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1. Turbulence in the Sub-Alfvénic Solar Wind

   https://doi.org/10.3847/2041-8213/ac51da  

   Zank, G. P. ; Zhao, L.-L. ; Adhikari, L. ; Telloni, D. ; Kasper, J. C. ; Stevens, M. ; Rahmati, A. ; Bale, S. D. ( February 2022 , The Astrophysical Journal Letters)

   Abstract The Parker Solar Probe (PSP) entered a region of sub-Alfvénic solar wind during encounter 8, and we present the first detailed analysis of low-frequency turbulence properties in this novel region. The magnetic field and flow velocity vectors were highly aligned during this interval. By constructing spectrograms of the normalized magnetic helicity, cross-helicity, and residual energy, we find that PSP observed primarily Alfvénic fluctuations, a consequence of the highly field-aligned flow that renders quasi-2D fluctuations unobservable to PSP. We extend Taylor’s hypothesis to sub- and super-Alfvénic flows. Spectra for the fluctuating forward and backward Elsässer variables ( z ± ,more »respectively) are presented, showing that z + modes dominate z − by an order of magnitude or more, and the z + spectrum is a power law in frequency (parallel wavenumber) f −3/2 ( k ∥ − 3 / 2 ) compared to the convex z − spectrum with f −3/2 ( k ∥ − 3 / 2 ) at low frequencies, flattening around a transition frequency (at which the nonlinear and Alfvén timescales are balanced) to f −1.25 at higher frequencies. The observed spectra are well fitted using a spectral theory for nearly incompressible magnetohydrodynamics assuming a wavenumber anisotropy k ⊥ ∼ k ∥ 3 / 4 , that the z + fluctuations experience primarily nonlinear interactions, and that the minority z − fluctuations experience both nonlinear and Alfvénic interactions with z + fluctuations. The density spectrum is a power law that resembles neither the z ± spectra nor the compressible magnetic field spectrum, suggesting that these are advected entropic rather than magnetosonic modes and not due to the parametric decay instability. Spectra in the neighboring modestly super-Alfvénic intervals are similar.« less
2. A Wake Modeling Paradigm for Wind Farm Design and Control

   https://doi.org/10.3390/en12152956  

   Shapiro, Carl R. ; Starke, Genevieve M. ; Meneveau, Charles ; Gayme, Dennice F. ( August 2019 , Energies)

   Wake models play an integral role in wind farm layout optimization and operations where associated design and control decisions are only as good as the underlying wake model upon which they are based. However, the desired model fidelity must be counterbalanced by the need for simplicity and computational efficiency. As a result, efficient engineering models that accurately capture the relevant physics—such as wake expansion and wake interactions for design problems and wake advection and turbulent fluctuations for control problems—are needed to advance the field of wind farm optimization. In this paper, we discuss a computationally-efficient continuous-time one-dimensional dynamic wake modelmore »that includes several features derived from fundamental physics, making it less ad-hoc than prevailing approaches. We first apply the steady-state solution of the model to predict the wake expansion coefficients commonly used in design problems. We demonstrate that more realistic results can be attained by linking the wake expansion rate to a top-down model of the atmospheric boundary layer, using a super-Gaussian wake profile that smoothly transitions between a top-hat and Gaussian distribution as well as linearly-superposing wake interactions. We then apply the dynamic model to predict trajectories of wind farm power output during start-up and highlight the improved accuracy of non-linear advection over linear advection. Finally, we apply the dynamic model to the control-oriented application of predicting power output of an irregularly-arranged farm during continuous operation. In this application, model fidelity is improved through state and parameter estimation accounting for spanwise inflow inhomogeneities and turbulent fluctuations. The proposed approach thus provides a modeling paradigm with the flexibility to enable designers to trade-off between accuracy and computational speed for a wide range of wind farm design and control applications.« less
3. Coordinated Wide-Area Control of Multiple Controllers in a Power System Embedded with HVDC Lines

   https://doi.org/10.1109/TPWRS.2020.3016354  

   Gupta, Pooja ; Pal, Anamitra ; Vittal, Vijay ( August 2020 , IEEE Transactions on Power Systems)

   This paper assesses the stability improvements that can be achieved through the coordinated wide-area control of power system stabilizers (PSSs), static VAr compensators (SVCs), and supplementary damping controllers (SDCs) for damping low frequency oscillations (LFOs) in a power system embedded with multiple high voltage DC (HVDC) lines. The improved damping is achieved by designing a coordinated widearea damping controller (CWADC) that employs partial state feedback. The design methodology uses a linear matrix inequality (LMI)-based mixed H2=H1 robust control for multiple operating scenarios. To reduce the high computational burden, an enhanced version of selective modal analysis (SMA) is employed that notmore »only reduces the number of required wide-area feedback signals, but also identifies alternate feedback signals. Additionally, the impact of delays on the performance of the control design is investigated. The studies are performed on a 29 machine, 127 bus equivalent model of the Western Electricity Coordinating Council (WECC) system-embedded with three HVDC lines and two wind farms.« less
4. Evaluation of Solar-Powered Battery Systems for Individuals Using Electricity-Dependent Medical Devices in Puerto Rico Following Hurricane Maria

   https://doi.org/10.1017/dmp.2021.114  

   Tosado, Gabriella A. ; Matos, Marvi ; Ahumada-Paras, Mareldi ; Chapko, Michael K. ; Pozzo, Lilo D. ( June 2021 , Disaster Medicine and Public Health Preparedness)

   Abstract Objectives: To determine if solar-powered battery systems could be successfully used for electricity-dependent medical devices by families during a power outage. Methods: We assessed the use of and satisfaction with solar-powered battery systems distributed to 15 families following Hurricane Maria in rural Puerto Rico. Interviews were conducted in July 2018, 3 mo following distribution of the systems. Results: The solar-powered battery systems powered refrigeration for medications and prescribed diets, asthma therapy, inflatable mattresses to prevent bedsores, and continuous positive airway pressure machines for sleep apnea. Despite some system problems, such as inadequate power, defective cables, and blown fuses, familiesmore »successfully dealt with these issues with some outside help. Almost all families were pleased with the systems and a majority would recommend solar-powered battery systems to a neighbor. Conclusions: Families accepted and successfully used solar-powered battery systems to power medical devices. Solar-powered battery systems should be considered as alternatives to generators for power outages after hurricanes and other disasters. Additional research and analysis are needed to inform policy on increasing access to such systems.« less
5. The Impact of Neglecting Climate Change and Variability on ERCOT’s Forecasts of Electricity Demand in Texas

   https://doi.org/10.1175/WCAS-D-21-0140.1  

   Lee, Jangho ; Dessler, Andrew E. ( April 2022 , Weather, Climate, and Society)

   Abstract The Electric Reliability Council of Texas (ERCOT) manages the electric power across most of Texas. They make short-term assessments of electricity demand on the basis of historical weather over the last two decades, thereby ignoring the effects of climate change and the possibility of weather variability outside the recent historical range. In this paper, we develop an empirical method to predict the impact of weather on energy demand. We use that with a large ensemble of climate model runs to construct a probability distribution of power demand on the ERCOT grid for summer and winter 2021. We find thatmore »the most severe weather events will use 100% of available power—if anything goes wrong, as it did during the 2021 winter, there will not be sufficient available power. More quantitatively, we estimate a 5% chance that maximum power demand would be within 4.3 and 7.9 GW of ERCOT’s estimate of best-case available resources during summer and winter 2021, respectively, and a 20% chance it would be within 7.1 and 17 GW. The shortage of power on the ERCOT grid is partially hidden by the fact that ERCOTs seasonal assessments, which are based entirely on historical weather, are too low. Prior to the 2021 winter blackout, ERCOT forecast an extreme peak load of 67 GW. In reality, we estimate hourly peak demand was 82 GW, 22% above ERCOT’s most extreme forecast and about equal to the best-case available power. Given the high stakes, ERCOT should develop probabilistic estimates using modern scientific tools to predict the range of power demand more accurately.« less