• Energy Research
• 2016-2025close
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In order to achieve paramount economy, hybrid renewable energy sources are gaining importance, as renewable sources are costless. Over the past few years wind energy incorporation drew more consideration in the electricity market, as wind power took an affirmative role in energy saving as well as sinking emission pollutants. Recently developed Grey wolf optimizer (GWO) algorithm has conspicuous behavior for verdicting global optima, without getting ensnared in premature convergence. In the proposed research the exploitation phase of the grey wolf optimizer has been further improved using random exploratory search algorithm, which uses perturbed solutions vectors along with previously generated solution vectors. The paper presents a hybrid version of Grey Wolf Optimizer algorithm combined with random exploratory search algorithm (hGWO-RES) for the solution of combinatorial scheduling and dispatch problem of electric power systems. To validate the feasibility of the algorithm, the proposed algorithm has been tested on 23 benchmark problems. To verify the feasibility and efficacy of operation of proposed algorithm on generation scheduling and dispatch of electric power systems, small and medium scale power systems consisting of 7-, 10-, 19-, 20- and 40-generating units systems taken into consideration. Commitment and scheduling pattern has been evaluated with and without wind integration and it has been experimentally founded that proposed hybrid algorithm provides superior solution as compared to other recently reported meta-heuristics search algorithms.

<abstract> <p>The rising proportion of inverter-based renewable energy sources in current power systems has reduced the rotational inertia of overall microgrid systems. This may cause high-frequency fluctuations in the system leading to system instability. Several initiatives have been suggested concerning inertia emulation based on other integrated external energy sources, such as energy storage systems, to combat the ever-declining issue of inertia. Hence, to deal with the aforementioned issue, we suggest the development of an optimal fractional sliding mode control (FSMC)-based frequency stabilization strategy for an industrial hybrid microgrid. An explicit state-space industrial microgrids model comprised of several coordinated energy sources along with loads, storage systems, photovoltaic and wind farms, is considered. In addition to this, the impact of electric vehicles and batteries with adequate control of the state of charge was investigated due to their short regulation times and this helps to balance the power supply and demand that in turn brings the minimization of the frequency deviations. The performance of the FSMC controller is enhanced by setting optimal parameters by employing the tuning strategy based on an iterative teaching-learning-based optimizer (ITLBO). To justify the efficacy of the proposed controller, the simulated results were obtained under several system conditions by using a vehicle simulator in a MATLAB/Simulink environment. The results reveal the enhanced performance of the ITLBO optimized fractional sliding mode control to effectively damp the frequency oscillations and retain the frequency stability with robustness, quick damping, and reliability under different system conditions.</p> </abstract>

Abstract Limiting the increase of global temperature requires electrification of the railway transport, which is relatively a distinct mode of transport in terms of economy, business and socialization of a country. However, battery complemented railway transport systems such as fuel cell hybrid railway propulsion systems are constrained by the high cost of the battery, and suboptimal performance of the fuel cell under varying loads. Optimized selection of battery can reduce its costs associated with sizing, life and utilization. Similarly, managing the load distribution between the battery and fuel cell can reduce the load variations concern for fuel cell. In this study, model-based selective characterization of the battery and fuel cell is done to identify the optimal features and constraints. Following characterization, the load allocation to battery and fuel cell is determined with the targets of collaborative utilization of optimal features and mitigation of constraints. Subsequently, considering this load allocation and results of characterization, conditions are proposed for reliable sizing and optimized selection of battery. The significance of the proposed conditions in reliable sizing is explored. Based on these conditions, certain commercially developed batteries are evaluated for optimized selection of battery. The results signify this study as a foundation for research on the reliable sizing and optimized selection of battery in fuel cell hybrid railway propulsion systems.

The use of superconducting magnetic energy storage (SMES) has been widely reported in the literature to mitigate various load frequency control (LFC) issues in a multi-area power system. Most of these are thyristor based SMES, employing proportional type controllers. In this paper, a supervisory adaptive model predictive control scheme (AMPC) is proposed for a voltage source converter based relatively small rating SMES for LFC application. The reference power command for the SMES is derived from the AMPC in such a manner that it effectively handles the operational constraints of the SMES system. A representative first-order system emulating the inner loop dynamics of the SMES chopper system, is tuned offline via genetic algorithm (GA) and is used to derive dynamic constraints for the cost function in AMPC. The effectiveness of the scheme is demonstrated through simulations.

Dans des scénarios réalistes, la performance dynamique d'un cluster de micro-réseaux est largement affectée par la puissance intermittente des sources d'énergie renouvelables et les changements de charge fréquents. Pour résoudre ce problème, un contrôleur secondaire à double couche basé sur le temps fixe distribué est conçu pour améliorer les performances dynamiques inter-microgrid et intra-microgrid dans un temps de stabilisation fixe. Le contrôleur proposé est indépendant des valeurs de fonctionnement initiales par opposition à la loi de contrôle à temps fini. Chaque agent global dans un micro-réseau fonctionne pour atténuer le décalage de charge entre les autres agents globaux, tandis que chaque agent local dans un micro-réseau fonctionne pour réaliser un partage de courant de charge proportionnel et une régulation de tension moyenne entre eux dans un temps fixe. Cependant, comme l'atténuation de la non-concordance de chargement dans des conditions de charge légère affecte l'efficacité du système en raison de pertes de ligne importantes, le fonctionnement du cluster passe à une approche de minimisation des pertes distribuées, qui fonctionne en utilisant des mesures en ligne des micro-réseaux voisins. Pour caractériser le mode de fonctionnement dans la cyber-couche globale, un seuil de point de chargement critique pour le cluster est ainsi déterminé. La performance du cluster utilisant la stratégie proposée est simulée dans l'environnement MATLAB/SIMULINK pour divers scénarios afin de démontrer sa fiabilité et son efficacité. En escenarios realistas, el rendimiento dinámico de un grupo de microrredes se ve afectado en gran medida por la potencia intermitente de las fuentes de energía renovables y los frecuentes cambios de carga. Para abordar este problema, un controlador secundario de doble capa basado en tiempo fijo distribuido está diseñado para mejorar el rendimiento dinámico entre microrredes y entre microrredes dentro de un tiempo de asentamiento fijo. El controlador propuesto es independiente de los valores operativos iniciales en oposición a la ley de control de tiempo finito. Cada agente global en una microrred opera para mitigar el desajuste de carga entre otros agentes globales, mientras que cada agente local en una microrred opera para lograr un reparto de corriente de carga proporcional y una regulación de voltaje promedio entre ellos en un tiempo fijo. Sin embargo, como la mitigación de la falta de coincidencia de carga durante condiciones de carga ligera afecta la eficiencia del sistema debido a pérdidas de línea significativas, la operación del clúster cambia a un enfoque de minimización de pérdidas distribuidas, que opera utilizando mediciones en línea de las microrredes vecinas. Para caracterizar el modo de operación en la capa cibernética global, se determina así un punto crítico de umbral de carga para el clúster. El rendimiento del clúster que emplea la estrategia propuesta se simula en el entorno MATLAB/SIMULINK para varios escenarios para demostrar su confiabilidad y eficiencia. In realistic scenarios, the dynamic performance of a microgrid cluster is largely affected by the intermittent power of renewable energy sources and frequent load changes. To address this issue, a distributed fixed-time based dual layer secondary controller is designed to improve inter-microgrid and intra-microgrid dynamic performance within a fixed settling time. The proposed controller is independent of initial operating values as opposed to the finite time control law. Each global agent in a microgrid operates to mitigate loading mismatch between other global agents, whereas each local agent in a microgrid operates to achieve proportionate load current sharing and average voltage regulation between them in fixed time. However, as loading mismatch mitigation during light load conditions affects the system efficiency due to significant line losses, the cluster operation switches to a distributed loss minimization approach, which operates using online measurements from the neighboring microgrids. To characterize the mode of operation in the global cyber layer, a critical point of loading threshold for the cluster is thus determined. The performance of the cluster employing the proposed strategy is simulated in MATLAB/SIMULINK environment for various scenarios to demonstrate its reliability and efficiency. في السيناريوهات الواقعية، يتأثر الأداء الديناميكي لمجموعة الشبكات الصغيرة إلى حد كبير بالطاقة المتقطعة لمصادر الطاقة المتجددة والتغيرات المتكررة في الحمل. لمعالجة هذه المشكلة، تم تصميم وحدة تحكم ثانوية ثنائية الطبقة موزعة على أساس الوقت الثابت لتحسين الأداء الديناميكي بين الشبكات الدقيقة وداخلها في غضون وقت استقرار ثابت. وحدة التحكم المقترحة مستقلة عن قيم التشغيل الأولية بدلاً من قانون التحكم في الوقت المحدود. يعمل كل عامل عالمي في شبكة صغرى على التخفيف من عدم تطابق التحميل بين العوامل العالمية الأخرى، في حين يعمل كل عامل محلي في شبكة صغرى على تحقيق مشاركة تيار الحمل المتناسب ومتوسط تنظيم الجهد بينهما في وقت محدد. ومع ذلك، نظرًا لأن تخفيف عدم تطابق التحميل أثناء ظروف الحمل الخفيف يؤثر على كفاءة النظام بسبب الخسائر الكبيرة في الخطوط، تتحول عملية المجموعة إلى نهج تقليل الخسارة الموزعة، والذي يعمل باستخدام القياسات عبر الإنترنت من الشبكات الصغيرة المجاورة. لتوصيف طريقة التشغيل في الطبقة السيبرانية العالمية، يتم تحديد نقطة حرجة لعتبة التحميل للمجموعة. تتم محاكاة أداء المجموعة التي تستخدم الاستراتيجية المقترحة في بيئة ماتلاب/سيمولينك لسيناريوهات مختلفة لإثبات موثوقيتها وكفاءتها.

Plastic film mulching (FM) became a general practice to enhance crop productivity and its net primary production (NPP), but it can increase greenhouse gas (GHG) emissions. The proper addition of organic amendments might effectively decrease the impact of FM on global warming. To evaluate the feasibility of biomass addition on decreasing this negative influence, cover crop biomass as a green manure was incorporated with different recycling levels (0-100% of aboveground biomass) under FM and no-mulching. The net global warming potential (GWP) which integrated with soil C stock change and GHG (N2O and CH4) fluxes with CO2-equivalent was evaluated during maize cultivation. Under the same biomass incorporation, FM significantly enhanced the grain productivity and NPP of maize by 22-61 and 18-58% over no-mulching, respectively. In contrast, FM also highly increased the respired C loss, which was 11-95% higher than NPP increase, over no-mulching. Irrespective with biomass recycling ratio and mulching system, negative NECB which indicates the decrease of soil C stock was observed, mainly due to big harvest removal. FM decreased more soil C stock by 57-158% over no-mulching, but its C stock was clearly increased with increasing biomass addition. FM significantly increased total N2O and CH4 fluxes by 4-61 and 140-600% over no-mulching, respectively. Soil C stock changes mainly decided net GWP scale, but N2O and CH4 fluxes negligibly influenced. As a result, FM highly increased net GWP over no-mulching, while this net GWP was clearly decreased with increasing biomass application. However, cover cropping, and its biomass recycling was not enough to compensate the negative impact of FM on global warming. Therefore, more biomass incorporation might be essential to compensate this negative effect of FM.

This study deals with the core design of a PM vernier machine considering modulation flux effects, and the comparative investigation on volume and performance characteristics of the vernier over conventional PM machines are addressed. To these ends, for a PM vernier machine in operation at the base-speed, the flux density equations for teeth and yokes considering the flux modulation effects are derived, where the air gap harmonic permeance function is used. Using the derived equations, a PM vernier motor with specified yoke flux densities is designed. To identify the predicted flux yoke densities, the flux distribution and iron losses in core parts are analyzed through time-step finite element (FE) simulations. Through Fourier series expansion of the air gap flux waves obtained by FE analysis at several specified times, the harmonic components constituting the flux waves are investigated and their speeds are also evaluated in numerical ways. Finally, to estimate the competitiveness of vernier machines versus conventional machines, the designed PM vernier motor is compared against two different conventional PM motors designed through the same design procedures in various aspects such as volume, torque capacity, efficiency, and power factor, in which, in particular, the core losses are included in efficiency calculation.

As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.