The challenges that arise when using a lidar are not always specific to one application area. Filtering lidar raw data is a good example – it needs to be accomplished whether the data is supposed to be used for turbine control or a power performance test. In addition, new developments within lidar research lead to new application areas such as using long-range lidars for wind power forecasting. Also initiatives such as OpenLidar have been formed in the last years that strive for a collaborative platform to develop the architecture of an open-source remote wind sensing lidar.
Therefore this fifth “application area” deals with all topics concerning the use of lidar that do not fit in a box. The objective is to leverage new ideas and developments that help to overcome barriers to the use of lidar for wind energy applications.
Objectives
- Discuss and find solutions to barriers that are common to all application areas.
- Leverage new ideas and developments that help to overcome barriers to the use of lidar for wind energy applications.
The cross-cutting nature of lidar challenges means that solutions developed in one application area often benefit others. Raw data filtering, for instance, is a fundamental step whether the lidar is deployed for turbine control, power performance assessment, or loads verification. As lidar technology matures, new applications continue to emerge, such as using long-range systems for wind power forecasting, which require novel approaches to data handling and uncertainty quantification. Collaborative initiatives that promote open-source architecture for remote wind sensing lidar help accelerate progress by pooling expertise across institutional and national boundaries. This sharing of knowledge and tools ultimately strengthens the entire wind energy community's ability to deploy lidar systems more effectively and confidently.