Posters - WindEurope Annual Event 2025

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Putting wind at the heart of Europe’s competitiveness Scale up, Electrify, Deliver
Putting wind at the heart of Europe’s competitiveness

Posters

Come meet the poster presenters to ask them questions and discuss their work

We would like to invite you to come and see the posters at our upcoming conference. The posters will showcase a diverse range of research topics, and will give delegates an opportunity to engage with the authors and learn more about their work. Whether you are a seasoned researcher or simply curious about the latest developments in your field, we believe that the posters will offer something of interest to everyone. So please join us at the conference and take advantage of this opportunity to learn and engage with your peers in industry and the academic community.

On 9 April at 17:15, we’ll also hold the main poster session and distinguish the 7 best posters of this year’s edition with our traditional Poster Awards Ceremony. Join us at the poster area to cheer and meet the laureates, and enjoy some drinks with all poster presenters!

We look forward to seeing you there!

PO109: Turbulence intensity estimation using MPAS via two methods and comparison with WRF/measurements

Eric Tromeur, Director Research, Innovation, Service and Expertise, Meteodyn

Abstract

The Model for Prediction Across Scales - Atmosphere (MPAS-A) is a fully-compressible, non-hydrostatic atmospheric model ideal for flexible and accurate weather and climate simulations. It uses a generalized terrain-following height coordinate and supports unstructured variable-resolution meshes, making it particularly effective for complex terrains. Turbulence intensity (TI) directly affects wind speed variability, impacting turbine energy capture efficiency and overall power generation. Accurate TI forecasting is crucial for optimizing wind turbine placement and determining the suitability of wind farm sites, balancing energy output and maintenance costs. This study compares the accuracy of TI simulations between MPAS-A and WRF using two methods: the traditional turbulence kinetic energy (TKE) method and the Kaimal model. The Kaimal model is an empirical approach used to describe turbulence spectra in the atmospheric boundary layer, detailing how turbulence energy is distributed across frequencies. An 11-month simulation was conducted at the Gaolong Mountain wind farm in Jiangxi Province, China, using observational data from an 80m meteorological mast. The results show that MPAS-A, when paired with the Kaimal model, outperforms WRF in accurately simulating TI at this wind farm, highlighting its potential for improved wind resource evaluation in complex terrains.

No recording available for this poster.


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