• Energy Research

L'objectif principal de cet article est de concevoir et d'évaluer l'étude des caractéristiques du nouveau générateur synchrone à aimant permanent pseudo-polaire à double stator (NDSPPFP-PMSG) pour l'application de l'énergie éolienne.Le générateur proposé a un double stator et deux ensembles de cinq enroulements de phase qui améliorent sa densité de puissance et sa capacité de tolérance aux pannes.La nouveauté de ce générateur est basée sur le fait que huit pôles magnétiques sont formés en utilisant seulement quatre pôles d'aimants réels sur les deux surfaces du rotor.Pour la conception et les performances électromagnétiques optimales du générateur proposé, un générateur dynamique Le modèle de circuit magnétique (DMCM) est rapporté.Pour valider les résultats obtenus à partir du DMCM, la méthode des éléments finis (FEM) a été choisie en raison de sa grande précision.Pour montrer la supériorité des performances, le générateur proposé est comparé à deux générateurs conventionnels à savoir, DSEPFP (Dual Stator Embedded-Pole Five Phase) et SSSRFP (Single Stator Single Rotor Five Phase) PMSG.Pour comparer leurs performances, les résultats du FEM sont pris en compte.La performance électromagnétique à savoir, la force électromotrice générée (EMF), pourcentage(%) Distorsion harmonique totale (THD) de la EMF générée, EMF générée vs la vitesse, la tension aux bornes en fonction du courant de charge, le couple électromagnétique développé sur le rotor en fonction du temps, le % de contenu d'ondulation dans le couple et le % d'efficacité en fonction du courant de charge sont étudiés pour les trois générateurs. De ces études, il ressort que la densité de puissance (rapport puissance/poids) du générateur proposé est maximale. El objetivo principal de este documento es diseñar y evaluar la investigación de características del nuevo generador síncrono de imanes permanentes de seudopolos de doble estator (NDSPPFP-PMSG) para la aplicación de energía eólica. El generador propuesto tiene un estator dual y dos conjuntos de devanados de cinco fases que mejoran su densidad de potencia y su capacidad de tolerancia a fallos. La novedad de este generador se basa en el hecho de que, ocho polos magnéticos se forman utilizando solo cuatro polos de imanes reales en ambas superficies del rotor. Para el diseño y el rendimiento electromagnético óptimo del generador propuesto, un Se informa el Modelo de Circuito Magnético (DMCM). Para validar los resultados obtenidos de DMCM, se ha optado por el Método de Elementos Finitos (FEM) debido a su alta precisión. Para mostrar la superioridad del rendimiento, se compara el generador propuesto con dos generadores convencionales, a saber, Dual Stator Embedded-Pole Five Phase (DSEPFP) y Single Stator Single Rotor Five Phase (SSSRFP) PMSG. Para comparar sus rendimientos, se consideran los resultados de FEM. El rendimiento electromagnético, a saber, la Fuerza Electromotriz generada (EMF), porcentaje(%) Distorsión Armónica Total (ThD) de EMF generada, EMF generada vs se investigan la velocidad, el voltaje terminal frente a la corriente de carga, el par electromagnético desarrollado en el rotor frente al tiempo, el % de contenido de ondulación en el par y el % de eficiencia frente a la corriente de carga para los tres generadores. A partir de estas investigaciones, se encuentra que la densidad de potencia (relación potencia-peso) del generador propuesto es máxima. The main focus of this paper is to design and assess the characteristics investigation of Novel Dual Stator Pseudo-Pole Five Phase Permanent Magnet Synchronous Generator (NDSPPFP-PMSG) for wind power application.The proposed generator has a dual stator and two sets of five phase windings which enhance its power density and fault tolerant capability.The novelty of this generator is based on the fact that, eight magnetic poles are formed using only four poles of actual magnets on both the surfaces of the rotor.For the designing and optimal electromagnetic performance of the proposed generator, a Dynamic Magnetic Circuit Model (DMCM) is reported.To validate the results obtained from DMCM, Finite Element Method (FEM) has been opted owing to its high accuracy.For showing the performance superiority, the proposed generator is compared with two conventional generators namely, Dual Stator Embedded-Pole Five Phase (DSEPFP) and Single Stator Single Rotor Five Phase (SSSRFP) PMSG.To compare their performances, FEM results are considered.The electromagnetic performance namely, generated Electromotive Force(EMF), percentage(%) Total Harmonic Distortion(THD) of generated EMF, generated EMF vs speed, terminal voltage vs load current, electromagnetic torque developed on rotor vs time, %ripple content in the torque, and %efficiency vs load current are investigated for all the three generators.From these investigations, it is found that the power density (power to weight ratio) of the proposed generator is maximum. ينصب التركيز الرئيسي لهذه الورقة على تصميم وتقييم التحقيق في خصائص المولد المتزامن للمغناطيس الدائم ثنائي القطب الزائف (NDSPPFP - PMSG) لتطبيق طاقة الرياح. يحتوي المولد المقترح على عضو ساكن مزدوج ومجموعتين من اللفات خماسية الطور التي تعزز كثافة طاقته وقدرته على تحمل الأخطاء. تعتمد حداثة هذا المولد على حقيقة أنه يتم تشكيل ثمانية أقطاب مغناطيسية باستخدام أربعة أقطاب فقط من المغناطيس الفعلي على كل من أسطح الدوار. للتصميم والأداء الكهرومغناطيسي الأمثل للمولد المقترح، تم الإبلاغ عن نموذج الدائرة المغناطيسية (DMCM). للتحقق من صحة النتائج التي تم الحصول عليها من نموذج الدائرة المغناطيسية (DMCM)، تم اختيار طريقة العناصر المحدودة (FEM) نظرًا لدقتها العالية. لإظهار تفوق الأداء، تتم مقارنة المولد المقترح مع اثنين من المولدات التقليدية وهما، المرحلة الخامسة للجزء الثابت المضمن (DSEPFP) و PMSG للجزء الثابت المفرد. لمقارنة أدائها، يتم النظر في نتائج FEM. الأداء الكهرومغناطيسي أي القوة المحركة الكهرومغناطيسية المتولدة (EMF)، النسبة المئوية (٪) التشوه التوافقي الكلي (THD) من المجال الكهرومغناطيسي المتولد، المجال الكهرومغناطيسي المتولد مقابل يتم فحص السرعة والجهد الطرفي مقابل تيار الحمل وعزم الدوران الكهرومغناطيسي المطور على الدوار مقابل الوقت ومحتوى التموج في عزم الدوران و ٪الكفاءة مقابل تيار الحمل لجميع المولدات الثلاثة. من هذه التحقيقات، وجد أن كثافة الطاقة (نسبة الطاقة إلى الوزن) للمولد المقترح هي الحد الأقصى.

Wind energy is one of the supremely renewable energy sources and has been widely established worldwide. Due to strong seasonal variations in the wind resource, accurate predictions of wind resource assessment and appropriate wind speed distribution models (for any location) are the significant facets for planning and commissioning wind farms. In this work, the wind characteristics and wind potential assessment of onshore, offshore, and nearshore locations of India—particularly Kayathar in Tamilnadu, the Gulf of Khambhat, and Jafrabad in Gujarat—are statistically analyzed with wind distribution methods. Further, the resource assessments are carried out using Weibull, Rayleigh, gamma, Nakagami, generalized extreme value (GEV), lognormal, inverse Gaussian, Rician, Birnbaum–Sandras, and Bimodal–Weibull distribution methods. Additionally, the advent of artificial intelligence and soft computing techniques with the moth flame optimization (MFO) method leads to superior results in solving complex problems and parameter estimations. The data analytics are carried out in the MATLAB platform, with in-house coding developed for MFO parameters estimated through optimization and other wind distribution parameters using the maximum likelihood method. The observed outcomes show that the MFO method performed well on parameter estimation. Correspondingly, wind power generation was shown to peak at the South West Monsoon periods from June to September, with mean wind speeds ranging from 9 to 12 m/s. Furthermore, the wind speed distribution method of mixed Weibull, Nakagami, and Rician methods performed well in calculating potential assessments for the targeted locations. Likewise, the Gulf of Khambhat (offshore) area has steady wind speeds ranging from 7 to 10 m/s with less turbulence intensity and the highest wind power density of 431 watts/m2. The proposed optimization method proves its potential for accurate assessment of Indian wind conditions in selected locations.

The increase in the emission of greenhouse gases (GHG) is one of the most important problems in the world. Decreasing GHG emissions will be a big challenge in the future. The transportation sector uses a significant part of petroleum production in the world, and this leads to an increase in the emission of GHG. The result of this issue is that the population of the world befouls the environment by the transportation system automatically. Electric Vehicles (EV) have the potential to solve a big part of GHG emission and energy efficiency issues such as the stability and reliability of energy. Therefore, the EV and grid relation is limited to the Vehicle-to-Grid (V2G) or Grid-to-Vehicle (G2V) function. Consequently, the grid has temporary energy storage in EVs’ batteries and electricity in exchange for fossil energy in vehicles. The energy actors and their research teams have determined some targets for 2050; hence, they hope to decrease the world temperature by 6 °C, or at least by 2 °C in the normal condition. Fulfilment of these scenarios requires suitable grid infrastructure, but in most countries, the grid does not have a suitable background to apply in those scenarios. In this paper, some problems regarding energy scenarios, energy storage systems, grid infrastructure and communication systems in the supply and demand side of the grid are reviewed.

Uncertainties are the most significant challenges in the smart power system, necessitating the use of precise techniques to deal with them properly. Such problems could be effectively solved using a probabilistic optimization strategy. It is further divided into stochastic, robust, distributionally robust, and chance-constrained optimizations. The topics of probabilistic optimization in smart power systems are covered in this review paper. In order to account for uncertainty in optimization processes, stochastic optimization is essential. Robust optimization is the most advanced approach to optimize a system under uncertainty, in which a deterministic, set-based uncertainty model is used instead of a stochastic one. The computational complexity of stochastic programming and the conservativeness of robust optimization are both reduced by distributionally robust optimization.Chance constrained algorithms help in solving the constraints optimization problems, where finite probability get violated. This review paper discusses microgrid and home energy management, demand-side management, unit commitment, microgrid integration, and economic dispatch as examples of applications of these techniques in smart power systems. Probabilistic mathematical models of different scenarios, for which deterministic approaches have been used in the literature, are also presented. Future research directions in a variety of smart power system domains are also presented.

The special issue “Energy Storage Systems and Power Conversion Electronics for E-Transportation and Smart Grid” on MDPI Energies presents 20 accepted papers, with authors from North and South America, Asia, Europe and Africa, related to the emerging trends in energy storage and power conversion electronic circuits and systems, with a specific focus on transportation electrification and on the evolution of the electric grid to a smart grid. An extensive exploitation of renewable energy sources is foreseen for smart grid as well as a close integration with the energy storage and recharging systems of the electrified transportation era. Innovations at both algorithmic and hardware (i.e., power converters, electric drives, electronic control units (ECU), energy storage modules and charging stations) levels are proposed.

Infrared Thermography has been used as a tool for predictive and preventive maintenance of Photovoltaic panels. International Electrotechnical Commission provides some guidelines for using thermography to detect defects in Photovoltaic panels. However, the proposed guidelines focus only on the location of the hot spot than diagnosing the types of faults. The long-term reliability and efficiency of panels can be affected by progressive defects such as discolouring and delamination. This paper proposed the new Thermal Pixel Counting algorithm to detect the above faults based on three thermal profile index values. The real-time experimental testing was carried out using FLIR T420bx® thermal imager and results have been provided to validate the proposed method. In this work, the fuzzy rule-based classification system is proposed to automate the classification process. Fuzzy reasoning method based on a single winner rule fuzzy classifier is designed with modified rule weights by particular grade. The performance of the proposed classifier is compared with the conventional fuzzy classifier and neural network model.

The introduction of electric vehicles into the transportation sector helps reduce global warming and carbon emissions. The interaction between electric vehicles and the power grid has spurred the emergence of a smart grid technology, denoted as vehicle-to grid-technology. Vehicle-to-grid technology manages the energy exchange between a large fleet of electric vehicles and the power grid to accomplish shared advantages for the vehicle owners and the power utility. This paper presents an optimal scheduling of vehicle-to-grid using the genetic algorithm to minimize the power grid load variance. This is achieved by allowing electric vehicles charging (grid-to-vehicle) whenever the actual power grid loading is lower than the target loading, while conducting electric vehicle discharging (vehicle-to-grid) whenever the actual power grid loading is higher than the target loading. The vehicle-to-grid optimization algorithm is implemented and tested in MATLAB software (R2013a, MathWorks, Natick, MA, USA). The performance of the optimization algorithm depends heavily on the setting of the target load, power grid load and capability of the grid-connected electric vehicles. Hence, the performance of the proposed algorithm under various target load and electric vehicles’ state of charge selections were analysed. The effectiveness of the vehicle-to-grid scheduling to implement the appropriate peak load shaving and load levelling services for the grid load variance minimization is verified under various simulation investigations. This research proposal also recommends an appropriate setting for the power utility in terms of the selection of the target load based on the electric vehicle historical data.