A One‐Year‐Long Evaluation of a Wind‐Farm Parameterization in HARMONIE‐AROME

Abstract

The need to mitigate climate change will boost the demand for renewable energy and lead to more wind turbines both on‐ and offshore. In the near future, the effect these wind farms have on the atmosphere can no longer be neglected. In numerical weather prediction models wind‐farm parameterisations (WFP) can be used to model the effect of wind farms on the atmosphere. There are different modeling approaches, but the parameterization developed by Fitch et al. (2012) is mostly used in previous studies. It models the wind farm as a momentum sink and a source of power production and turbulent kinetic energy. In this paper, we have implemented the Fitch et al. (2012) WFP into HARMONIE‐AROME, the numerical weather prediction model that is currently used by at least 11 national weather services in Europe. We used HARMONIE‐AROME to make year‐long simulations for 2016 with and without the WFP. The results were extensively evaluated using lidar, tower and flight measurements at several locations near wind farms. Including the WFP reduces the model bias for wind speed near offshore wind farms. Wind farms not only affect wind, but also temperature and humidity, especially during stable atmospheric conditions: the enhanced mixing caused by the wind turbines reduces the stratification of temperature and humidity. Including the WFP in HARMONIE‐AROME results in a more realistic representation of the atmosphere near wind farms and makes it a more future‐proof model for weather forecasting.

An analytical model of momentum availability for predicting large wind farm power

“…The sub-problems are coupled together using the conservation of momentum. As farms become larger, one of the grand challenges facing the wind energy community is to understand the impact of farm-atmosphere interaction (Veers et al 2019). Kirby, Nishino & Dunstan (2022) confirmed this by performing large-eddy simulations (LES) of 50 different periodic turbine layouts.…”

“…However, this approach would be too computationally expensive for wind farm optimisation unless a sufficiently long set of twin NWP simulations (such as those reported by van Stratum et al. 2022) has already been conducted for candidate wind farm sites.…”

“…Wind energy is a key technology for the renewable energy transition. To meet future energy demands, wind energy capacity will need to increase rapidly, and individual farms will likely become larger (Veers et al 2022). A key aspect for designing wind farms is predicting their power output.…”

“…Recent studies by Patel, Dunstan & Nishino (2021) and Legris et al (2023) used 'twin' numerical weather prediction (NWP) simulations to calculate the momentum availability and thus predict how farm-scale losses (including the so-called farm blockage losses) change with atmospheric conditions. However, this approach would be too computationally expensive for wind farm optimisation unless a sufficiently long set of twin NWP simulations (such as those reported by van Stratum et al 2022) has already been conducted for candidate wind farm sites.…”