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Abstract Renewable energy has gained popularity as an alternative to fossil fuels, which regularly emit large amounts of Greenhouse Gases and consume/withdraw large amounts of water, but renewable energy market penetration is still limited while fossil fuels are still the U.S.‘s dominant power source. This is due to resistance in the market, or in this case, the failure of renewable energy policies to achieve long-term environmental sustainability due to neglected external factors (economic, societal, etc.). No available literature analyzes potential sources and/or effects of this policy resistance, so this research investigates the underlying mechanisms in the renewable energy generation market by utilizing a system dynamics model. A two-alternative Generalized Bass Model was developed to simulate the renewable energy market (specifically with respect to solar PV and wind energy), including the environmental, societal, and economic concerns associated with each of the alternatives evaluated in this study, so as to identify and address possible causes of policy resistance and its subsequent effects on environmental impacts (esp. GHG emissions and water withdrawal rates). Based on this model, three separate policy areas (solar PV investments, wind power investments, and the elimination of fossil fuel subsidies) and various combinations thereof were proposed and tested within the context of the model. Based on the results of this study, it is highly recommended to invest as generously as possible into multiple renewable energy industries, reduce fossil fuel subsidies (in turn freeing up funding for renewable energy investments), and seek further advancement in renewable energy technologies (e.g. enhancing the useable lifetimes of wind turbines). A balanced policy have potential to increase the share of renewable's up to roughly 40% in the U.S. by 2050, as well as 17% and 32% GHG and water withdrawal reduction potential by 2050.

La tecnología de almacenamiento de energía es uno de los principales componentes de la integración de las energías renovables y la descarbonización de los sistemas energéticos mundiales. Se beneficia significativamente al abordar los servicios de energía auxiliares, la estabilidad de la calidad de la energía y la confiabilidad del suministro de energía. Sin embargo, los últimos años de la pandemia de COVID-19 han dado lugar a la crisis energética en diversos sectores industriales y tecnológicos. Para resolver estos desafíos, se realiza una encuesta integrada sobre el desarrollo de la tecnología de almacenamiento de energía, su clasificación, rendimiento y gestión segura. El desarrollo de la tecnología de almacenamiento de energía se ha clasificado en métodos electromecánicos, mecánicos, electromagnéticos, termodinámicos, químicos e híbridos. El estudio actual identifica tecnologías potenciales, marco operativo, análisis de comparación y características prácticas. Este estudio propuesto también proporciona información útil y práctica a los lectores, ingenieros y profesionales sobre los efectos económicos globales, los efectos ambientales globales, la resiliencia de la organización, los desafíos clave y las proyecciones de las tecnologías de almacenamiento de energía. También se propone un modelo de programación óptimo. A continuación, se describen las políticas de adaptación sostenible. Se ha recopilado una extensa lista de publicaciones hasta la fecha en la literatura abierta para retratar diversos desarrollos en esta área. La technologie de stockage de l'énergie est l'un des principaux composants de l'intégration des énergies renouvelables et de la décarbonisation des systèmes énergétiques mondiaux. Il bénéficie considérablement des services d'alimentation auxiliaires, de la stabilité de la qualité de l'énergie et de la fiabilité de l'alimentation électrique. Cependant, les dernières années de la pandémie de COVID-19 ont donné lieu à la crise énergétique dans divers secteurs industriels et technologiques. Une enquête intégrée sur le développement de la technologie de stockage d'énergie, sa classification, ses performances et sa gestion sûre est réalisée pour résoudre ces problèmes. Le développement de la technologie de stockage d'énergie a été classé en méthodes électromécaniques, mécaniques, électromagnétiques, thermodynamiques, chimiques et hybrides. La présente étude identifie les technologies potentielles, le cadre opérationnel, l'analyse comparative et les caractéristiques pratiques. Cette étude proposée fournit également des informations utiles et pratiques aux lecteurs, ingénieurs et praticiens sur les effets économiques mondiaux, les effets environnementaux mondiaux, la résilience des organisations, les principaux défis et les projections des technologies de stockage d'énergie. Un modèle d'ordonnancement optimal est également proposé. Les politiques d'adaptation durable sont ensuite décrites. Une longue liste de publications à ce jour dans la littérature ouverte est sollicitée pour décrire divers développements dans ce domaine. Energy Storage Technology is one of the major components of renewable energy integration and decarbonization of world energy systems. It significantly benefits addressing ancillary power services, power quality stability, and power supply reliability. However, the recent years of the COVID-19 pandemic have given rise to the energy crisis in various industrial and technology sectors. An integrated survey of energy storage technology development, its classification, performance, and safe management is made to resolve these challenges. The development of energy storage technology has been classified into electromechanical, mechanical, electromagnetic, thermodynamics, chemical, and hybrid methods. The current study identifies potential technologies, operational framework, comparison analysis, and practical characteristics. This proposed study also provides useful and practical information to readers, engineers, and practitioners on the global economic effects, global environmental effects, organization resilience, key challenges, and projections of energy storage technologies. An optimal scheduling model is also proposed. Policies for sustainable adaptation are then described. An extensive list of publications to date in the open literature is canvassed to portray various developments in this area. تعد تقنية تخزين الطاقة أحد المكونات الرئيسية لتكامل الطاقة المتجددة وإزالة الكربون من أنظمة الطاقة العالمية. وهو يفيد بشكل كبير في معالجة خدمات الطاقة الإضافية، واستقرار جودة الطاقة، وموثوقية إمدادات الطاقة. ومع ذلك، أدت السنوات الأخيرة من جائحة كوفيد-19 إلى أزمة الطاقة في مختلف القطاعات الصناعية والتكنولوجية. يتم إجراء مسح متكامل لتطوير تكنولوجيا تخزين الطاقة وتصنيفها وأدائها وإدارتها الآمنة لحل هذه التحديات. تم تصنيف تطوير تكنولوجيا تخزين الطاقة إلى طرق كهروميكانيكية وميكانيكية وكهرومغناطيسية وديناميكية حرارية وكيميائية وهجينة. تحدد الدراسة الحالية التقنيات المحتملة والإطار التشغيلي وتحليل المقارنة والخصائص العملية. توفر هذه الدراسة المقترحة أيضًا معلومات مفيدة وعملية للقراء والمهندسين والممارسين حول الآثار الاقتصادية العالمية والآثار البيئية العالمية ومرونة المنظمة والتحديات الرئيسية وتوقعات تقنيات تخزين الطاقة. كما يُقترح نموذج جدولة أمثل. ثم يتم وصف سياسات التكيف المستدام. يتم فحص قائمة واسعة من المنشورات حتى الآن في الأدبيات المفتوحة لتصوير التطورات المختلفة في هذا المجال.

Abstract In pursuit of the United Nations (UN) Sustainable Development Goals (SDGs), nations are growing more conscious of the importance of implementing SDGs and adopting various tools and frameworks to advance environmental and human development. Current study aims to investigate the environmental impacts of airport ground operations through Life Cycle Assessment (LCA) and was conducted on three different Ground Power Units (GPU) namely, diesel, biodiesel, and electric-powered by adopting a system boundary of cradle-to-gate, using SimaPro version 9.4 software and adopted a CML Baseline V3.09 EU25 characterization model. Results show that the highest environmental impact was caused by diesel-powered GPU, followed by the biodiesel-powered GPU. At the same time, the electric-powered GPU contributed to lower environmental impact in comparison. The Abiotic Depletion (AD) in the diesel, biodiesel, and electric-powered GPU in a respective manner was (in kg Sb eq, 0.196, 0.196 and 0.162), global warming (kg CO2 eq of 1142, 1130 and 1044), Ozone Depletion Potential (ODP) (kg CFC-11 eq of 0.0003, 0.0001 and 0.0001), Human Toxicity Potential (HTP) (kg 1,4-DB eq of 516.49, 510.96 and 549.29), Freshwater Aquatic Ecotoxicity (kg 1,4-DB eq of 441.56, 463.22 and 605.91), Terrestrial Ecotoxicity (kg 1,4-DB eq of 2.74, 2.31 and 2.35), Photochemical Oxidation (kg C2H4 eq of 0.609, 0.70 and 0.545), Acidification (kg SO2 eq of 11.01, 11.23 and 10.11) and Eutrophication of (kg PO4 eq 3.432, 3.459 and 3.2311). Batteries, diesel, aluminium, wheel rims, and synthetic rubber were the main contributors to these environmental impacts. It was concluded that lead-ion batteries are a good replacement to lithium-ion batteries due to their lower impact. Similarly, switching to stationary GPUs rather than mobile, can contribute to lowering impacts as the wheel rims in mobile GPUs are the main contributors to overall environmental impact of airport ground operations.

Abstract By applying the principles of the second law of thermodynamics and utilizing the HSC Chemistry software, the thermodynamic equilibrium and efficiency analysis of the CaSO4 CaO water splitting cycle was performed in this investigation. The temperatures desirable and the equilibrium compositions allied with the thermal reduction of CaSO4 and the re-oxidation of CaO via water splitting reaction were estimated. The obtained results indicate that the thermal reduction temperature (TH) required to completely decompose the CaSO4 was decerased from 2220 to 1890 K due to the rise in the molar flow rate of ( n ˙ A r ) from 1 to 50 mol/s. In addition, the consequence of the TH, n ˙ A r , and the water splitting temperature ( T L ) on the process parameters such as total amount of solar energy needed, re-radiation losses, energy dissipated by the water splitting reactor and others associated with the CaSO4 CaO water splitting cycle was scrutinized. By utilizing higher n ˙ A r from 1 to 50 mol/s, the TH was decreased from 2200 to 1890 K. However, as the n ˙ A r was increased from 1 to 50 mol/s, the amount of heat energy needed to heat the Ar was also upsurged from 12.5 to 625.6 kW. This rise in the Q ˙ A r − h e a t i n g , directly reflected into an increase in the Q ˙ s o l a r − c y c l e from 1063.4 up to 2653.9 kW. The findings of this study further confirms that the maximum solar-to-fuel energy conversion efficiency ( η s o l a r − t o − f u e l ) equal to 27.4% was realized by conducting the CaSO4 CaO water splitting cycle at TH = 2220 K, n ˙ A r = 1 mol/s, and TL = 1100 K. By using 50% of the recuperable heat, the η s o l a r − t o − f u e l of the CaSO4 CaO water splitting cycle can be enhanced up to 36.2%.

Abstract Fuel cells convert the chemical energy present in fuel (e.g., hydrogen) into electrical energy with high efficiency, low pollution and low noise. Of the various types of fuel cells, the solid oxide fuel cell (SOFC) was developed specifically for power plants and residual power systems. SOFCs are classified into three categories based on their shape: planar, cylindrical and flat-tube. The flat-tube SOFC (FT-SOFC) exhibits the advantages of ease in sealing, low stack volume and low current-collecting resistance. However, due to its weak strength, the FT-SOFC may get deformed or break during the manufacturing process. To improve the cell strength, the cell support must be thickened. However, as the support thickness is increased, the electrons must travel a longer distance, which leads to an increase in the electrical resistance. In another method, the hydrogen channel diameter can be reduced for the strong strength. But, it may lead to a corresponding decrease in the hydrogen mass transfer rate. In this manuscript, we study the performance of several FT-SOFC designs and suggest the better design. The numerical analysis for the FT-SOFC incorporates several physical phenomena such as gas flow, heat transfer and electrochemical reactions. The governing equations (i.e., mass, momentum, energy and species balance equations) are calculated for heat and mass transfer. The open circuit voltage, activation polarization, ohmic polarization and contact resistance are simulated simultaneously. The experimental results are compared with the numerical data for the purposes of code validation. The current density and temperature distribution are then investigated on the SOFC surface. The average current density decreases by 14.6% if the hydrogen channel diameter is narrowed by 50%, and by 10.2% if the support thickness is increased by 50%. Based on these results, we present a design for a stack of FT-SOFCs.

Abstract The Cold Lake development, located in Alberta, Canada, is the world’s largest heavy oil in situ thermal development. At Cold Lake, operated by Imperial Oil Resources, an ExxonMobil affiliate, the Cyclic Steam Stimulation (CSS) process is used to produce 23,500 m3/d (150 kB/d) of heavy oil. In 2009, Cold Lake produced its one billionth barrel (160 million m3) of heavy oil. The Nabiye project will be the fifth central steam generation and fluid processing hub added at Cold Lake. Nabiye (Dené for Otter) continues the historical Cold Lake development concept of maximizing value through the utilization of a phased development strategy. Relative to current operations, the key reservoir difference at Nabiye is reduced pay thickness. Averaging 12 meters (40 feet), Nabiye pay is about half as thick as the initial pads of the previous expansion (Mahkeses). While reservoir of similar thickness as Nabiye is currently being developed as Productivity Maintenance pads to sustain production in the existing operation, the risk profile for Nabiye is higher because new plant investment is required. As Cold Lake develops more challenging subsurface environments, more advanced reservoir engineering techniques must be employed to mitigate risk. This paper describes the extensive use of both thermal simulation and wellbore integrity modeling to complement analog performance prediction techniques. This paper will demonstrate how the Nabiye project is effectively commercializing an unconventional resource by integrating analog performance data and advanced reservoir and geomechanical modeling. The application of (1) thermal simulation for performance prediction and (2) geomechanical modeling for steam strategy optimization will be presented.

Abstract The thermal performance of the thermosyphon water heater unit was analyzed to show its applicability in Bahrain, using data of several sunny, cloudy and hazy days in winter. The performance of this unit was studied under various maximum daily solar intensities, ranging from 1, 2 and 3 on a cloudy day, upto 695 W/m 2 on a sunny day, with the daily outside temperature ranges between 25–19°C. The results show that the system has an average efficiency of 38% with storage tank temperature above 50°C. These results show that this system is quite suitable for application in Bahrain weather conditions.

The random forest (RF) classifier, which is a combination of tree predictors, is one of the most powerful classification algorithms that has been recently applied for fault detection and diagnosis (FDD) of industrial processes. However, RF is still suffering from some limitations such as the noncorrelation between variables. These limitations are due to the direct use of variables measured at nodes and therefore the only use of static information from the process data. Thus, this article proposes two enhanced RF classifiers, namely the Euclidean distance based reduced kernel RF (RK-RF $_{\text{ED}}$ ) and K-means clustering based reduced kernel RF (RK-RF $_{\text{Kmeans}}$ ), for FDD. Based on the kernel principal component analysis, the proposed classifiers consist of two main stages: feature extraction and selection, and fault classification. In the first stage, the number of observations in the training data set is reduced using two methods: the first method consists of using the Euclidean distance as dissimilarity metric so that only one measurement is kept in case of redundancy between samples. The second method aims at reducing the amount of the training data based on the K-means clustering technique. Once the characteristics of the process are extracted, the most sensitive features are selected. During the second phase, the selected features are fed to an RF classifier. An emulated grid-connected PV system is used to validate the performance of the proposed RK-RF $_{\text{ED}}$ and RK-RF $_{\text{Kmeans}}$ classifiers. The presented results confirm the high classification accuracy of the developed techniques with low computation time.