Soft Actor-Critic Based Voltage Support for Microgrid Using Energy Storage Systems
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Increase in the number and frequency of widespread outages in recent years has been directly linked to drastic climate change necessitating better preparedness for outage mitigation. Severe weather conditions are experienced more frequently and on larger scales, challenging system operation and recovery time after an outage. In conclusion, the impact is more evident and concerning than before, considering the increased dependency on electricity in all aspects of our lives.
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This work revisits the theoretical limits of one-degree-of-freedom wave energy converters. This paper considers the floating sphere used in the Ocean Energy Systems Task 10 Wave Energy Converter modeling and verification effort for analysis. Analytical equations are derived to determine bounds on the motion amplitude, time-averaged power, and power-take-off (PTO) force. A unique result was found that shows the time-averaged power absorbed by a wave energy converter can be defined solely by the inertial properties and radiation hydrodynamic coefficients. In addition, a unique expression for the PTO force amplitude was derived that has provided upper and lower bounds when resistive control is used to maximize power generation. For complex conjugate control, this same expression can only provide a lower bound, as there is theoretically no upper bound. These bounds are used to compare the performance of a floating sphere if it were to extract energy using surge or heave motion. The analysis shows that because of the differences in hydrodynamic coefficients of each oscillating mode, there will be different frequency ranges that provide better power capture efficiency. The influence of a motion constraint on power absorption while also utilizing a nonideal power take-off is examined and found to reduce the losses associated with bidirectional energy flow. The expression to calculate the time-averaged power with a nonideal PTO is modified by the mechanical-to-electrical efficiency and the ratio of the PTO spring and damping coefficients. The PTO spring and damping coefficients were separated in the expression, which allows for limits to be set on the possible values of PTO coefficients to ensure a net flow of power to the grid.
We report a design and implementation of proton deflectometry with an in situ reference x-ray image of a mesh to precisely measure non-uniform magnetic fields in expanding plasmas at the OMEGA and OMEGA EP laser facilities. The technique has been developed with proton and x-ray sources generated from both directly driven capsule implosions and short pulse laser–solid interactions. The accuracy of the measurement depends on the contrast of both the proton and x-ray images. Here we present numerical and analytic studies to optimize the image contrast using a variety of mesh materials and grid spacings. Our results show clear enhancement of the image contrast by factors of four to six using a high Z mesh with large grid spacing. This leads to further improvement in the accuracy of the magnetic field measurement using this technique in comparison with its first demonstration at the OMEGA laser facility [Rev. Sci. Instrum. 93, 023502 (2022) [CrossRef]].
An interior partition wall integrated with active thermal storage and a dynamic insulation system was built and then installed in an office building in Oak Ridge, Tennessee, TN. This smart wall, termed the Empower Wall, was equipped with embedded pipes in the building envelope core component and an additional pipe network enclosing rigid insulation to switch on and off the active insulation dynamically. The performance of the wall's contribution to cooling load reduction under different parameters has been investigated in previous publications. Aiming to be deployed into model predictive control and other optimization methods, simplified and reliable models for the developed wall and the room accommodating it are required. They are needed to characterize the properties and thermal response of both Empower Wall and building envelope, which form an essential component for accurate indoor temperature or cooling/heating demand prediction. In this study, simplified gray-box and regression models as well as machine learning model were developed and the performance of them were compared and analyzed.
The GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model has been developed by Argonne National Laboratory with the support of the U.S. Department of Energy (DOE). GREET is a life-cycle analysis (LCA) tool, structured to systematically examine the energy and environmental effects of a wide variety of transportation fuels and vehicle technologies in major transportation sectors (i.e., road, air, marine, and rail) and other end-use sectors, and energy systems. Argonne has expanded and updated the model in various sectors in GREET 2020, and this report provides a summary of the release.
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