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In recent years, floating lidar systems (FLS) have been used in increasing numbers for project planning and design of offshore wind farm projects. To assess the quality of the measured data or the wind resources, an exact knowledge of the measurement uncertainty of the FLS is important. However, this is difficult because there is usually no reference measurement system at the offshore sites where FLSs are to be used to assess wind resources. In order to estimate the quality of the measurements or the measurement uncertainty for a site without a reference measurement system, in this case only measurement uncertainties from measurement campaigns or trial campaigns that have already been carried out can be used. However, the respective wind and wave conditions differ from location to location. In this respect, a direct transfer of the measurement uncertainty from one measurement location to another location is again subject to a certain uncertainty. In this paper, we explore the possibilities of a different, simulation-based, approach. First, we discuss which parts of the measurement uncertainty of the FLS can be investigated in the context of simulations. Additionally, we present a workflow for the simulation of an FLS for different wind and wave conditions and an approach to determine and compare the simulated bin-averaged deviations for these conditions with real measurement data. Finally, we show a comparison of the simulated uncertainties with measurement uncertainties determined during a six-month measurement campaign of an FLS against an offshore measurement mast and a fixed reference lidar and give an outlook on possible further use cases of this simulation-based methodology.

Floating lidar system (FLS) measurements are essential for offshore site assessment. Here an important part is the data accuracy and uncertainty, which are determined by the wind speed deviations between the FLS and reference data obtained during a verification trial. The reference anemometer is normally a cup anemometer installed on a met mast. Due to the different measurement principles, mast wake effects, the distance between FLS and reference, and FLS motions, the share of these factors in the deviations are not clear. In this work, we present an FLS verification measurement conducted in proximity to the FINO3 met mast located in the North Sea in 2017. Additionally, the data acquired by a fixed, non-moving lidar installed on FINO3 is considered. This allows studying wind speed deviations with different, well-defined influence factors. Methods for analyzing the wind speed accuracy and uncertainty, which are used in FLS verification and classification, are presented and applied to all combinations of data sources. As a preliminary work, directional wind speed deviations are studied to define a valid wind direction sector used for filtering for all data sources. As a result, the wind speed deviations between the FLS and the references are dominated by the FLS motion and the distance to the reference, respectively. Nevertheless, uncertainties may also be seen for the fixed lidar. For the classification results, approximately 1/3 of the sensitivity is contributed by the different measurement principles.

This paper sheds new light on the assessment of firm networks via multiple directorships in terms of corporate firm performance. Using a large sample of European listed firms in the period from 2003 to 2011 and system GMM we find a significant compensation effect on corporate firm performance for the initial negative effect of horizontal multiple directorships by product market competition. In markets with effective competition, horizontal multiple directorships turn out to be an efficient mechanism to increase firm performance and thus assure competitive advantages. By contrast, linkages between up- and downstream firms have no significant influence on financial performance, irrespective of the level of competition intensity.