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Krishnamurthy, Raghavendra

Publications and source records attributed to Krishnamurthy, Raghavendra.

9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Large-eddy simulation of an atmospheric bore and associated gravity wave effects on wind farm performance in the southern Great Plains

Gravity waves are a common occurrence in the atmosphere, with a variety of generation mechanisms. Their impact on wind farms has only recently gained attention, with most studies focused on wind farm-induced gravity waves. In this study, the interaction between a wind farm and gravity waves generated by an atmospheric bore event is assessed using multiscale large-eddy simulations. The atmospheric bore is created by a thunderstorm downdraft from a nocturnal mesoscale convective system (MCS). The associated gravity waves impact the wind resource and power production at a nearby wind farm during the American Wake Experiment (AWAKEN) in the US southern Great Plains. A two-domain nested setup (Δx=300 and 20 m) is used in the Weather Research and Forecasting (WRF) model, forced with data from the High-Resolution Rapid Refresh model, to capture both the formation of the bore and its interaction with individual wind turbines. The MCS is resolved on the large outer domain, where the structure of the bore and the associated gravity waves are found to be especially sensitive to parameterized microphysics processes. On the finer inner domain, gravity wave interactions with individual wind turbines are resolved; wake dynamics are captured using a generalized actuator disk parameterization in WRF. The gravity waves are found to have a strong effect on the atmosphere above the wind farm; however, the effect of the waves is more nuanced closer to the surface where there is additional turbulence, both ambient and wake-generated. Notably, the gravity waves modulate the mesoscale environment by weakening and dissipating the preexisting low-level jet, which reduces hub-height wind speed and hence the simulated power output, which is confirmed by the observed supervisory control and data acquisition (SCADA) power data. Additionally, the gravity waves induce local wind direction variations correlated with fluctuations in pressure, which lead to fluctuations in the simulated power output as various turbines within the farm are subjected to waking from nearby turbines.

17 WIND ENERGY↗
DOE OSTI2024

Characterizing model uncertainties in simulated coast-to-offshore wind over the northeast U.S. using multi-platform measurements from the TCAP field campaign

Numerical weather prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, are widely used to provide estimates of the offshore wind energy resource owing to their large spatial coverage compared to available observations. Nevertheless, spatiotemporal distribution of model biases is highly dependent on factors including model configuration, location, and the interplay of multi-scale physical processes. Here, in this study, we focus on the characterization of model uncertainties in simulated coast-to-offshore winds over the northeast U.S., by varying sea surface temperature (SST) forcings, surface layer (SL) and planetary boundary layer (PBL) parameterizations, as well as identifying biases that may be directly passed from initial and boundary conditions. Multiple measurements, including aircraft data collected during the U.S. Department of Energy's Two-Column Aerosol Project (TCAP) experiment, are used to constrain the model results and facilitate quantitative comparisons. Our analysis indicates while SST forcing has notable impacts on simulated air temperature and moisture within PBL, the modeled winds are in general more sensitive to the choices of SL and PBL physics than to SST. The model’s forcing data not only controls the vertical dependence of wind speed errors, but also alters regional variability in wind speed’s spatial correlation. Bias comparisons between ERA5 reanalysis and ensemble simulations revealed significant similarity, particularly in wind speed biases during winter, underscoring their dependency on initial and boundary conditions. Coastal and offshore near-surface wind speed biases tend to exhibit much higher similarity in winter than in summer due to the presence of much stronger and more persistent synoptic wind conditions. This study highlights the importance of accurate atmospheric forcing and parameterization choices in improving wind forecasts and suggests the potential for extrapolating coastal wind biases to offshore locations, aiding wind energy forecasting and informing the Wind Forecast Improvement Project-3 (WFIP3).

17 WIND ENERGY↗
DOE OSTI2024

Coastal Upwelling Off the California Coast - A Satellite Perspective

The planning of offshore wind farms off the California coast, near Humboldt Bay in northern CA and Morro Bay in central CA, raises concerns about their potential influence on local wind patterns and, consequently, coastal upwelling dynamics. The coastal upwelling phenomenon is responsible for transporting cold, nutrient-rich waters from the deeper ocean to the surface, nurturing the area's ecosystems and fisheries that are deeply intertwined with the region's cultural identity. As stakeholders voice concerns about the impact of the wind farm developments, this study endeavors to shed light on the interactions between offshore wind conditions and coastal upwelling processes using satellite data. We aim to provide observational insights from a multi-decade time period that deepen the scientific understanding of coastal upwelling processes and eventually inform sustainable energy policies with broader implications for coastal ecosystems.

California↗
DOE OSTI2024

Wind Energy Instrumentation Development Roadmap

The instrumentation development roadmap provides a guide on which measurements, and instruments, are important for future field campaigns to meet both the science objects and validation plans for their successful execution. The roadmap ensures the measurements are of sufficient type and resolution to meet science objectives and validation needs essential to the campaigns. The roadmap includes measurement categories ranging from instruments that need to be created to existing instruments essential to the field campaigns. The creation of the instrumentation development roadmap builds upon the previous Atmospheric to Electrons (A2e) validation work and formation of the American WAKE experimeNt (AWAKEN) science objectives.

17 WIND ENERGY↗
DOE OSTI2024

Lessons Learned From the Planning of Recent Wind Energy Technologies Office Field Campaigns

The U.S. Department of Energy (DOE) Wind Energy Technology Office (WETO) has funded several wind-energy-focused field campaigns in recent years. While essential to advance our understanding of the interactions between atmosphere and wind turbines, the planning of such campaigns has presented several challenges to the institutions involved in these efforts. In this document, we focus on the planning phase of the field campaigns and summarize the lessons learned from the recent AWAKEN, RAAW, and WFIP-3 field projects. We cover a variety of aspects to offer a proposed methodological pipeline that we recommend is followed when future similar endeavors are planned.

17 WIND ENERGY↗
DOE OSTI2024

Tilted lidar profiling: Development and testing of a novel scanning strategy for inhomogeneous flows

The most common profiling techniques for the atmospheric boundary layer based on a monostatic Doppler wind lidar rely on the assumption of horizontal homogeneity of the flow. This assumption breaks down in the presence of either natural or human-made obstructions that can generate significant flow distortions. The need to deploy ground-based lidars near operating wind turbines for the American WAKE experimeNt (AWAKEN) spurred a search for novel profiling techniques that could avoid the influence of the flow modifications caused by the wind farms. With this goal in mind, two well-established profiling scanning strategies have been retrofitted to scan in a tilted fashion and steer the beams away from the more severely inhomogeneous region of the flow. Results from a field test at the National Renewable Energy Laboratory's 135-m meteorological tower show that the accuracy of the horizontal mean flow reconstruction is insensitive to the tilt of the scan, although higher-order wind statistics are severely deteriorated at extreme tilts mainly due to geometrical error amplification. A numerical study of the AWAKEN domain based on the Weather Research and Forecasting Model and large-eddy simulation are also conducted to test the effectiveness of tilted profiling. It is shown that a threefold reduction of the error on inflow mean wind speed can be achieved for a lidar placed at the base of the turbine using tilted profiling.

17 WIND ENERGY↗