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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.

Abstract The prime purpose of this work is to prepare a novel kind of Pickering interfacial solid catalysts for biodiesel production to meet the requirements of highly efficiency and environmental benign. To achieve this goal, the core–shell P[xSPA-yDABCO]@SiO2@Fe3O4 composite materials with a shell of photo-responsive and base catalytic sites were manufactured by means of layer-by-layer fabrication method. The modified materials, entirely characterized by transmission electron microscopy (TEM), scanning electron microscope (SEM), Fourier transform infrared (FT-IR) spectra, X-ray powder diffraction (XRD) and magnetization versus magnetic (VSM) techniques, demonstrated sufficient catalytic active sites and photo-responsive sites. Among all the so-prepared catalysts, P[3SPA-2DABCO]@SiO2@Fe3O4 performs extremely well and can stabilize soybean oil-in-methanol Pickering emulsion for 24 h, achieving a biodiesel yield up to 98.2% at a catalyst dosage of 5 wt% after the reaction time of 5 h at 60 °C. Furthermore, the double responsive solid catalyst can be readily separated from the mixture of reaction by an external magnet and UV irradiation, and still presented superior catalytic activity after 6 cycles.

This paper reports the generalized results of computer simulation of physical processes at a rotor-disk film evaporating plant. Optimization of the operation mode cannot be achieved without establishing patterns in the course of physical processes. We have proposed a computer model of hydrodynamics that accounts for all the features, initial and boundary conditions. The results of computer simulations make it possible to adequately assess the effectiveness of using a rotor-disk film evaporating plant (RDFVP) for the concentration of heat-labile materials. We have established patterns in the course of physical processes within a structure of RDFVP by using computer simulation of hydrodynamics in the programming environment ANSYS and applying a k-e turbulence model. The result of simulation is the derived velocity fields of the concentrated fluid (w max =0.413 m/s) and the gas phase (w max =8.176 m/s), as well as the magnitude of values for shear stress τ=0.94·10 -6 Pa. It was established that the gas heat-carrier is characterized by the highly-turbulent flows with maximum values for kinetic energy TKE max =8.985·10 -1 m 2 /s 2 . The reliability of results is ensured by the correctness, completeness, and adequacy of physical assumptions when stating the problem and while solving it using the computer aided design system ANSYS. It has been established that the proposed structure is an effective alternative to equipment for the concentration of solutions. The data obtained could be used when designing heat-and-mass-exchange equipment for the highly efficient dehydration of thermolabile materials

The electro-hydraulic servo pump control system (EHSPCS) is a volume control system that uses a permanent magnet synchronous motor (PMSM) with a fixed displacement pump to directly drive and control the hydraulic cylinder. The energy transmission law of the system is very complicated due to the transformation of electrical, mechanical and hydraulic energy as well as other energy fields, and qualitative analysis of the energy transfer efficiency is difficult. Energy transfer analysis of the EHSPCS under different working conditions and loads is proposed in this paper. First, the energy flow transfer mechanism was analyzed, and the mathematical and energy transfer models of the key components of the system were established to explore the energy characteristic state transition rule. Second, a power bond diagram model was built, its state equation and state matrix were deduced, and a system simulation model was built. Finally, combined with the EHSPCS experimental platform, simulation experiments were carried out on the dynamic position following and steady-state position holding conditions of the system, and the variation rules of the power of each energy characteristic state and the system energy transfer efficiency under different loads were obtained. The research results provide a foundation for the study of power matching and energy-saving mechanism of the EHSPCS.

AbstractTo maximize improving the tracking wind power output plan and the service life of energy storage systems (ESS), a control strategy is proposed for ESS to track wind power planning output based on model prediction and two-layer fuzzy control. First, based on model predictive control, a model with deviations of grid-connected power from the planned output and the minimum deviation of the remaining capacity of the ESS from the ideal value is established as the target. Then, when the grid-connected power exceeds the allowable deviation band of tracking, the weight coefficients in the objective function are adjusted by introducing the first layer of fuzzy control rules, combining the state of charge (SOC) of the ESS with the dynamic tracking demand of the planned value of wind power. When the grid-connected power is within the tracking allowable deviation band, the second layer of fuzzy control rules is used to correct the charging and discharging power of the ESS to improve its ability to track the future planned deviation while not crossing the limit. By repeatedly correcting the charging and discharging power of the ESS, its safe operation and the multitasking execution of the wind power plan output tracking target are ensured. Finally, taking actual data from a wind farm as an example, tests on a simulation platform of a combined wind-storage power generation system verify the feasibility and superiority of the proposed control strategy.