• Energy Research

Wind energy is an abundant renewable energy resource that has been extensively used worldwide in recent years. The present work proposes a new Multi-Objective Optimization (MOO) based genetic algorithm (GA) model for a wind energy system. The proposed algorithm consists of non-dominated sorting which focuses to maximize the power extraction of the wind turbine, minimize the cost of generating energy, and the lifetime of the battery. Additionally, the performance characteristics of the wind turbine and battery energy storage system (BESS) are analyzed specifically torque, current, voltage, state of charge (SOC), and internal resistance. The complete analysis is carried out in the MATLAB/Simulink platform. The simulated results are compared with existing optimization techniques such as single-objective, multi-objective, and non-dominating sorting GA II (Genetic Algorithm-II). From the observed results, the non-dominated sorting genetic algorithm (NSGA III) optimization algorithm offers superior performance notably higher turbine power output with higher torque rate, lower speed variation, reduced energy cost, and lesser degradation rate of the battery. This result attested to the fact that the proposed optimization tool can extract a higher rate of power from a self-excited induction generator (SEIG) when compared with a conventional optimization tool.

With the growing consumer demand in the electronics field, sustainable and effective cooling approaches are imperative to maximize operational efficiency. Heat pipes shave a major consideration in the field of heat transfer in a modern era of miniaturization of equipment. In current trends, the proportion of custom-designed electronic chips is increasing, given the space constraints of the application. Additionally, the use of nanofluids in heat pipes has drawn considerable attention because of their exceptional performance in heat transfer. This research is proposed primarily to investigate the effect of nanofluids on the performance of the partially flattened heat pipe. Here, the evaporator portion forms flat shape which is mostly suitable for fixing easily in electronic circuits. The remaining portions, such as the adiabatic and condenser, are left as circular. This work also covers the development of flattened heat pipes and analyzes their performance. Pure water, Titanium Oxide (TiO2), and Aluminum Oxide (Al2O3)-water-based nanofluids have been used in this research as working fluids. The heat transfer analysis on the customized partially flattened heat pipe was performed, and the results have been compared with fully flattened and circular heat pipes. The heat transfer parameters, such as the heat transfer coefficient and thermal resistance, have been determined from the heat input, evaporator temperature, and condenser temperature for various inclination angles including 0°, 45°, and 90° with the heat input varied between 50–300 W. The results have shown that the flattened heat pipe performed better with Al2O3 nanofluid at an inclination angle of 45° at all of the heat inputs and provided better thermal resistance compared with the other combinations. At 45°, the resistance of the heat pipe was reduced by 2% and 8% with Al2O3 nanofluid compared with water and TiO2 nanofluid. Furthermore, the heat transfer coefficient was found higher by 4 W/m2-K and 4.6 W/m2-K with Al2O3 and gives better results in terms of resistance and heat transfer coefficient.

L'utilisation de nanofluides (NF) est prometteuse pour améliorer l'efficacité thermique des capteurs solaires thermiques. Parmi les différentes solutions NF, les NF de boue rouge (RM) ont attiré l'attention en raison de leur absorption efficace de l'énergie solaire thermique. La RM comprend des oxydes de métaux précieux, ce qui en fait un milieu compétent pour l'absorption directe de la chaleur solaire. Cette étude visait à formuler des NF RM à base d'eau avec des concentrations allant de 0,1 à 0,75 % en volume. Dans la plage de température de 303 à 333 K, nous avons évalué la chaleur spécifique (SH), la viscosité (VST) et la conductivité thermique (TC) des NF. Pour maintenir la stabilité, nous avons utilisé un tensioactif à base de polyvinylpyrrolidone (PVP). Les résultats ont indiqué que la SH des NF RM est inférieure à celle de l'eau. De plus, à mesure que les concentrations de RM NF augmentaient, il y avait une amélioration significative de la CT. L'augmentation de la CT la plus élevée de 36,9 % est observée à 333 K pour une concentration de 0,75 % en volume par rapport à l'eau. Sur la base des données recueillies, des équations uniques ont été développées pour estimer les propriétés des NF RM dans la plage étudiée. Nos résultats suggèrent que les NF RM ont le potentiel de remplacer efficacement l'eau dans les applications de l'énergie solaire. En outre, nous avons utilisé des techniques innovantes d'apprentissage automatique de type ensemble (ML), à savoir Adaptive Boosting (AdaBoost) et Random Forest (RF), pour résoudre le problème. Nous avons également utilisé ces nouvelles méthodes de ML pour construire des métamodèles pour prédire les propriétés considérées, offrant des modèles précis et efficaces pour analyser le comportement NF. L'incorporation de MP dans les applications solaires thermiques pourrait contribuer à résoudre les problèmes d'élimination associés à ces déchets, contribuant ainsi à leur gestion à long terme. La utilización de nanofluidos (NF) es prometedora para mejorar la eficiencia térmica de los colectores solares térmicos. Entre las diversas soluciones de NF, los NF de lodo rojo (RM) han ganado atención debido a su absorción efectiva de energía solar térmica. RM comprende óxidos de metales preciosos, lo que lo convierte en un medio competente para la absorción directa de calor solar. Este estudio tuvo como objetivo formular NF de RM a base de agua con concentraciones que oscilan entre 0.1 y 0.75% en volumen. Dentro del rango de temperatura de 303-333 K, evaluamos el calor específico (SH), la viscosidad (VST) y la conductividad térmica (TC) de los NF. Para mantener la estabilidad, empleamos tensioactivo de polivinilpirrolidona (PVP). Los resultados indicaron que el SH de los NF de MR es menor que el del agua. Además, a medida que aumentaron las concentraciones de RM NF, hubo una mejora significativa en TC. La mayor mejora de TC del 36,9 % se observa a 333 K para una concentración del 0,75% en volumenen comparación con el agua. Con base en los datos recopilados, se desarrollaron ecuaciones únicas para estimar las propiedades de los NF de RM dentro del rango estudiado. Nuestros hallazgos sugieren que los RM NF tienen el potencial de reemplazar eficazmente el agua en aplicaciones de energía solar. Además, empleamos técnicas innovadoras de aprendizaje automático (ML) de tipo conjunto, a saber, el impulso adaptativo (AdaBoost) y el bosque aleatorio (RF), para abordar el problema. También utilizamos estos nuevos métodos de ML para construir metamodelos para predecir las propiedades consideradas, ofreciendo modelos precisos y eficientes para analizar el comportamiento de NF. La incorporación de RM en aplicaciones solares térmicas podría contribuir a resolver los desafíos de eliminación asociados con este material de desecho, ayudando así en su gestión a largo plazo. The utilization of nanofluids (NFs) holds promise for enhancing the thermal efficiency of solar thermal collectors. Among the various NF solutions, red mud (RM) NFs have gained attention due to their effective absorption of solar thermal energy. RM comprises precious metal oxides, making it a proficient medium for direct solar heat absorption. This study aimed to formulate water-based RM NFs with concentrations ranging from 0.1 to 0.75 vol%. Within the temperature range of 303–333 K, we assessed the specific heat (SH), viscosity (VST), and thermal conductivity (TC) of the NFs. To maintain stability, we employed polyvinylpyrrolidone (PVP) surfactant. The results indicated that the SH of RM NFs is lower than that of water. Additionally, as RM NF concentrations increased, there was a significant improvement in TC. The highest TC enhancement of 36.9 % is observed at 333 K for a concentration of 0.75 vol% compared to water. Based on the gathered data, unique equations were developed to estimate the properties of RM NFs within the studied range. Our findings suggest that RM NFs have the potential to effectively replace water in solar energy applications. Furthermore, we employed innovative ensemble-type machine learning (ML) techniques, namely Adaptive Boosting (AdaBoost) and random forest (RF), to address the problem. We also utilized these novel ML methods to construct metamodels for predicting the considered properties, offering accurate and efficient models for analyzing NF behavior. The incorporation of RM in solar thermal applications could contribute to resolving disposal challenges associated with this waste material, thereby aiding in its long-term management. إن استخدام السوائل النانوية (NFs) يبشر بالخير لتعزيز الكفاءة الحرارية للمجمعات الحرارية الشمسية. من بين حلول NF المختلفة، اكتسبت NFs الطين الأحمر (RM) الاهتمام بسبب امتصاصها الفعال للطاقة الحرارية الشمسية. يتكون RM من أكاسيد المعادن الثمينة، مما يجعله وسيطًا بارعًا لامتصاص الحرارة الشمسية المباشرة. تهدف هذه الدراسة إلى صياغة NFs المستندة إلى الماء بتركيزات تتراوح من 0.1 إلى 0.75 ٪. ضمن نطاق درجة حرارة 303–333 كلفن، قمنا بتقييم الحرارة النوعية (SH) واللزوجة (VST) والموصلية الحرارية (TC) لـ NFs. للحفاظ على الاستقرار، استخدمنا مادة البولي فينيل بيروليدون (PVP) الخافضة للتوتر السطحي. أشارت النتائج إلى أن SH لـ RM NFs أقل من الماء. بالإضافة إلى ذلك، مع زيادة تركيزات RM NF، كان هناك تحسن كبير في TC. لوحظ أعلى تعزيز TC بنسبة 36.9 ٪ عند 333 كلفن لتركيز 0.75 ٪ من الحجم مقارنة بالماء. استنادًا إلى البيانات التي تم جمعها، تم تطوير معادلات فريدة لتقدير خصائص RM NFs ضمن النطاق المدروس. تشير النتائج التي توصلنا إليها إلى أن RM NFs لديها القدرة على استبدال المياه بشكل فعال في تطبيقات الطاقة الشمسية. علاوة على ذلك، استخدمنا تقنيات مبتكرة للتعلم الآلي من نوع المجموعة (ML)، وهي التعزيز التكيفي (AdaBoost) والغابات العشوائية (RF)، لمعالجة المشكلة. كما استخدمنا طرق غسل الأموال الجديدة هذه لبناء نماذج ميتاموديل للتنبؤ بالخصائص المدروسة، وتقديم نماذج دقيقة وفعالة لتحليل سلوك NF. يمكن أن يساهم دمج RM في التطبيقات الحرارية الشمسية في حل تحديات التخلص المرتبطة بمواد النفايات هذه، وبالتالي المساعدة في إدارتها على المدى الطويل.

India has ambitious goals to increase renewable energy penetration, and significant progress has been made since 2017. However, the Indian energy mix is highly dominated by fossil fuels. To set India on the pathway of the energy transition, a comprehensive analysis of the complex factors influencing the Indian energy sector is required. This study is put forward to delineate the current energy transition scenario in India and to direct the energy sector towards a prospective scenario for accomplishing a smooth energy transition. A hybrid quantitative-qualitative SWOT-integrated MCDA methodology is employed to accomplish the objective of this study. An extensive literature review is performed to understand and sort the various factors under each SWOT category. Fuzzy AHP methodology is utilized to convert the qualitative significance of each SWOT factor into quantitative scores, through which the crucial influencing factor in the current energy transition scenario is obtained. The top three highest-influence factors include utilizing the cost-competitiveness of solar and wind energy technologies over fossil fuels, the inadequacy of manpower having specialized skillsets, and connecting households to electricity and electrifying the transportation sector. The recommendation strategies are framed and presented for prospective energy transition scenarios. These strategies are assessed against the SWOT factors by using the PROMETHEE II methodology. The assessment results highlight that developing robust regulatory and policy frameworks, increasing the contribution of local energy resources, and promoting the distributed generation and grid infrastructure development are the highest-scoring strategies that have a synergic effect on multiple dimensions of energy transition, including political, financial, and techno-economic aspects. The proposed study will be conducive to framing effective policy in the upcoming years to assist the energy transition in India.

Les réseaux électriques existants (PG) et les contrôleurs de gestion de l'énergie à domicile n'offrent pas à ses utilisateurs le choix de maintenir le confort et de fournir une solution supportable en termes de faible coût et de réduction des émissions de carbone. Ce travail est basé sur la planification et la gestion de la consommation d'énergie dans le cadre des services publics d'électricité et des sources d'énergie renouvelables, c'est-à-dire l'énergie solaire (SE), la chaleur et l'électricité contrôlables (CHP) et l'énergie éolienne (WE) ensemble. L'intégration efficace des sources d'énergie renouvelables (SER) et du système de stockage sur batterie (BSS) a été suggérée pour résoudre le problème de la gestion de l'énergie, réduire le coût de la facture, le rapport crête/moyenne (par) et les émissions de carbone. La réduction de la facture d'électricité de l'utilisateur a été obtenue grâce à la méthode proposée de planification de la consommation d'énergie et à l'intégration de sources d'énergie renouvelables à faible coût. LA MINIMISATION DU par a été obtenue en déplaçant la demande en réponse au prix en temps réel des heures de pointe vers les heures de faible pointe. Dans ce contexte, un contrôleur de planification de charge et de gestion du système de stockage d'énergie (LSEMC) est proposé, qui est basé sur des algorithmes heuristiques, à savoir l'algorithme génétique (GA), l'optimisation éolienne (WDO), l'optimisation de l'essaim de particules binaires (BPSO), l'optimisation de la recherche de nourriture bactérienne (BFO) et notre hybride suggéré de l'algorithme GA, WDO et PSO (HGPDO). La performance des algorithmes heuristiques et du schéma proposé est évaluée numériquement. Les résultats démontrent que notre algorithme proposé et le LSEMC réduisent la facture d'électricité, PAR et CO 2 dans le cas 1, de 58,69%, 52,78% et 72,40%, dans le cas 2, de 47,55%, 45,02% et 92,90% et dans le cas 3, de 33,6%, 54,35% et 91,64%, respectivement par rapport aux imprévus. De plus, le confort d'utilisation de notre algorithme HGPDO proposé en termes de délai, thermique, qualité de l'air et visuel s'améliore respectivement de 35,55%, 16,66%, 91,64% et 45%. Las redes eléctricas (PG) existentes y los controladores de gestión de energía en el hogar no ofrecen a sus usuarios la opción de mantener la comodidad y proporcionar una solución soportable en términos de bajo costo y reducción de emisiones de carbono. Este trabajo se basa en la programación y gestión del uso de energía bajo la utilidad eléctrica y las fuentes de energía renovables, es decir, energía solar (SE), calor y energía controlables (CHP) y energía eólica (WE) juntos. Se ha sugerido una integración eficiente de las fuentes de energía renovables (RES) y el sistema de almacenamiento de baterías (BSS) para resolver el problema de la gestión de la energía, reducir el costo de la factura, la relación pico a promedio (par) y las emisiones de carbono. La reducción de la factura de electricidad del usuario se ha logrado mediante el método de programación del uso de energía propuesto y la integración de RES de bajo costo. LA minimización de PAR se ha logrado mediante el cambio de la demanda en respuesta al precio en tiempo real de horas pico altas a horas pico bajas. En este contexto, se propone la programación de carga y el controlador de gestión del sistema de almacenamiento de energía (LSEMC) que se basa en algoritmos heurísticos, es decir, algoritmo genético (GA), optimización impulsada por el viento (WDO), optimización de enjambre de partículas binarias (BPSO), optimización de forrajeo bacteriano (BFO) y nuestro algoritmo híbrido sugerido de GA, WDO y PSO (HGPDO). Se evalúa numéricamente el rendimiento de los algoritmos heurísticos y esquema propuesto. Los resultados demuestran que nuestro algoritmo propuesto y la LSEMC reducen la factura de electricidad, PAR y CO 2 en el Caso 1, en un 58.69%, 52.78% y 72.40%, en el Caso 2, en un 47.55%, 45.02% y 92.90% y en el Caso 3, en un 33.6%, 54.35% y 91.64%, respectivamente, en comparación con lo no programado. Además, la comodidad del usuario por nuestro algoritmo HGPDO propuesto en términos de retraso, térmica, calidad del aire y visual mejora en un 35,55%, 16,66%, 91,64% y 45%, respectivamente. Existing power grids (PGs) and in-home energy management controllers do not offer its users the choice to maintain comfort and provide a bearable solution in terms of low cost and reduced carbon emission. This work is based on energy usage scheduling and management under electric utility and renewable energy sources i.e., solar energy (SE), controllable heat and power (CHP) and wind energy (WE) together. Efficient integration of renewable energy sources (RES) and battery storage system (BSS) have been suggested to solve the energy management problem, reduce the bill cost, peak-to-average ratio (PAR) and carbon emission. User's electricity bill reduction have been achieved by proposed power usage scheduling method and integrating low cost RESs. PAR minimization have been achieved through shifting the demand in response to real time price from high-peak hours to low-peak hours. In this context, load scheduling and energy storage system management controller (LSEMC) is proposed which is based on heuristic algorithms i.e., genetic algorithm (GA), wind driven optimization (WDO), binary particle swarm optimization (BPSO), bacterial foraging optimization (BFO) and our suggested hybrid of GA, WDO and PSO (HGPDO) algorithm. The performance of the heuristic algorithms and proposed scheme is evaluated numerically. Results demonstrate that our proposed algorithm and the LSEMC reduces the electricity bill, PAR and CO 2 in Case 1, by 58.69%, 52.78% and 72.40%, in Case 2, by 47.55%, 45.02% and 92.90% and in Case 3, by 33.6%, 54.35% and 91.64%, respectively as compared with unscheduled. Moreover, the user comfort by our proposed HGPDO algorithm in terms of delay, thermal, air quality and visual improves by 35.55%, 16.66%, 91.64% and 45%, respectively. لا توفر شبكات الطاقة الحالية (PGs) ووحدات التحكم في إدارة الطاقة داخل المنزل لمستخدميها خيار الحفاظ على الراحة وتوفير حل محتمل من حيث التكلفة المنخفضة وانخفاض انبعاثات الكربون. يعتمد هذا العمل على جدولة وإدارة استخدام الطاقة في إطار المرافق الكهربائية ومصادر الطاقة المتجددة، أي الطاقة الشمسية (SE) والحرارة والطاقة التي يمكن التحكم فيها (CHP) وطاقة الرياح (WE) معًا. تم اقتراح التكامل الفعال لمصادر الطاقة المتجددة (RES) ونظام تخزين البطارية (BSS) لحل مشكلة إدارة الطاقة، وتقليل تكلفة الفاتورة، ونسبة الذروة إلى المتوسط (PAR) وانبعاثات الكربون. تم تحقيق تخفيض فاتورة الكهرباء للمستخدم من خلال طريقة جدولة استخدام الطاقة المقترحة ودمج RESs منخفضة التكلفة. تم تحقيق التقليل من القيمة الاسمية من خلال تحويل الطلب استجابة للسعر في الوقت الفعلي من ساعات الذروة العالية إلى ساعات الذروة المنخفضة. في هذا السياق، يُقترح جدولة الحمل ووحدة التحكم في إدارة نظام تخزين الطاقة (LSEMC) التي تعتمد على الخوارزميات الاستكشافية، أي الخوارزمية الجينية (GA)، والتحسين المدفوع بالرياح (WDO)، والتحسين الثنائي لسرب الجسيمات (BPSO)، والتحسين البكتيري للبحث عن الطعام (BFO)، وخوارزمية الهجين المقترحة من خوارزمية GA و WDO و PSO (HGPDO). يتم تقييم أداء الخوارزميات الإرشادية والمخطط المقترح رقميًا. تظهر النتائج أن خوارزميتنا المقترحة و LSEMC تقلل من فاتورة الكهرباء، PAR و CO 2 في الحالة 1، بنسبة 58.69 ٪ و 52.78 ٪ و 72.40 ٪، في الحالة 2، بنسبة 47.55 ٪ و 45.02 ٪ و 92.90 ٪ وفي الحالة 3، بنسبة 33.6 ٪ و 54.35 ٪ و 91.64 ٪، على التوالي مقارنة بالحالة غير المجدولة. علاوة على ذلك، تتحسن راحة المستخدم من خلال خوارزمية HGPDO المقترحة من حيث التأخير والحرارة وجودة الهواء والبصر بنسبة 35.55 ٪ و 16.66 ٪ و 91.64 ٪ و 45 ٪ على التوالي.

Cyber-Physical System (CPS) is a new kind of digital technology that increases its attention across academia, government, and industry sectors and covers a wide range of applications like agriculture, energy, medical, transportation, etc. The traditional power systems with physical equipment as a core element are more integrated with information and communication technology, which evolves into the Cyber-Physical Power System (CPPS). The CPPS consists of a physical system tightly integrated with cyber systems (control, computing, and communication functions) and allows the two-way flows of electricity and information for enabling smart grid technologies. Even though the digital technologies monitoring and controlling the electric power grid more efficiently and reliably, the power grid is vulnerable to cybersecurity risk and involves the complex interdependency between cyber and physical systems. Analyzing and resolving the problems in CPPS needs the modelling methods and systematic investigation of a complex interaction between cyber and physical systems. The conventional way of modelling, simulation, and analysis involves the separation of physical domain and cyber domain, which is not suitable for the modern CPPS. Therefore, an integrated framework needed to analyze the practical scenario of the unification of physical and cyber systems. A comprehensive review of different modelling, simulation, and analysis methods and different types of cyber-attacks, cybersecurity measures for modern CPPS is explored in this paper. A review of different types of cyber-attack detection and mitigation control schemes for the practical power system is presented in this paper. The status of the research in CPPS around the world and a new path for recommendations and research directions for the researchers working in the CPPS are finally presented.

A strong energy mix of Renewable Energy Sources (RESs) is needed for sustainable development in the electricity sector. India stands as one of the fastest developing countries in terms of RES production. In this framework, the main objective of this review is to critically scrutinize the Maharashtra state energy landscape to discover the gaps, barriers, and challenges therein and to provide recommendations and suggestions for attaining the RES target by 2022. This work begins with a discussion about the RES trends in various developing countries. Subsequently, it scrutinizes the installed capacity of India, reporting that Maharashtra state holds a considerable stake in the Indian energy mix. A further examination of the state energy mix is carried out by comparing the current and future targets of the state action plan. It is found that the installed capacity of RESs accounts for about 22% of the state energy mix. Moreover, the current installed capacity trend is markedly different from the goals set out in the action plan of the state. Notably, the installed capacity of solar energy is four times less than the target for 2020. Importantly, meeting the targeted RES capacity for 2022 presents a great challenge to the state. Considering this, an analysis of the state’s strengths, barriers, and challenges is presented. Moreover, strong suggestions and recommendations are provided to clear the track to reach the desired destination. This can be useful for the government agencies, research community, private investors, policymakers, and stakeholders involved in building a sustainable energy system for the future.