14:30 - 16:00 LIDARs - the zapping competition
Resource assessment
![Onshore Onshore](onshore-neg.png)
![Offshore Offshore](offshore-neg.png)
Room: Hall G2
In this highly interactive quick-fire session, participants will scan through 14 LIDAR-related presentations and vote to select the three contributions they would like to hear in full. Presentations will cover a wide range of possible LIDAR applications, both offshore and onshore, such as power-curve validation, resource assessment in complex terrain, turbulence intensity measurements, and more.
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Learning objectives
Get a wide overview of the latest research and field work involving LIDARs, both onshore and offshore.
This session will be chaired by:
![](../submit-an-abstract/thumb/ADMIN_15Courtney,_Mike_2015.jpg)
![](../submit-an-abstract/thumb/ADMIN_507Landberg_Lars.jpg)
![](../submit-an-abstract/thumb/ADMIN_506Ivanell_Stephan.jpg)
Presenter
![](../submit-an-abstract/thumb/18x.jpg)
Co-authors:
Megan Smith (1) F
(1) Carbon Trust, London, United Kingdom (2) RES Offshore, London, United Kingdom
Presenter's biography
Biographies are supplied directly by presenters at WindEurope Summit 2016 and are published here uneditedMichael is an Associate in the Offshore Wind team at the Carbon Trust. He manages the Wakes and Wind Resource, and Foundations Research Areas of the Offshore Wind Accelerator.
Prior to joining the Carbon Trust, Michael worked for a number of years on the consent application for the Dogger Bank Offshore Wind Farms focusing on offshore environmental impacts, and more recently project managed the construction of onshore wind farms in England.
Michael holds a degree in Renewable Energy from the University of Exeter.
Abstract
Power curve validation using LIDAR
Introduction
The OWA Power Curve Validation using LiDAR project aims to assess the effectives of performing LiDAR based power curve measurement offshore. A total of 10 LiDAR power curve analyses will be presented spanning multiple LiDAR technologies; Nacelle LiDAR, Scanning LiDAR and Floating LiDAR. Three of the LiDAR datasets have concurrent meteorological masts available for comparison (of which two are fully IEC compliant). The study represents a unique overview of the current state of the art in power curve measurement with LiDAR.
Approach
Collecting data from a range of OWA partners and 10 different sites, including floating, scanning, and nacelle LIDAR data sources, the OWA engaged RES offshore to analyse the data and draw conclusions on the efficacy of using these technologies for power curve validation.
Main body of abstract
Results from all 10 data sets will be presented and conclusions will be drawn regarding the capability of LiDAR to perform contractual power curve measurements in the absence of expensive offshore met masts. The implications for the uncertainty assigned to Offshore LiDAR based power curve measurements will be discussed and recommendations on LiDAR deployment configuration will also be made.
The LiDAR data is further explored to enable improvements in turbine performance modelling. For each power curve test a parametric study of the dataset is conducted to characterise the sensitivity of power deviation against each signal in the dataset (air density, turbulence, shear, inflow angle, etc.). This reveals the parameters which have the most significant relationship with real world power deviations. These observed deviations are compared to theoretical expectations from advanced turbine performance models and the effectiveness of industry standard correction methods (IEC air density and turbulence corrections, REWS correction, inflow angle correction) is evaluated. This insight into the performance of turbines in a broad variety of wind conditions provides valuable input for model development.
Conclusion
LIDAR has the capability to be used as a significantly cheaper and more flexible alternative in place of met masts to undertake power curve verification tests. The presentation will discuss the implications and practical considerations when undertaking these tests based on direct experience.
Learning objectives
Delegates will better understand the viability of lidar in place of met masts with respect to power curve validation tests.
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