arXiv subjects

Dennice Gayme

Publications and source records attributed to Dennice Gayme.

7 recordsLinked to original sources

arXiv2026

Shift or curtail? How much data-center flexibility is worth depends on the host power grid

Data-center growth risks overbuilding power grid infrastructure and stranding capital. Flexible data-center operation can defer infrastructure investments, but its value depends on the flexibility mechanism and the host power grid characteristics. We classify data-center load as firm, flexible or interruptible, and embed them in capacity expansion applied to market-organized, fossil-heavy PJM and carbon-capped, centrally coordinated Korea. In PJM, the flexibility value is spatial: shifting workloads between zones reduces system cost by 6% in 2028 and 19% in 2038, avoiding 4.4 GW and 8.9 GW of gas and nuclear generation. In Korea, it is temporal: shifting load into midday solar hours makes 0.5 GW of additional solar worth building in 2028 and avoids 1.2 GW of gas and 0.3 GW of batteries in 2038. In both, realistic event-shape limits diminish the value of curtailment. The results show that flexibility procurement and its value are driven by grid characteristics and policy objectives.

physics.soc-ph↗

arXiv2026

Actuator Disk Models reproduce Actuator Line Model power and thrust fluctuation statistics in wind farm simulations

Actuator-disk models (ADM) are widely used in wind-farm simulations, but their accuracy in reproducing power and thrust temporal fluctuation statistics has not yet been compared to the more accurate and detailed predictions of actuator-line models (ALM). This work provides a detailed comparison of such model predictions under three distinct atmospheric conditions. Data is obtained from a database (JHTDB-Wind) containing actuator-line turbine-response and time-resolved flow field data from a large-eddy simulation of a small windfarm operating over a full diurnal cycle. Power and thrust time series corresponding to ADM are constructed from disk-averaged velocity signals and compared with the corresponding more detailed actuator-line signals over three temporal windows within the diurnal cycle. The analysis compares time series, power spectral densities, and both the fluctuation and increment probability density distributions. The results show that the ADM time-series capture the dominant temporal, spectral, and statistical features of the ALM values at resolved and disk-averaged flow-field time scales, i.e. slower than the rotor frequency. Effects of temporal filtering that are often applied to ADM inputs are examined. Overall, the results provide strong support for the use of ADM for predicting power and thrust fluctuation statistics in wind-farm simulations.

physics.flu-dyn↗

arXiv2026

Wind farms as sensor arrays of turbulent boundary layer spatio-temporal flow structure

Temporal fluctuations of wind farm-generated power arise from the interaction between atmospheric turbulence, turbine properties, and wind-farm layout. However, accurately characterizing these fluctuations remains an open challenge. We here present and extend an analytical framework to predict the temporal spectrum of wind farm power-fluctuations, and compare its predictions with detailed large-eddy-simulations (LES) of a wind farm operating within a conventionally neutral boundary layer. The modeling framework assembles several established concepts from turbulent boundary layer physics: a spatio-temporal turbulence spectral model accounting for mean advection and assuming random sweeping by large eddies, a top-down wind farm model of a fully developed wind turbine array boundary layer flow providing the required mean-flow and turbulence scales, and a spatial sampling kernel representing turbine positions and finite rotor size. The latter is extended to three dimensions to represent filtering of spatial fluctuations of turbulence along the vertical direction. Using only atmospheric, turbine, and layout parameters, the model predictions are evaluated against an extensive LES database of a large wind farm on flat terrain. The model accurately predicts the aggregate power frequency spectrum, including peaks associated with advection between turbine rows, the decay of inertial-range turbulence fluctuations due to rotor averaging, and spectra of aggregate power signals from various arrangements of groups of turbines within the array (e.g. staggered or random subsets). The ability to predict wind power fluctuation spectra from fundamental fluid dynamics and existing boundary layer turbulence models could help improve wind farm grid integration.

physics.flu-dyn↗

arXiv2026

Cross-Atlantic Research Agenda for Scalable Grid Architectures and Distributed Flexibility

Electric power systems are rapidly evolving into deeply digital, cyber-physical infrastructures in which large fleets of distributed energy resources must be coordinated as system-level flexibility across multiple spatial and temporal scales. Despite growing distributed energy resource deployment, existing grid and market architectures lack scalable, interoperable mechanisms to reliably translate device-level flexibility into grid-aware services, creating risks to reliability, affordability, and resilience at high penetration. We propose that scalable and reliable coordination of distributed energy resource-based flexibility in future power systems is fundamentally an architectural problem that can be addressed through laminar cyber-physical design using minimal, standardized interoperability interfaces that link device autonomy with system-level objectives. To assess this claim, we present and discuss a layered cyber-physical systems architecture and explicate its implementation through standards-based interfaces, Flexibility Functions, hierarchical control, and case studies spanning U.S. and Danish regulatory, market, and operational contexts. Empirical evidence from New York's Grid of the Future proceedings, Danish Smart Energy Operating System pilots, and operational aggregator deployments demonstrates that such architecture enables predictable, grid-aware flexibility while preserving device autonomy, interoperability, reliability, and quality of service. These results support a cross-Atlantic research agenda centered on joint testbeds, harmonized interoperability mechanisms, and coordinated policy experiments to accelerate the deployment of resilient, scalable, and flexible clean energy systems.

eess.SY↗

arXiv2025

Surface Wave-Aerodynamic Roughness Length Model for Air-Sea Interactions

A new model to evaluate the equivalent hydrodynamic length or surface roughness, z0, of ocean waves is developed and tested. The proposed Surface Wave-Aerodynamic Roughness Length (SWARL) model requires maps of the wave surface height at consecutive times and the air flow characteristic Reynolds number as inputs. Pressure drag is accounted for by approximating the relative velocity in a frame moving with the local wave phase-speed assuming ideal inviscid ramp flow (Ayala et al. 2024). Drag from viscous and unresolved ripples is modeled using the standard equilibrium model. The SWARL model is tested using over 300 datasets for monochromatic and broad-spectrum wave surfaces. The model-predicted z0 and drag coefficients are compared to measured values, as well as commonly used wave parametrization methods found in the literature. For datasets with well-characterized surfaces, the proposed model shows significantly better agreement with data compared to prior models. For data that did not include a full characterization of the wave fields (typically field data), the model yields predictions with accuracy similar to prior models. Results highlight that including detailed flow physics and extensive wave-field characterization in the modeling of z0 can provide significant improvements in roughness-length based modeling of air-sea interactions.

physics.flu-dyn↗

arXiv2024

A Moving Surface Drag Model for LES of Wind over Waves

Numerical prediction of the interactions between wind and ocean waves is essential for climate modeling and a wide range of offshore operations. Large Eddy Simulation (LES) of the marine atmospheric boundary layer is a practical numerical predictive tool but requires parameterization of surface fluxes at the air-water interface. Current momentum flux parameterizations primarily use wave-phase adapting computational grids, incurring high computational costs, or use an equilibrium model based on Monin-Obukhov similarity theory for rough surfaces that cannot resolve wave phase information. To include wave phase-resolving physics at a cost similar to the equilibrium model, the Moving Surface Drag (MOSD) model is introduced. It assumes ideal airflow over locally piece-wise planar representations of moving water wave surfaces. Horizontally unresolved interactions are still modeled using the equilibrium model. Validation against experimental and numerical datasets with known monochromatic waves demonstrates the robustness and accuracy of the model in representing wave-induced impacts on mean velocity and Reynolds stress profiles. The model is formulated to be applicable to a broad range of wave fields and its ability to represent cross-swell and multiple wavelength cases is illustrated. Additionally, the model is applied to LES of a laboratory-scale fixed-bottom offshore wind turbine model, and the results are compared with wind tunnel experimental data. The LES with the MOSD model shows good agreement in wind-wave-wake interactions and phase-dependent physics at a low computational cost. The model's simplicity and minimal computational needs make it valuable for studying turbulent atmospheric-scale flows over the sea, particularly in offshore wind energy research.

physics.flu-dyn↗

arXiv2018

A Framework for Input-Output Analysis of Wall-Bounded Shear Flows

We propose a framework to understand input-output amplification properties of non- linear partial differential equation (PDE) models of wall-bounded shear flows, which are spatially invariant in one coordinate (e.g., streamwise-constant plane Couette flow). Our methodology is based on the notion of dissipation inequalities in control theory. In particular, we consider flows with body and other forcings, for which we study the input- to-output properties, including energy growth, worst-case disturbance amplification, and stability to persistent disturbances. The proposed method can be applied to a large class of flow configurations as long as the base flow is described by a polynomial. This includes many examples in both channel flows and pipe flows, e.g., plane Couette flow, and Hagen-Poiseuille flow. The methodology we use is numerically implemented as the solution of a (convex) optimization problem. We use the framework to study input-output amplification mechanisms in rotating Couette flow, plane Couette flow, plane Poiseuille flow, and Hagen-Poiseuille flow. In addition to showing that the application of the proposed framework leads to results that are consistent with theoretical and experimental amplification scalings obtained in the literature through linearization around the base flow, we demonstrate that the stability bounds to persistent forcings can be used as a means to predict transition to turbulence in wall-bounded shear flows.

physics.flu-dyn↗