Optimize wind farm performance by delivering accurate shortest-term wind and power forecasts

The aim of this project is to deliver accurate wind power production forecasts for wind turbines and wind flow predictions around the turbines for the next minutes and up to several hours ahead. Some years ago wind farm owners did not have very good insight into the high resolution data sets about power performance and actual turbine state. In recent years this has changed and more and more wind farm management software products are developed which help the wind farm owner to understand what is going on in his wind farm. Beside of only monitoring the actual turbine state the operators are now also interested in controlling the wind farm and to understand if they could improve the performance of their wind farm. Wind farm operators use shortest-term forecasts like they are developed in this project for optimizing the wind farm performance, to balance the energy in the electrical grid and to trade the energy. Not only the power is of interest for the wind farm operator but also the flow field around the turbines which causes loads on the turbines and can lead to damages on the turbine blades. Using the technique which will be developed under this project to deliver a flow field prediction for the next minutes can help the operator to understand what is going on in his wind farm. The result of the project will be software that delivers forecast services for the next minutes and hours of power production for individual turbines and wind flow characteristics for the complete wind farm.

The aim of this project is to deliver accurate wind power production forecasts for wind turbines and wind flow predictions around the turbines for the next minutes and up to several hours ahead. A coupling between numerical weather prediction models (NWP), advanced measurements, Artificial Neural Network (ANN) techniques and computational fluid dynamics (CFD) are used in a new way to deliver this shortest-term forecast. Some years ago wind farm owners did not have very good insight into the high resolution data sets about power performance and actual turbine state. In recent years this has changed and more and more wind farm management software products are developed which help the wind farm owner to understand what is going on in his wind farm. Beside of only monitoring the actual turbine state the operators are now also interested in controlling the wind farm and to understand if they could improve the performance of their wind farm. Wind farm operators use shortest-term forecasts like they are developed in this project for optimizing the wind farm performance, to balance the energy in the electrical grid and to trade the energy. Not only the power is of interest for the wind farm operator but also the flow field around the turbines which causes loads on the turbines and can lead to fatigue of the blades. Using NWP, CFD and advanced measurements to deliver a flow field prediction for the next minutes can help the operator to take actions and change e.g. the angle of the blades to decrease the loads. The result of the project will be software that delivers forecast services for the next minutes and hours of power production for individual turbines and wind flow characteristics for the complete wind farm.