ESR 2

The aim of ESR2 project is to develop a very-short term wind field forecast to improve wind farm operation, increase the efficiency of the energy production within a windfarm and subsequently the grid stability, based on an experimental approach with a forecast horizon up to 30 minutes.

Sudden wind speed fluctuations, together with even relatively small variations in the wind direction may lead to strong wind power fluctuations of up to -50% and/ or high structural loads on downstream turbines if these turbines are operating in multiple wake conditions. ESR 2 will focus first, on characterizing the impact that uncertain forecasts of wind speed and wind direction have on the power variation of large offshore wind farms.

As electricity supply must meet electricity demand at any time, fluctuations in wind energy output affect supply reliability and power quality of the grid. On the short time scale, depending on the volume of wind power in the grid, the generation mix and the long-distance transmission capacity, variability of wind power significantly impacts the grid stability. The fellow candidate ESR2 will develop strategies, which finally may face the grid stability when wind power generation varies, by means of very-short term wind forecast based on precise wind inflow measurements by applied remote sensing with a forecast horizon of up to 30 minutes. Based on the pool of experimental LiDAR data different objectives are pursued, such as study on the deterministic behaviour of the potentially heterogenic inflow of a wind farm or systematic analysis of the accuracy of the LiDAR system over long distances in cooperation with the academic partner entity.

Industrial

DONG Energy
Schedule: August – December 2017

Academic

Technical University of Denmark (DTU)
Schedule: September 2016 – January 2017

• L Valldecabres, W Friedrichs, L von Bremen and M Kühn (2016) Spatial-temporal analysis of coherent offshore wind field structures measured by scanning Doppler-lidar, Journal of Physics: Conference Series, 753(072028), DOI: 10.1088/1742-6596/753/7/072028 Full text: http://iopscience.iop.org/article/10.1088/1742-6596/753/7/072028

• Elena Gonzalez, Emmanouil M. Nanos, Helene Seyr, Laura Valldecabres, Nurseda Y. Yürüşen, Ursula Smolka, Michael Muskulus, Julio J. Melero, Key Performance Indicators for Wind Farm Operation and Maintenance, Energy Procedia, Volume 137, 2017, Pages 559-570, https://doi.org/10.1016/j.egypro.2017.10.385.

• L Valldecabres, W Friedrichs, L von Bremen and M Kühn (2016) Analysis of Wind Field Fluctuations on Wind Farm Power Output, 12th EAWE PhD Seminar on Wind Energy in Europe. Oral presentation.

• Valldecabres, A. Peña, M. Courtney, L. von Bremen and M. Kühn. Very short-term wind speed forecast of coastal flow by dual-Doppler scanning lidar. WESC 2017, DTU, Copenhagen, Denmark. Oral presentation.

• Valldecabres, L., Steinfeld, G., Trujillo, J.-J., von Bremen, L., Kühn, M., Optimizing LIDAR measurements for very short-term power forecasting using a LIDAR simulator, EAWE PhD Seminar, Cranfield, United Kingdom, 2017. Poster presentation.

• Valldecabres, L., Steinfeld, G., von Bremen, L., Kühn, M., Very short-term wind power forecasting using remote sensing data: Experiments with a Lidar simulator.  Ninth Conference on Weather, Climate and the New Energy Economy, 98th AMS meeting, Austin, Texas, 2018.  Oral presentation.