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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.

The Intergovernmental Panel on Climate Change (IPCC) report that to limit warming to 1.5 °C, Bioenergy with Carbon Capture and Storage (BECCS) is required. Integrated assessment models (IAMS) predict that a land area between the size of Argentina and Australia is required for bioenergy crops, a 3–7 time increase in the current bioenergy planting area globally. The authors pose the question of whether vertical farming (VF) technology can enable BECCS deployment, either via land sparing or supply. VF involves indoor controlled environment cultivation, and can increase productivity per unit land area by 5–10 times. VF is predominantly being used to grow small, high value leafy greens with rapid growth cycles. Capital expenditure, operational expenditure, and sustainability are challenges in current VF industries, and will affect the ability to utilise this technology for other crops. The authors argue that, whilst challenging, VF could help reach wider climate goals. Application of VF for bioenergy crops could be a game changer in delivering BECCS technologies and may reduce the land footprint required as well as the subsequent associated negative environmental impacts. VF bioenergy could allow us to cultivate the future demand for bioenergy for BECCS on the same, or less, land area than is currently used globally.

Second-generation bioethanol can be produced from various lignocellulosic biomasses such as wood, agricultural or forest residues. Lignocellulosic biomass is inexpensive, renewable and abundant source for bioethanol production. The conversion of lignocellulosic biomass to bioethanol could be a promising technology though the process has several challenges and limitations such as biomass transport and handling, and efficient pretreatment methods for total delignification of lignocellulosics. Proper pretreatment methods can increase concentrations of fermentable sugars after enzymatic saccharification, thereby improving the efficiency of the whole process. Conversion of glucose as well as xylose to bioethanol needs some new fermentation technologies to make the whole process inexpensive. The main goal of pretreatment is to increase the digestibility of maximum available sugars. Each pretreatment process has a specific effect on the cellulose, hemicellulose and lignin fraction; thus, different pretreatment methods and conditions should be chosen according to the process configuration selected for the subsequent hydrolysis and fermentation steps. The cost of ethanol production from lignocellulosic biomass in current technologies is relatively high. Additionally, low yield still remains as one of the main challenges. This paper reviews the various technologies for maximum conversion of cellulose and hemicelluloses fraction to ethanol, and it point outs several key properties that should be targeted for low cost and maximum yield.

<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>

Smart grid (SG) is an innovative technology which aims to make the conventional power grids capable enough to handle the ever increasing demands of power in an efficient manner. SG technology renders the electric distribution system with the capability of accumulating energy from various sources like wind, solar etc. But these sources have intermittency issues which can be handled in an effective manner with the coupling of electric vehicles (EVs) into the SGs. Thus, this paper presents a novel concept in the vehicle-to-grid (V2G) configuration. The primary objective of this paper to provide frequency support to grid by regulating the charging and discharging rates of EVs. These EVs are made to charge and discharge their respective energies at the charging stations (CSs) based on grid's overall requirements. Aggregators (AGs) at the CS level have been specially deployed to regulate EVs activities and maintain grid's stability. It has been verified through extensive simulations that EVs in V2G environment can stabilize the grid in terms of frequency if the coordination amongst the EVs is achieved through aggregators. The results obtained clearly depict that the controlled charging and discharging of EVs' battery can stabilize the grid in terms of frequency.

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.

Abstract Transient thermal behaviors of ultra-supercritical steam turbine control valves during the cold start warm-up process of steam turbine systems were comprehensively studied using conjugate heat transfer (CHT) simulation. The geometrical configurations and boundary conditions used in simulation were identical to the field setup in a thermal power plant. The simulated temperature variations were first validated using measurements by the flush-mounted thermocouples inside the solid valve bodies. The CHT simulation implementing the shear stress transport (SST) turbulence model demonstrated good agreement with the field data, and the overall numerical errors were below 10%; however, the numerical errors of the simulation, which used empirical heat transfer coefficients at the fluid–solid interfaces, reached 40%. The determined temperature differences between the cold valve bodies with the hot steam flow decreased significantly. Specifically, the temperature differences along the inner wall surfaces of the valve bodies decreased to less than 50 °C. Further investigation of the transient heat flux distributions and Nusselt number distributions confirmed that the unsteady flow behaviors, such as the alternating oscillations of the annular wall-attached jet, the central reverse flow and the intermediate shear layer instabilities, enhanced the fluid–solid heat convection process and thus contributed to the warming up of the solid valve bodies.

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.

The distribution feeders often gets overload under peak power demands. This situation is generally countered by load shading, which leads to financial losses to utilities and individual users. This paper presents the new methodology to support the real and reactive power demand through energy storage (ES) to avoid the load shading situation. The compensation of real / reactive power not only provides the voltage profile improvement but also ensures the sustain power to the consumers. A control scheme incorporated also maintains the unity power factor on source side. This relieves the existing distribution network from the extra reactive loading hence the line is having extra capacity for real power transfer to its maximum thermal limit. This additional capacity availability adds more customer base to justify the energy storage investment. The operational features are presented through a simulation of a realistic urban feeder data. The financial analysis is also presented to justify the energy storages with the distribution networks.