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Abstract The renewable energy is expanding in the sub-systems of distribution electrical grids, due to having low energy costs and high reliability. In this study, off-grid design of the hybrid energy system based-renewable resources is proposed for a house in Hamadan city in Iran. The resources are designed based on economic and climate data such as battery, solar cells, wind turbines, and electrolyser/fuel cell. The design of mentioned resources is done with attention to twofold optimization modelling including operation cost (OC) and net present cost (NPC). The modelling of resources is implemented in HOMER software based on optimal sizing and installation costs. In the numerical simulation, the three optimal designs are presented to meet electrical demand with minimum costs and high reliability.

Abstract In this paper, a multi objective optimization approach is studied for optimal energy scheduling of the smart autonomous electrical grid with participation of active consumers (ACs) and hydrogen storage system (HSS). The objective functions consist of: 1) minimizing the costs and 2) maximizing reliability. The ACs participation are modelled through demand reduction approach based on offer price to peak demand management. The proposed optimization is solved by epsilon-constraint method and LINMAP decision making strategy. The 21-node test system is employed to analyse the efficiency of the proposed approach at two case studies. The obtained results shown the high effectiveness of smart autonomous electrical grid with participation of ACs and HSS to supply the demand.

The Global Plant Health Assessment (GPHA) is a collective, volunteer-based effort to assemble expert opinions on plant health and disease impacts on ecosystem services based on published scientific evidence. The GPHA considers a range of forest, agricultural, and urban systems worldwide. These are referred to as (Ecoregion × Plant System), i.e., selected case examples involving keystone plants in given parts of the world. The GPHA focuses on infectious plant diseases and plant pathogens, but encompasses the abiotic (e.g., temperature, drought, and floods) and other biotic (e.g., animal pests and humans) factors associated with plant health. Among the 33 (Ecoregion × Plant System) considered, 18 are assessed as in fair or poor health, and 20 as in declining health. Much of the observed state of plant health and its trends are driven by a combination of forces, including climate change, species invasions, and human management. Healthy plants ensure (i) provisioning (food, fiber, and material), (ii) regulation (climate, atmosphere, water, and soils), and (iii) cultural (recreation, inspiration, and spiritual) ecosystem services. All these roles that plants play are threatened by plant diseases. Nearly none of these three ecosystem services are assessed as improving. Results indicate that the poor state of plant health in sub-Saharan Africa gravely contributes to food insecurity and environmental degradation. Results further call for the need to improve crop health to ensure food security in the most populated parts of the world, such as in South Asia, where the poorest of the poor, the landless farmers, are at the greatest risk. The overview of results generated from this work identifies directions for future research to be championed by a new generation of scientists and revived public extension services. Breakthroughs from science are needed to (i) gather more data on plant health and its consequences, (ii) identify collective actions to manage plant systems, (iii) exploit the phytobiome diversity in breeding programs, (iv) breed for plant genotypes with resilience to biotic and abiotic stresses, and (v) design and implement plant systems involving the diversity required to ensure their adaptation to current and growing challenges, including climate change and pathogen invasions.

Récemment, une grande attention a été accordée à l'application des énergies renouvelables dans les questions environnementales. Pendant ce temps, l'industrie des piles à combustible, qui est considérée comme une industrie respectueuse de l'environnement, est l'une des composantes importantes de ce projet. Ce sont en fait des dispositifs pour la conversion directe de l'énergie chimique en énergie électrique par une réaction électrochimique sans avoir besoin de pièces mécaniques. Dans cette étude, on tente de modéliser l'un de leurs types importants, appelé pile à combustible à membrane échangeuse de protons, afin qu'il puisse être utilisé pour prédire le comportement de la pile à combustible et examiner divers paramètres affectant les performances de la pile. L'idée principale est d'estimer les paramètres optimaux pour les piles à combustible à membrane échangeuse de protons en minimisant la valeur d'erreur quadratique totale entre la tension de sortie empirique et la tension de sortie approchée. Pour donner de meilleurs résultats en termes de précision et de fiabilité, une nouvelle conception d'une métaheuristique appelée l'algorithme équilibré Water Strider est utilisée. Les résultats de la méthode suggérée sont finalement validés par comparaison avec plusieurs derniers optimiseurs appliqués sur un cas de test pratique. Après avoir exécuté tous les optimiseurs 30 fois indépendamment, la méthode proposée avec une erreur absolue minimale est égale à 3,4831e−4 montre les meilleurs résultats par rapport aux autres. Recientemente, se prestó mucha atención a la aplicación de energías renovables en temas ambientales. Mientras tanto, la industria de pilas de combustible, que se considera una industria respetuosa con el medio ambiente, es uno de los componentes importantes de este proyecto. De hecho, son dispositivos para la conversión directa de energía química en energía eléctrica mediante una reacción electroquímica sin necesidad de piezas mecánicas. En este estudio, se intenta modelar uno de sus tipos importantes, llamado celdas de combustible de membrana de intercambio de protones, para que pueda usarse en la predicción del comportamiento de la celda de combustible y examinar varios parámetros que afectan el rendimiento de la celda. La idea principal es la estimación óptima de los parámetros para las celdas de combustible de membrana de intercambio de protones minimizando el valor total de error al cuadrado entre el voltaje de salida empírico y el voltaje de salida aproximado. Para dar mejores resultados en términos de precisión y confiabilidad, se utiliza un nuevo diseño de una metaheurística llamada Algoritmo equilibrado Water Strider. Los resultados del método sugerido se validan finalmente mediante la comparación con varios de los últimos optimizadores aplicados en un caso de prueba práctico. Después de ejecutar todos los optimizadores 30 veces de forma independiente, el método propuesto con un error absoluto mínimo igual a3.4831e −4 muestra los mejores resultados hacia los demás. Recently, much attention was paid to the application of renewable energy in environmental issues. Meanwhile, the fuel cell industry, which is considered an environmentally friendly industry, is one of the important components of this project. They are in fact devices for the direct conversion of chemical energy into electrical energy by an electrochemical reaction without the need for any mechanical parts. In this study, it is attempted to model one of their important types, called proton exchange membrane fuel cells, so that it can be used in predicting the behavior of the fuel cell and examining various parameters affecting the performance of the cell. The main idea is to optimal parameters estimation for the proton exchange membrane fuel cells by minimizing the total Squared Error value between the empirical output voltage and the approximated output voltage. For giving better results in terms of accuracy and reliability, a new design of a metaheuristic called the balanced Water Strider Algorithm is utilized. The results of the suggested method are finally validated by comparison with several latest optimizers applied on a practical test case. After running all of the optimizers 30 times independently, the proposed method with minimum absolute error equals 3.4831e−4 shows the best results toward the others. في الآونة الأخيرة، تم إيلاء الكثير من الاهتمام لتطبيق الطاقة المتجددة في القضايا البيئية. وفي الوقت نفسه، تعد صناعة خلايا الوقود، التي تعتبر صناعة صديقة للبيئة، أحد المكونات المهمة لهذا المشروع. وهي في الواقع أجهزة للتحويل المباشر للطاقة الكيميائية إلى طاقة كهربائية عن طريق تفاعل كهروكيميائي دون الحاجة إلى أي أجزاء ميكانيكية. في هذه الدراسة، يتم محاولة نمذجة أحد أنواعها المهمة، يسمى خلايا وقود غشاء التبادل البروتوني، بحيث يمكن استخدامه في التنبؤ بسلوك خلية الوقود وفحص المعلمات المختلفة التي تؤثر على أداء الخلية. الفكرة الرئيسية هي تقدير المعلمات الأمثل لخلايا وقود غشاء التبادل البروتوني عن طريق تقليل إجمالي قيمة الخطأ التربيعي بين جهد الخرج التجريبي وجهد الخرج التقريبي. لإعطاء نتائج أفضل من حيث الدقة والموثوقية، يتم استخدام تصميم جديد لميتاهيوريستيك يسمى خوارزمية سترايدر المياه المتوازنة. يتم التحقق من صحة نتائج الطريقة المقترحة أخيرًا بالمقارنة مع العديد من أحدث المحسنات المطبقة على حالة اختبار عملية. بعد تشغيل جميع المحسنات 30 مرة بشكل مستقل، فإن الطريقة المقترحة مع الحد الأدنى من الخطأ المطلق تساوي 3.4831e -4 تظهر أفضل النتائج تجاه الآخرين.

Abstract This study focused on energy saving in energy hub system using smart grid technologies and management of the energy demand. The two-layer energy management is proposed for implementing energy saving. In first layer, energy demand such as electrical, thermal and natural gas are optimized subject to optimal level of the demand at day-ahead. Then, optimized energy demand is applied in second layer to reduction energy generation costs. The optimization of the proposed approach is done by shuffled frog leaping algorithm (SFLA), and results at several case studies to confirmation of the proposed approach are investigated.