Incorporation of the Rotor-Equivalent Wind Speed into the Weather Research and Forecasting Model’s Wind Farm Parameterization

Abstract

Wind power installations have been increasing in recent years. Because wind turbines can influence local wind speeds, temperatures, and surface fluxes, weather forecasting models should consider their effects. Wind farm parameterizations do currently exist for numerical weather prediction models. They generally consider two turbine impacts: elevated drag in the region of the wind turbine rotor disk and increased turbulent kinetic energy production. The wind farm parameterization available in the Weather Research and Forecasting (WRF) Model calculates this drag and TKE as a function of hub-height wind speed. However, recent work has suggested that integrating momentum over the entire rotor disk [via a rotor-equivalent wind speed (REWS)] is more appropriate, especially for cases with high wind shear. In this study, we implement the REWS in the WRF wind farm parameterization and evaluate its impacts in an idealized environment, with varying amounts of wind speed shear and wind directional veer. Specifically, we evaluate three separate cases: neutral stability with low wind shear, high stability with high wind shear, and high stability with nonlinear wind shear. For most situations, use of the REWS with the wind farm parameterization has marginal impacts on model forecasts. However, for scenarios with highly nonlinear wind shear, the REWS can significantly affect results.

Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)

“…2). In Siedersleben et al (2018a, b), we obtained best results using a horizontal grid size of 1.67 km.…”

“…We use two different sets of vertical levels. The default configuration corresponds to that of Siedersleben et al (2018a, b) with a vertical spacing of 35 m in the lowest 200 m and increasing to 100 m at 1000 m above mean sea level (a.m.s.l. ), corresponding to one vertical level below the rotor area and three within the rotor area for the wind turbine type installed at the MSO and ONO wind farms (case study I; Fig.…”

Simulated wind farm wake sensitivity to configuration choices in the Weather Research and Forecasting model version 3.8.1

“…We simulate each 24-hour day of August 24 through 27 individually, beginning spin-up at 1200 UTC on the previous day with analysis retained after 0000 UTC. We define the wake effect by comparing a simulation without the WFP to a simulation with the WFP, as in Fitch et al (2012); Lee and Lundquist (2017a); Redfern et al (2019). We use the power and thrust curve of the 1.5-MW PSU generic turbine (Schmitz, 2012) to parameterize the wind turbines, based on the General Electric SLE turbine (80-m hub height and 77-m rotor diameter).…”

Observed and simulated turbulent kinetic energy (WRF 3.8.1) overlarge offshore wind farms

“…Equation 1is formulated for a Cartesian coordinate system with the indexes i, j, k corresponding to the directions x, y, z, that in turn is equal to the geographic directions West-East, South-North, and the vertical axis with k=0 the level closest to the ground. The variable N ij describes the number of wind turbines within a grid cell i, j; V ij is the horizontal wind speed at hub height at grid cell ij (Redfern et al (2019) showed that during strong shear events rotor-equivalent wind speed result in a different change in 5 TKE). A ikj is the rotor area between the two vertical levels k and k + 1, at a height z k and z k+1 , and V H the horizontal wind speed at hub height.…”