks (CNNs) for analysis and classification, due to the sheer size of pixel data present in them. Which can provide a lot of information about colorectal cancer. We used ten different types of pr-trained models with two type method of classification techniques namely (normal classification and k-fold crosse validation) to classify the tumor tissue, we used two different kinds of datasets were these datasets consisting of three classes (normal, low tumors, and high tumors). Among all these eight models of deep transfer learning, the highest accuracy achieved was 96.6% with Darknet53 for 5-Fold and for normal classification the highest results obtained was 98.7% for ResNet50. Moreover, we compared our result with many other papers in stat-of-the-art, the results obtained show clearly the proposed method was outperformed the other papers.

Fuel consumption is one of the biggest expense items in the operation of ships. Fuel consumption takes place via the main engine for propulsion of the ship and diesel generators for all other auxiliary engines. According to IMO rules, when a new machine system needs to be integrated into the ship, it is required to have low fuel consumption in terms of energy efficiency and emissions. The same is true for ballast treatment. Ballast water treatment systems (BWTS) are available in many different types of marine markets. Ship operators want to choose BWTS that will consume minimum fuel and operate at maximum efficiency. Therefore, in this study, fuel consumption under both IMO and USGC conditions, and hence the operational cost, is calculated if the UV-based BWTS system is integrated into a bulk carrier ship. While making this calculation, different generator loads and the use of different fuels (VLSFO, MGO and IFO380) used on the ships were taken into account. As a result, the highest cost is $9773 when the most expensive fuel, MGO, is used and operation is performed with a single ballast pump. In USCG mode, the minimum cost is $6382 and the maximum cost is $18929 under the same conditions. It is seen that if the fuel price increases to 1.4 $/kg, the cost of using BWTS in IMO mode can increase to $11392, and if it drops to 0.3 $/kg, the cost of using BWTS in IMO mode can decrease to $1826. It is seen that the highest cost can go up to $22066 and the lowest cost can go down to $3983, with the change of fuel prices in the use of BWTS in USCG mode. With the resulting formulation, with the power consumption of the BWTS and the diesel generator shop trail test fuel consumption values, researchers or shipping companies can repeat the calculations for all kinds of different fuels and different amounts of UV-chambers for variable ballast operations with different ballast tank capacities. Consequently, it is thought that this study is useful in determining the additional operational cost of UV-based BWTSs.

© 2022 IEEE.This paper proposes an optimal coordination strategy for electric vehicles and energy storage devices in distribution grids besides the optimal allocation problem of renewable distributed generation (RDGs) and energy storage devices (ESDs). By finding the optimal number, size, and site of the RDGs and ESDs, together with the operation strategy of the ESDs and smart charging of a large number of EVs, the performance of the distribution grids will be improved. An advanced grey wolf optimization (AGWO) algorithm is used to minimize energy losses and voltage violations simultaneously in the test systems. Simulations are tested on IEEE 33 and 69 bus networks to find near-optimal solutions for the optimization problem. Based on the simulation results, the proposed optimization framework reduced the systems\" losses while minimizing the voltage violations by finding the optimal control parameters of the devices.

In the present era, the demand for energy continues to increase and nevertheless, energy resources are gradually decreasing. Therefore, extracting energy from the operating ambient is of great importance especially for industrial applications. Among the numerous available ambient energy sources, wind energy is one of the most promising and prevalent energy sources existing in the environment. In this study, a piezoelectric energy harvester (PEH) consisting of an electromechanical coupling of GFRP cantilever beam with an embedded piezoelectric patch is developed for wind energy harvesting. The cantilever beam under the wind flow vibrates due to the pressure field that occurs on the leeward side of the beam. The generation of the pressure field is based on the vortex shedding phenomenon. Theoretical model of the regarding electromechanical coupling subjected to vortex induced vibration is presented and the effect of the pressure field having various vortex shedding frequencies on harvested power is investigated by means of numerical simulations validated with an experimental study. In order to determine the effect of the direction in which the wind excites the PEH, two wind flow conditions are considered; cross wind and head wind. According to the results, it was found that the PEH generates considerably more voltage outputs under cross wind loading than that obtained from the head wind excitation. In cross wind case, maximum open circuit voltage of 82.4 V is obtained at the wind speed of 6 m/s with the vortex shedding frequency of 18 Hz, which is very close to the second resonance frequency of the PEH. With a calculated load resistance of 100 kΩ, the resulting maximum direct voltage and electric power is 58.7 V and 11.5 mW, respectively. As far as the energy efficiency of PEH is concerned, it is determined that the efficiency is about 0.75 for the frequency of 18 Hz, which is quite acceptable for energy harvesting. It is concluded that a composite PEH with an embedded piezoelectric patch can be used as an effective energy harvester for the vortex induced vibration when the vortex shedding frequency is close to its resonance frequency.

Gemilerin çoğunda elektrik enerjisi ihtiyacı dizel jeneratör grupları ile karşılanmaktadır. Gemilerin türüne bağlı olarak gemilerde farklı sayılarda ve kapasitelerde jeneratör grupları bulunabilir. Gemilerde elektrik enerjisi ihtiyacının birden fazla jeneratör ile karşılanması durumunda diğer jeneratörün senkronize bir şekilde devreye alınması gerekmektedir. Bu süreç hem otomatik hem de manuel olarak yürütülebilmektedir. Bu çalışmada, bir gemide iki jeneratörün senkronizasyon süreci Matlab&Simulink programında bir benzetim çalışması yapılarak incelenmiştir. Sonrasında, senkronizasyon sürecinde jeneratör baralarındaki elektriksel parametrelerin değişimleri yorumlanmıştır. Bu çalışma ile özellikle gemi personelinin senkronizasyon süreci hakkında teorik bilgi edinmesi ve literatüre gemi elektriği alanında katkı sunulması amaçlanmıştır. The electrical energy needs of ships are generally met by diesel generator sets. Depending on the type of ships, there may be different numbers and capacities of generator sets on the ships. If the electrical energy needs of ships are met by more than one generator, the other generator should be activated in a synchronized manner. This process can be carried out both automatically and manually. In this study, the synchronization process of two generators on a ship was performed by making a simulation study in Matlab&Simulink. Then, the changes in the electrical parameters in the generator busbars during the synchronization process were interpreted. With this study, it is aimed to obtain theoretical knowledge about the synchronization process of ship personnel and to contribute to the literature in the field of ship electricity.

In this research, the advantages of the e-scooter tool used in the mail or package delivery process were discussed by considering the Turkish Post Office (PTT) data in the districts of Istanbul (Kadıköy, Üsküdar, Kartal, and Maltepe) in Turkey. The optimization Poisson regression model was utilized to deliver the maximum number of packages or mails with minimum cost and the shortest time in terms of energy consumption, cost, and environmental contribution. Statistical and optimization results of dependent and independent variables were calculated using numerical and categorical features of 100 e-scooter drivers. The Poisson regression analysis determined that the e-scooter driver’s gender (p|0.05 < 0.199) and age (p|0.05 < 0.679) factors were not effective on the dependent variable. We analysed that the experience in the profession (tenure), the size of the area responsible, and environmental factors is effective in the e-scooter distribution activity. The number of packages delivered was 234 in a day, and the delivery cost per package was calculated as 0.51 TL (Turkish Lira) for the optimum values of the dependent variables. The findings show that the choice of e-scooter vehicle in the mail or package delivery process is beneficial in terms of time, cost, energy, and environmental contribution in districts with higher population density. As the most important result, the operation of e-scooter vehicles with electrical energy shows that it is environmentally friendly and has no CO2 emission. The fact that the distribution of packages or mail should now turn to micro-mobility is emerging with the advantages of e-scooter vehicles in the mail and package delivery. Finally, this analysis aims to provide a model for integrating e-scooters in package or mail delivery to local authorities, especially in densely populated areas.

For long decades, Nigeria has the highest population in Africa and has been struggling by slow economic growth, poor GDP per capita, high unemployment, and a host of other problems.These problems affect the country's energy sector which in turn leads to a negative crisis feedback loop. The Nigeria energy sector has been labeled by both its citizens and foreigners as a total failure in terms of economic perspective. Despite the continuous government investment over the years, there has been a slight growth in the sector with an ever-rising demand due to its population explosion, leading to a total breakdown across Nigeria economic and industrial development. This study aims to examine how the country can maximize its full energy potential by turning towards the vast quantities of solar resources at its disposal. A review of the nation’s solar energy policies was done with the aim to identify the barriers hindering the country’s solar development, the serviceability of solar energy to the country. Researchers attempt to demonstrate Nigeria's energy gains through the incorporation of solar energy into the country's energy resources.

Solar energy has increased in its share of global electrical energy production. The increasing reliability of solar energy has positively affected the sustainability of photovoltaic (PV) power plants. A failure in any module in the plant can reduce or interrupt the production of electrical energy, causing significant losses in both efficiency and asset value. Therefore, responding to a fault as quickly as possible in a PV power plant is critical. The ability of the PV plant operator to react to potential faults is directly related to the rapid detection of faulty modules. In this paper, different PV monitoring systems in the literature are investigated extensively from the point of view of the devices and the techniques used to measure PV systems\" current, voltage, solar radiation, and module temper-ature. In particular, the communication methods and data acquisition cards used in monitoring were examined. Remote monitoring technologies quickly detect the location of a malfunction in a large-scale power plant. In this context, traditional wire communication methods, today\"s communication technologies, and the low-cost IoT (Internet of Things) technologies used to monitor the performance of large and small-scale PV power plants are compared in detail. With the advancement of Internet of Things technologies such as Zigbee and LoRa, research on remote wireless monitoring of photovoltaic modules has accelerated in recent years. These technologies are projected to be widely deployed in the near future for the maintenance and fault detection of numerous photovoltaic installations.

In this study, a laboratory-scale cooling system, simulating a household refrigerator, was examined experimentally for an average cabinet temperature of 4 degrees C with two different types of phase change materials (PCMs) (water and eutectic solution). The system was tested with various amounts of water and different concentrations of sodium sulfate (Na2SO4) in water. The influence of different amounts and types of the PCMs on the cabinet air temperature and compressor power consumption was analyzed during the running period. The cabinet air temperature change over time was also observed during the power failure period. The examinations suggest using 1.0 wt.% Na2SO4 solution as the PCM in the cooling systems. This solution provides the lowest energy consumption (19.5 kJ), and the running time percentage (21.7%); while maximizing the energy saving (14.2%). In addition, integrating it as PCM could allow preserving products for long periods without significant quality loss during a power failure; because it prevented the rapid increase of the cabinet air temperature in this scenario. Lastly, when the cycle frequency is considered, it has the best time interval and the number of cycles (5.3). Thus, it has a positive effect on reducing the compressor cycling frequency, which eventually increases the compressor lifespan.

Today, where clean, renewable and high efficiency energy production gains importance, methane gas draws attention due to its low carbon content. In this study, flame instability and temperature of methane gas were tested in a premixed model gas turbine combustor at different helium dilution conditions. The burner power was kept constant as 3 kW and the equivalence ratio as 0.7. In addition, a swirl generator with a swirl number of 1 is placed at the burner outlet. The dynamic pressure values of the flame were recorded under external acoustic enforcements at different frequencies applied to the flame and thermo-acoustic combustion instability was interpreted. Methane flame diluted with Helium at 10, 20, 30, 40 and 45 volumetric ratios showed the following results. If helium dilutions of up to 20% did not significantly affect flame instability, instability increased at 30% He. After this critical value, when 45% He dilution was tested, the lowest instability value was determined. In addition, the burner exit temperature of the flame decreased at all helium dilution ratios.

© 2022 IEEE.This paper solves the optimal operation problem of distribution systems using renewable energy sources and voltage regulators. The developed model makes use of Whale Optimization Algorithm based optimization. We apply the proposed optimization model to a modified low voltage distribution system of Almaty, Kazakhstan. Three different cases were simulated. The cases considered are medium load level with medium PV power output, high load level with medium PV output, and high load level and low PV power outputs. The simulation results show that the proposed algorithm is able lower the active power losses.

© 2022 IEEE.Increased photovoltaic (PV) penetration in distribution systems helps improve the system\"s performance by reducing the active power loss, in addition to the environmental benefits. However, high PV generation during light loading periods results in reverse power flows in the system. In turn, the voltage increases at the nodes located further from the main substation. This paper proposes a reactive power control method to coordinate the participation of different PV smart inverters in solving the overvoltage problem. The proposed control method operates at the lateral level based on the measured voltage at the lateral\"s end-node (or most downstream PV system). The lateral controller sequentially dispatches power factor commands to the smart inverters. This method maintains the coordination between the PV systems at different operating conditions keeping the reactive power requirement as low as possible. The proposed control method is compared to the volt/var control method from the IEEE standard 1547 and shows an improved performance in terms of reactive power requirement and active power loss.

Solar energy is considered as one of the clean and sustainable energy sources. As known, big portion of the energy demand in industrial processes are generally met by fossil energy sources. Utilizing renewable and sustainable energy technologies in industrial facilities can decrease negative environmental effects. In this study, applicability of a rooftop solar energy generation system in an industrial building has been analyzed. In the simulation process, PvSOL software has been employed. Considering available areas on the roof of the facility, solar electrical energy generation system with installed power of 573.75 kWp was planned and simulated. Moreover, economic analysis results of the proposed rooftop solar energy system were presented within the scope of this research. According to the economic analysis outcomes, payback period of the proposed rooftop energy system was achieved less than 4 years.

A Virtual Power Plant system is an advanced power distributing and trading platform, that acts as a smart grid system unlike the existing conventional methodology of power allocation. The system is known to facilitate the connection of renewable energy sources to the national grid from a specific region, it is made up of Energy Storage System, Distributable Energy Resources, and Control System. Energy sources are classified as Distributable Energy Resources and various assets can be linked to the platform such as small-scale microgrids or community-based power platforms with demand-side management portfolios. A Virtual Power Plant platform has the power-distributing capability and an evolutionary trading platform (Peer to Peer trading). It has also proven to cut down carbon emissions as more renewables find their way to the grid. Additionally, data analytics and forecasting tools on the Virtual Power Plant are used to give information to the end-users on their storage, demand, and expected future generation, the user can interact with the system through a Human Machine Interface that has easy to use dashboard. Currently, the VPP systems have been implemented as pilot programs in countries such as Sweden, Norway, Belgium, and the USA. The potential application of the system can be extended as a case study and futuristic smart grid system for Kenya, as the National grid is substantially fed from renewable energy sources, and the vast majority of rural areas can benefit from cheap and affordable energy. Finally, Virtual Power Plants are proven to be reliable systems, and power outages and delays can be minimized.

With the rising concerns about climate change and technological developments, the deployment of low carbon technologies (LCT) is gaining importance for reliable and sustainable power system operation. To decarbonize the heat and transportation sectors, LCTs such as heat pumps (HP) and electric vehicles (EV) are integrated into the power system from the low voltage (LV) distribution network, where predominantly end-users are connected. However, the increasing penetration of EVs and HPs, together with distributed photovoltaic (PV) systems on the demand side, can cause technical challenges in LV distribution networks, such as under/over voltages at the far end of the feeders. Therefore, the hosting capacity of a grid for LCTs is limited due to network constraints such as line ampacity, bus voltage, and frequency. In this paper, voltage-constrained management approaches for LCTs are proposed to improve the grid hosting capacity in a real large-scale distribution network. Moreover, HPs, PVs, battery energy storage systems (BESS), and EVs as well as their vehicle-to-grid (V2G) feature are evaluated as LCTs. The uncertain behavior of these technologies is taken into consideration for more realistic analyses. In addition, the charging and discharging interactions of BESSs are controlled by following the power consumption profiles from the economic point of view. Furthermore, the hourly carbon data is used to control BESSs from an emission-sensitive aspect. To demonstrate the effectiveness of the proposed algorithms, a series of tests is conducted on a real distribution network model. The results show that the hosting capacity of the considered LV network can be increased from 35% to 50% using the proposed algorithms. The promising results obtained in this study pave the way for future active LCT management studies to improve hosting capacity in urban networks, and pilot demonstrations in the field.