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Smart cities, as well as smart homes research, are becoming of concern, especially in the field of energy consumption and production. However, there is a lack in the dataset that can be used to simulate smart city energy consumption and prediction or even smart homes. Therefore, this paper provides a carefully generated dataset for smart home energy management simulation. Five datasets are generated and analysed to ensure suitability, including 20, 50, 100, and 200 homes across 365 days. For more accurate data, energy consumption and production for 50 homes are generated based on real input taken from a dataset for homes in Saudi Arabia. Due to the unavailability of a comprehensive dataset related to the complex scenario of smart home sensors, energy consumption, and peer-to-peer data exchange, synthetic data was generated to support the simulation of smart home energy generation and consumption. This synthetic data plays a crucial role in situations where simulating uncommon events, ensuring data availability, facilitating extensive experimentation and model validation, and enabling scalability are paramount. It offers a valuable opportunity to incorporate these rare yet significant occurrences into the simulation, particularly in the context of infrequent events, such as abnormal energy consumption patterns observed in smart homes. The generated data is analysed and validated in this article, ready to be used for many smart home and city research.

Experimental investigations of an air gap membrane distillation (AGMD) unit were carried out to study the energy-saving by heat recovery. The spiral air gap membrane module in the water desalination unit was used. The unit was configured to operate in two novel arrangements and designed to minimize the loss of heat within the drains which maximize the unit productivity as well as the thermal efficiency. Water of salt concentrations 10,000 ppm and 20,000 ppm were used. Measurements of the heat source in the form of inlet and outlet temperatures, water productivity, and thermal efficiency are conducted for different flow rates of coolant and water feeds. The new arrangements are found to save much of the supplied heat, minimize the heat loss, and maximize the unit performance. An enhancement of 38.62% in the water productivity was achieved compared to the conventional AGMD unit. The considered heat recovery system showed water productivity of 155.92 m3/year for the proposed fresh potable water system with a cost of $12.85 per m3.

Dans le contexte des systèmes d'énergie renouvelable, les micro-réseaux (MG) sont une solution pour améliorer la fiabilité des systèmes électriques. Au cours des dernières années, il y a eu une utilisation croissante des systèmes de stockage d'énergie (SSE), tels que les systèmes de stockage d'hydrogène et de batterie, en raison de leur nature respectueuse de l'environnement en tant que dispositifs de conversion de puissance. Cependant, leur courte durée de vie représente un défi majeur pour leur commercialisation à grande échelle. Pour résoudre ce problème, la stratégie de contrôle proposée dans cet article comprend des fonctions de coût qui tiennent compte de la dégradation des dispositifs à hydrogène et des batteries. De plus, le contrôleur proposé utilise des scénarios pour refléter la nature stochastique des ressources en énergie renouvelable (SER) et de la demande de charge. L'objectif de cet article est d'intégrer une stratégie de contrôle prédictif de modèle stochastique (RCP) pour une MG économique/environnementale couplée à des ESS d'hydrogène et de batterie, qui interagit avec le réseau principal et les consommateurs externes. La participation du système au marché de l'électricité est également gérée. Des analyses numériques sont menées à l'aide de profils res et de prix au comptant de panneaux solaires et de parcs éoliens à Abou Dhabi, aux Émirats arabes unis, pour démontrer l'efficacité du contrôleur proposé en présence d'incertitudes. Sur la base des résultats, il a été prouvé que le contrôle développé gère efficacement le système intégré en répondant aux contraintes globales et aux demandes d'énergie, tout en réduisant le coût opérationnel des dispositifs à hydrogène et en prolongeant la durée de vie de la batterie. En el contexto de los sistemas de energía renovable, las microrredes (MG) son una solución para mejorar la fiabilidad de los sistemas de energía. En los últimos años, ha habido un uso creciente de sistemas de almacenamiento de energía (ESS), como los sistemas de almacenamiento de hidrógeno y baterías, debido a su naturaleza respetuosa con el medio ambiente como dispositivos convertidores de potencia. Sin embargo, su corta vida útil representa un gran desafío para su comercialización a gran escala. Para abordar este problema, la estrategia de control propuesta en este documento incluye funciones de costo que consideran la degradación tanto de los dispositivos de hidrógeno como de las baterías. Además, el controlador propuesto utiliza escenarios para reflejar la naturaleza estocástica de los recursos de energía renovable (FER) y la demanda de carga. El objetivo de este documento es integrar una estrategia de control predictivo de modelo estocástico (SMPC) para un MG económico/ambiental junto con ESS de hidrógeno y batería, que interactúa con la red principal y los consumidores externos. También se gestiona la participación del sistema en el mercado eléctrico. Los análisis numéricos se realizan utilizando perfiles RES y precios al contado de paneles solares y parques eólicos en Abu Dhabi, Emiratos Árabes Unidos, para demostrar la efectividad del controlador propuesto en presencia de incertidumbres. Con base en los resultados, se ha demostrado que el control desarrollado gestiona de manera efectiva el sistema integrado al cumplir con las restricciones generales y las demandas de energía, al tiempo que reduce el costo operativo de los dispositivos de hidrógeno y extiende la vida útil de la batería. In the context of renewable energy systems, microgrids (MG) are a solution to enhance the reliability of power systems. In the last few years, there has been a growing use of energy storage systems (ESSs), such as hydrogen and battery storage systems, because of their environmentally-friendly nature as power converter devices. However, their short lifespan represents a major challenge to their commercialization on a large scale. To address this issue, the control strategy proposed in this paper includes cost functions that consider the degradation of both hydrogen devices and batteries. Moreover, the proposed controller uses scenarios to reflect the stochastic nature of renewable energy resources (RESs) and load demand. The objective of this paper is to integrate a stochastic model predictive control (SMPC) strategy for an economical/environmental MG coupled with hydrogen and battery ESSs, which interacts with the main grid and external consumers. The system's participation in the electricity market is also managed. Numerical analyses are conducted using RESs profiles, and spot prices of solar panels and wind farms in Abu Dhabi, UAE, to demonstrate the effectiveness of the proposed controller in the presence of uncertainties. Based on the results, the developed control has been proven to effectively manage the integrated system by meeting overall constraints and energy demands, while also reducing the operational cost of hydrogen devices and extending battery lifetime. في سياق أنظمة الطاقة المتجددة، تعد الشبكات الدقيقة (MG) حلاً لتعزيز موثوقية أنظمة الطاقة. في السنوات القليلة الماضية، كان هناك استخدام متزايد لأنظمة تخزين الطاقة (ESSs)، مثل أنظمة تخزين الهيدروجين والبطاريات، بسبب طبيعتها الصديقة للبيئة كأجهزة تحويل الطاقة. ومع ذلك، فإن عمرها القصير يمثل تحديًا كبيرًا لتسويقها على نطاق واسع. لمعالجة هذه المشكلة، تتضمن استراتيجية التحكم المقترحة في هذه الورقة وظائف التكلفة التي تأخذ في الاعتبار تدهور كل من أجهزة الهيدروجين والبطاريات. علاوة على ذلك، تستخدم وحدة التحكم المقترحة سيناريوهات لتعكس الطبيعة العشوائية لموارد الطاقة المتجددة (RESs) والطلب على الحمولة. الهدف من هذه الورقة هو دمج استراتيجية التحكم التنبؤي للنموذج العشوائي (SMPC) من أجل MG اقتصادي/بيئي إلى جانب ESSs للهيدروجين والبطارية، والتي تتفاعل مع الشبكة الرئيسية والمستهلكين الخارجيين. كما تتم إدارة مشاركة النظام في سوق الكهرباء. يتم إجراء التحليلات العددية باستخدام ملفات تعريف RESs، والأسعار الفورية للألواح الشمسية ومزارع الرياح في أبو ظبي، الإمارات العربية المتحدة، لإثبات فعالية وحدة التحكم المقترحة في وجود حالات عدم اليقين. بناءً على النتائج، ثبت أن التحكم المطور يدير النظام المتكامل بفعالية من خلال تلبية القيود الإجمالية ومتطلبات الطاقة، مع تقليل التكلفة التشغيلية لأجهزة الهيدروجين وإطالة عمر البطارية.

The morphology of built environments has a significant effect on human well-being. To match the emotional effect of natural environment, architects need to create connections with its stimuli. In Islamic architecture, and due to the strict prohibition of depictions of human and animal forms, geometry was the only appropriate tool to create these connections through tessellations, stalactites, and motifs that cascade without an end. This paper employs Christopher Alexander’s 15 properties of Art and Nature as a preliminary qualitative tool for analyzing the visual properties of Nasir El-Molk mosque to measure how far the architects succeeded in creating these connections. A numerical model by Nikos Salingaros was also employed for a quantitative measurement of these qualities. The paper concludes that the building's design was based on a thoughtful process focused on extracting the qualities of Creation and reproducing them in abstract compositions to give the building qualities of Nature and Life.

The sudden increase in the concentration of carbon dioxide (CO2) in the atmosphere due to the high dependency on fossil products has created the need for an urgent solution to mitigate this challenge. Global warming, which is a direct result of excessive CO2 emissions into the atmosphere, is one major issue that the world is trying to curb, especially in the 21st Century where most energy generation mediums operate using fossil products. This investigation considered a number of materials ideal for the capturing of CO2 in the post-combustion process. The application of aqueous ammonia, amine solutions, ionic liquids, and activated carbons is thoroughly discussed. Notable challenges are impeding their advancement, which are clearly expatiated in the report. Some merits and demerits of these technologies are also presented. Future research directions for each of these technologies are also analyzed and explained in detail. Furthermore, the impact of post-combustion CO2 capture on the circular economy is also presented.

Research and development in the field of renewable energy is receiving more attention as a result of the growing demand for clean, sustainable energy. This paper proposes a model for forecasting renewable energy generation. The proposed model consists of three main phases: data preparation, feature selection-based rough set and nutcracker optimization algorithm (NOA), and data classification and cross-validation. First, the missing values are tackled using the mean method. Then, data normalization and data shuffling are applied in the data preparation phase. In the second phase, a new feature selection algorithm is proposed based on rough set theory and NOA, namely RSNOA. The proposed RSNOA is based on adopting the rough set method as the fitness function during the searching mechanism to find the optimal feature subset. Finally, a custom long -short -term memory architecture with the k-fold cross-validation method is utilized in the last phase. The experimental results revealed that the proposed model is very competitive. It is achieved with 4.2113 root mean square error, 0.96 R2, 2.835 mean absolute error, and 4.6349 mean absolute percentage error. The findings also show that the proposed model has great promise as a useful tool for accurately forecasting renewable energy generation across various sources. Web of Science 11 6222 6208

Abstract Direct injection spark ignition (DISI) engines have been widely used in passenger cars due to their lower fuel consumption, better controllability, and high efficiency. However, DISI engines are suffering from wall wetting, imperfect mixture formation, excess soot emissions, and cyclic variations. Applying a new fuel atomization technique and using biofuels with their distinctive properties can potentially aid in improving DISI engines. In this research, the effects of isobutanol and 2-butanol and their blends with Toluene Primary Reference Fuel (TPRF) on spray characteristics, DISI engine combustion, and particle number (PN) emissions are investigated for conditions with and without flash boiling of the injected fuel. Spray characteristics are investigated using a constant volume chamber. Then, the combustion, flame propagation, and PN emissions are examined using an optical DISI engine. The fuel temperature is set to 298 K and 453 K for liquid injection and flash boiling injection, respectively. The tested blending ratio is 30 vol% butanol isomers and 70 vol% TPRF. The results of the spray test reveal that liquid fuel plumes are distinctly observed, and butanol blends show a slightly wider spray angle with lower penetration length compared to TPRF. However, under flash boiling injection, the sprays collapse towards the injector axis, forming a more extended single central vapor jet due to the plumes' interaction. Meanwhile, butanol blends yield a narrow spray angle with more extended penetration compared to TPRF. The flame visualization test shows that the flash boiling injection reduced yellow flames compared to liquid fuel injection, reflecting the improvements in mixture formation. Thus, improvements were noted in the heat release and PN emissions. Butanol addition reduced the PN emissions by 43% under regular liquid injection. Flash boiling injection provided an additional 25% reduction in PN emissions.

Institutional linkages and information flow between agricultural organizations play a critical role in addressing sustainability issues and promoting agrarian innovation. The aim of this study was to evaluate institutional relations and information between the various actors within the agricultural knowledge and information system (AKIS). The study focused on eight actors within the AKIS in Dakahlia governorate of Egypt, namely policy, extension, research, agricultural cooperatives, higher education, secondary education, credit, and the private sector. Thus, the survey sample included 11 representatives of each actor with 88 respondents. Data were collected by a standardized questionnaire distributed online. The graph theoretical technique was used for the quantitative assessment of information flow and institutional linkages established among actors. The findings indicated that agricultural extension ranked first about their real cause and effect on the rest of the system, having a value of 7.95. Two critical information pathways within the AKIS sustained innovation outcomes: (1) higher education–extension–agricultural cooperatives, (2) research–extension–agricultural cooperatives. The results also revealed that agricultural cooperatives ranked second after the extension component on the extent of supplying information to other members in the AKIS, with a value of 4.8. In contrast, the highest component received information from other components (7.6). By analyzing institutional linkages and information flow, this article gives insights to policymakers on the mechanisms that still need to be strengthened and the information gaps between actors to address the challenges of sustainable rural development.