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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.

The path congestion and communication risks of electric power communication network have emerged as the carried businesses are becoming more and more heavy. In this paper, a multi-objective optimization method for power communication network routing considering the importance of the carried businesses is proposed to reduce load imbalance and transmission risk. Firstly, information entropy is introduced as the objective of communication network load balancing optimization. And a risk assessment model for power communication network nodes and links is established. Then fuzzy membership functions are adopted to singularize the two objectives to jointly optimize path congestion and communication risks. The device nodes are dynamically divided according to the carried businesses to pursue the global optimization of the power communication network in which the Yen's algorithm is adopted. Finally, this paper uses the IEEE 30-bus communication network to carry out case simulations and analyzes the proposed method to verify the effectiveness and feasibility.

In this paper, we study the interactions among interconnected autonomous microgrids, and propose a joint energy trading and scheduling strategy. Each interconnected microgrid not only schedules its local power supply and demand, but also trades energy with other microgrids in a distribution network. Specifically, microgrids with excessive renewable generations can trade with other microgrids in deficit of power supplies for mutual benefits. Since interconnected microgrids operate autonomously, they aim to optimize their own performance and expect to gain benefits through energy trading. We design an incentive mechanism using Nash bargaining theory to encourage proactive energy trading and fair benefit sharing. We solve the bargaining problem by decomposing it into two sequential problems on social cost minimization and trading benefit sharing, respectively. For practical implementation, we propose a decentralized solution method with minimum information exchange overhead. Numerical studies based on realistic data demonstrate that the total cost of the interconnected-microgrids operation can be reduced by up to 13.2% through energy trading, and an individual participating microgrid can achieve up to 29.4% reduction in its cost through energy trading. To appear in IEEE Transactions on Smart Grid

Abstract With the rapid advancement in wearable electronics, energy harvesting devices based on triboelectric nanogenerators (TENGs) have been intensively investigated for providing sustainable power supply for them. However, the fabrication of wearable TENGs still remains great challenges, such as flexibility, breathability and washability. Here, a route to develop a new kind of woven-structured triboelectric nanogenerator (WS-TENG) with a facile, low-cost, and scalable electrospinning technique is reported. The WS-TENG is fabricated with commercial stainless-steel yarns wrapped by electrospun polyamide 66 nanofiber and poly(vinylidenefluoride-co-trifluoroethylene) nanofiber, respectively. Triggered by diversified friction materials under a working principle of freestanding mode, the open-circuit voltage, short-circuit current and maximum instantaneous power density from the WS-TENG can reach up to 166 V, 8.5 µA and 93 mW/m2, respectively. By virtue of high flexibility, desirable breathability, washability and excellent durability, the fabricated WS-TENG is demonstrated to be a reliable power textile to light up 58 light-emitting diodes (LED) connected serially, charge commercial capacitors and drive portable electronics. A smart glove with stitched WS-TENGs is made to detect finger motion in different circumstances. The work presents a new approach for self-powered textiles with potential applications in biomechanical energy harvesting, wearable electronics and human motion monitoring.

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 rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. The commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.