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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.

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.

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

The hydrate-based gas separation for capturing CO2 from flue gas has the characteristics of low energy consumption, simple operation and convenience for the subsequent CO2 storage and utilization. In order to reduce the total cumulative deviation of multi-stage hydration reaction, it is of great importance to establish an accurate thermodynamic model. Based on the vdW–P + CPA model, therefore, we refitted the parameters of the thermodynamic model considering the association between CO2 and H2O. Firstly, the energy parameter α0.5 of H2O and CO2 are developed as the cubic function and the linear function of [1-(T/Tc)0.5], respectively. Then, the calculation parameters of Langmuir absorption coefficient of vdW–P model is refitted based on the temperature dependent binary interaction parameters kij. The following research results are obtained. First, when the novel fitted thermodynamic model is used to predict the density of saturated fluid, the average absolute deviation (AAD) of H2O drops from 1.84% to 0.08% and that of CO2 drops from 4.06% to 2.09%. Second, when it is used to predict the phase equilibrium pressure of the hydrate generated from pure CO2 and pure N2, the AAD is 0.86% and 0.82%, respectively. Third, when it is used to calculate the phase equilibrium condition of hydrate generated from flue gas with different compositions, the AAD is decreased from 15.16% to 5.02%. In conclusion, this novel fitted thermodynamic model is of higher accuracy and it, to some extent, can decrease the total accumulative deviation of multi-stage hydration reaction. The research results provide reference for the actual application of the hydrate-based gas separation for capturing CO2 from flue gas. Keywords: Hydrate-based gas separation, Flue gas, CO2 capture, CO2 thermodynamic model, Multi-stage hydration reaction, Energy parameter, Langmuir absorption coefficient, Prediction

Owing to the growing interest of bioconvection flow of nanomaterials, many investigations on this topic have been performed, especially in this decade. The bioconvection flow of nanofluid includes some novel significance in era of biotechnology and bio-engineering like bio-fuels, microbial enhanced oil recovery, enzymes, pharmaceutical applications, petroleum engineering, etc. The current analysis aims to explore the various thermal properties of Sutterby nanofluid over rotating and stretchable disks with external consequences of variable thermal conductivity, heat absorption/generation consequences, activation energy and thermal radiation. The considered flow problem is changed into dimensionless form with convenient variables. The numerical structure for the obtained non-dimensional equations is numerically accessed with built-in shooting technique. The consequences of various physical parameters are observed for enhancement of velocity, temperature, concentration and motile microorganism. It is noted that both axial and tangential velocity components decrease with Reynolds number and buoyancy ratio parameter. The nanofluid concentration improves with activation energy and concentration Biot number. Moreover, an improved microorganisms profile is noticed with microorganism Biot number and bioconvection Rayleigh number.

Abstract The variation of properties with temperature have many practical applications in the area of chemical engineering and metallurgy, in the process of extrusion, the materials moving between a feed roll and on carrier belt. Here our intention is to explore the consequences of temperature dependent viscosity and variable thermal conductivity on flow of nanoliquid in a rotating system. Fluid between parallel plates is taken. Energy expression incorporates the exponential heat source. This analysis also explores the attributes of modified Arrhenius energy function with chemical reaction. Boundary layer problems have been computed via NDSolve approach. The obtained solutions are sketched for various estimations of embedded variables of interest. Results pointed out that both axial and transverse velocities show decaying behavior for higher rotation parameter. Thermal field boosts up with an enhancement of thermophoretic and space dependent heat source variables. Moreover the rate of mass transport decays through dimensionless activation energy.

Abstract The promise of redox flow batteries (RFBs) utilizing soluble redox couples, such as all vanadium ions as well as iron and chromium ions, is becoming increasingly recognized for large-scale energy storage of renewables such as wind and solar, owing to their unique advantages including scalability, intrinsic safety, and long cycle life. An ongoing question associated with these two RFBs is determining whether the vanadium redox flow battery (VRFB) or iron-chromium redox flow battery (ICRFB) is more suitable and competitive for large-scale energy storage. To address this concern, a comparative study has been conducted for the two types of battery based on their charge–discharge performance, cycle performance, and capital cost. It is found that: i) the two batteries have similar energy efficiencies at high current densities; ii) the ICRFB exhibits a higher capacity decay rate than does the VRFB; and iii) the ICRFB is much less expensive in capital costs when operated at high power densities or at large capacities.