## 9 Conclusions  
The IEA Wind Task 32 workshop \"Optimizing Lidar Design for Wind Turbine Control Applications\" made it clear that there is no single metric that can determine whether a lidar is optimal for control purposes. Indeed, workshop participants had different views of what it means to optimize a lidar for control purposes. Instead, several objectives must be achieved to arrive at an optimal lidar for control purposes, including availability, reliability, measurement accuracy, and system cost. A review of the literature on lidar optimization for control applications revealed a large body of work on the optimization of lidar scan patterns via the resulting controller performance, time domain assessments of measurement accuracy, and direct frequency domain calculations of measurement coherence and measurement error. More practical aspects of lidar optimization have been treated as well, including the determination of availability requirements through feedforward control simulations as well as analyses of how the lidar beam angle, mounting position on the nacelle, and sampling time affect measurement availability. Presentations and group discussions at the workshop, augmented by additional input from the authors, reveal a number of practical barriers preventing the widespread use of lidars for control. Some of the main barriers related to the lidar system are:  
* High lidar measurement availability is necessary to maximize the value creation of lidar-assisted control (LAC). However, due to weather and atmospheric conditions, 100% availability cannot be achieved. * Lidar reliability is seen as a potential problem. Again, the value creation depends heavily on the ability of the lidar to function properly when needed. * Difficulty in assessing the cost-benefit relationship for LAC. * The lack of common guidelines for assessing lidar applicability to LAC. * The need to bring theoretical knowledge from the research community and practical requirements from industry into accordance. Proposed solutions to these barriers include:
* Lidars that can adapt to changing measurement quality to increase availability. For example, a lidar could switch to shorter measurement ranges when poor atmospheric conditions make measuring at the ideal preview distance impossible. * Reducing the amount of lidar downtime due to reliability issues by developing a regular maintenance plan involving modular lidar components. * Using a systems engineering approach to improve the understanding of the cost-benefit relationship of LAC, where the complexity of the lidar system can be optimized. * The creation of common documents providing guidelines for evaluating LAC performance and defining variables such as availability. The recent IEA Wind Task 32 workshop\"Certification of Lidar-Assisted Control Applications\" served as a first step in this direction. * Perhaps most importantly, further collaboration between the research community and industry is needed to ensure that common goals are being targeted and the latest methods are being employed. Scan pattern optimization was analyzed from a theoretical perspective by using frequency domain methods from the literature to directly calculate mean square rotor effective wind speed measurement error and measurement coherence bandwidth for various continuous wave and pulsed lidar scenarios. The models were extended in this paper to include the direct calculation of mean square generator speed error for a simple feedforward control scenario. This paper only considered scan pattern optimization for rotor effective wind speed. In general, the optimal configurations for measuring shear or wind direction are different. The main conclusions from the frequency domain optimization are:  
* In general, measurement locations should approximate a rotor disk average. Line-of-sight errors penalize large cone angles and errors from wind evolution penalize long preview distances. * As the number of beams increases, measurement/generator speed error decreases.