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Delegates are invited to meet and discuss with the poster presenters during the poster presentation sessions between 10:30-11:30 and 16:00-17:00 on Thursday, 19 November 2015.

Lead Session Chair:
Stephan Barth, ForWind - Center for Wind Energy Research, Germany
Detlef Stein DNV GL, Germany
Co-authors:
Detlef Stein (1) F Hans Cleijne (2) Simon Cox (3) Brieuc Pey (4)
(1) DNV GL, Hamburg, Germany (2) DNV GL, Arnhem, The Netherlands (3) DNV GL, Bristol, United Kingdom (4) DNV GL, Paris, France

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Presenter's biography

Biographies are supplied directly by presenters at EWEA 2015 and are published here unedited

Detlef Stein: Ocean physicist, diploma degree University of Kiel, Germany. Since 2002 with DNV GL (legacy GL Garrad Hassan). Global Head of Resource Measurements, Deputy Head of Section Offshore/Hamburg, Principal Offshore Consultant, Remote Sensing Expert, Senior Researcher. Assignments to wind resource measurements, power performance tests and offshore site assessments. Technical O&M of offshore wind research platform FINO1 in North Sea and FINO2 in the Baltic Sea. Execution of wind measurements on FINO3-Mast, North Sea. Since 2003 development and execution of Remote Sensing (LiDAR/SoDAR) measurement strategies. Expert for fixed and floating LiDAR solutions and Remote Sensing on- and offshore device validations.


Poster

Poster Download poster (12.90 MB)

Abstract

Offshore Wind Resource Assessments using Floating Lidar Systems as main Source of Finance relevant Wind Data: Practical Aspects and Expected Wind Data Uncertainty

Introduction

An alternative to expensive offshore met masts is to employ Floating LiDAR technology. The layout of an Offshore Wind Resource Assessment (OWRA) campaign based on Floating Lidar System (FLS) measurements to be uses as primary source of data for Energy Production Assessments will be presented. Practical aspects of a FLS deployment and expected uncertainties of FLS wind data will be discussed together with implications on offshore wind farm financing aspects.

Approach

To use Floating LiDAR Systems as the main source of wind data for finance relevant wind resource and energy productions assessments.

Main body of abstract

Ground based LiDAR systems are nowadays frequently used for e.g. onshore wind resource assessment, although generally in simple terrain and/or in conjunction with a met mast. As a subsequence buoy-mounted variants for offshore use have been developed in the past few years. Such floating system may substantially be cheaper to deploy offshore than met masts and can be relocated to address spatial variation of resource across a site. Mounting existing fixed deployment proven Wind LiDAR technology on buoys introduces additional uncertainties (e.g. by the moving sea surface) in the data produced, creating challenges for reliability, maintainability and power management. Implications on uncertainty for energy production predictions need strong attention. Similar to conventional anemometry, uncertainty can be reduced through selection of well-established units with proven track-records and by specification of suitable calibration and mounting arrangements. It is particularly crucial to perform a thorough planning of the OWRA campaign from Lidar unit and complete FLS performance verification through proper site selection to commissioning and operation at the projected offshore wind farm site. A typical layout of an OWRA campaign employing FLS measurements as primary source of data will be presented based on recent cases of real offshore deployments. Expected uncertainties from FLS data will be put into context with other typical wind data sources like offshore wind atlas and weather model data, publically available metrological data including high quality tall offshore masts and weather service measurements, possibly completed by new installations of fixed platform mounted Lidars or even hub height offshore metrological mast. Related cost implications and potential benefits with respect to more accurate calculations of the annual energy production, hence lower risk surplus and therefore lower cost of capital for an offshore wind farm will be discussed.

Conclusion

Recent wind resource assessments campaigns for offshore wind farm projects based on thouroughly planned Floating Lidar deployments have yielded very encouraging results. The related wind data uncertainty estimates suggest potential benefits over classical expensive onsite anemometry with regards to accuracy of the annual energy production, leading to a lower risk surplus and therefore lower cost of capital for the project.


Learning objectives
To get an idea of the technical care be taken, environmental challenges and potential benefits over classical anemometry when using Floating Lidar System for finance relevant wind resource assessment purposes.