The RW-Turb (Rainfall, Wind and Turbulence) project was recently funded by the French National Research Agency.
Few studies showed that the effects of rainfall (rain rate and drop size distribution –DSD-) on wind turbine efficiency are significant, but have surprisingly received little attention. The main
goal of WR-Turb is to overcome the current lack of knowledge on this topic through a collaboration between an academic institution (the Hydrology, Meteorology and Complexity laboratory – HM&Co https://hmco.enpc.fr/- of Ecole des Ponts ParisTech) and a wind power production firm (Boralex). A wider consortium including Centrale Nantes (France), Univ. Oldenburg (Germany) and NERL (USA) is also involved.
Literature review shows that: (i) wind turbulence is a complex feature requiring appropriate framework such as Universal Multifractals (UM, a parsimonious framework that enables to quantify the variability across scales of fields extremely variable across wide range of scales) for analysis and simulations; and intermittency of the input power is further propagating to the wind turbine and power output; (ii) Rainfall also exhibits scale invariant multifractal features. WR-Turb will combine the existing knowledge on wind turbulence and rainfall fields to create a coupled framework enabling to tackle its objectives. Two distinct aspects will be studied: first the rainfall effect on the wind energy resources notably taking into account its non Gaussian extreme small spatio-temporal scale fluctuations and second the rainfall effect on the conversion process of wind power to electric power by the wind turbine.
A scientific programme to be primarily implemented through two PhD projects was designed:
– WP 1: Experimental set-up and data collection.
– WP 2: Analysis and simulation of rainfall effects on the wind power available.
– WP 3: Analysis and simulation of rainfall effects on energy conversion by wind turbine.
The share of renewable energy is rapidly growing in France and Europe. Hence it is highly relevant to understand the uncertainty affecting the electricity production by such resources, notably because its intermittent nature raises complex challenges in terms of grid management. WR-Turb will have a strong impact on this field by providing a quantification of rainfall effects of wind power production and opening perspectives for improving nowcasts. Results will be up-scalable to other site because they will mainly be event-based. The novel findings of WR-Turb, which will be disseminated to both the scientific and professional community, will also open the path for future investigations.
Description du poste
- The PhD #1 will focus on the measurement campaign and data analysis. More precisely, PhD #1 will:
– create a user friendly data base and carefully validate the data collected from an observatory for combined high resolution measurements of wind (speed, direction, shear and turbulence), rainfall (DSD, and fall velocities) and power production that will be installed for 2 years on a wind farm operated by Boralex and having a 86 m meteo mast.
– analyse mainly with UM tools the collected data to quantify the influence of rainfall conditions on wind turbulence and air density. A classification of rainfall events will be designed for this purpose. Interpretation will require the development of innovative models. A new 3+1D model of drop fields in a 3D turbulent wind at wind turbine scale will be also developed.
– analyse the data collected to quantify the transfer of wind intermittency to power production, primarily through a joint multifractal analysis that will require the development of innovative tools.
Supervisers : Daniel Schertzer and Auguste Gires (HM&Co-ENPC)
- PhD#2 will focus on numerical simulations. More precisely, PhD#2 will:
– improve existing tools based on continuous UM cascades to create numerical simulations of scalar and vector spatio-temporal wind fields for scales ranging from few cm to wind turbine size over few tens of seconds. Comparison with state of the art models will be carried out.
– develop two numerical modelling chains with increasing complexity to simulate and quantify the effect of wind turbulence on power production. The wind fields simulated in WP2 will be used (i) to compute available torque fluctuations, and (2) as input in a multi-disciplinary model for numerical simulation of wind turbine behaviour (the FAST – TurbSim modelling chain developed by the NERL – US https://nwtc.nrel.gov/FAST will be used as basis). Ensembles of possible inputs will be used to quantify the sensitivity of the modelling chains to various input parameters corresponding to the different rainfall conditions.
Supervisers : Ioulia Tchiguirinskaia and Auguste Gires (HM&Co-ENPC)
Co-supervisor: Pr Sandrine Aubrun (Laboratory on Hydrodynamics, Energetics and Atmospheric
Environment – Centrale Nantes / CNRS UMR6598)
Modalités de candidature
If interested by one of the PhD projects : please contact email@example.com with CV and cover letter