Performance evaluation of a floating lidar buoy in nearshore conditions
This work provides a signal-processing and statistical-error analysis methodology to assess key performance indicators for a floating Doppler wind lidar. The study introduces the raw-to-clean data processing chain, error assessment indicators and key performance indicators, as well as two filtering...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/105706 |
| Acesso em linha: | https://hdl.handle.net/2117/105706 https://dx.doi.org/10.1002/we.2118 |
| Access Level: | acceso abierto |
| Palavra-chave: | Remote sensing Doppler wind lidar Offshore wind farm Resource assessment Turbulence Signal processing Teledetecció Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció |
| Resumo: | This work provides a signal-processing and statistical-error analysis methodology to assess key performance indicators for a floating Doppler wind lidar. The study introduces the raw-to-clean data processing chain, error assessment indicators and key performance indicators, as well as two filtering methods at post-processing level to alleviate the impact of angular motion and spatial variability of the wind flow on the performance indicators. Towards this aim, the study mainly revisits horizontal wind speed (HWS) and turbulence intensity measurements with a floating ZephIR 300 lidar buoy during a 38 day nearshore test campaign in Pont del Petroli (Barcelona). Typical day cases along with overall statistics for the whole campaign are discussed to illustrate the methodology and processing tools developed. |
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