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Conference programme 

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Poster session

Lead Session Chair:
Stephan Barth, Managing Director, ForWind - Center for Wind Energy Research, Germany
Steve McCarthy SgurrEnergy Ltd, United Kingdom
Co-authors:

(1) SgurrEnergy Ltd, Glasgow, United Kingdom

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Poster
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Abstract

Lidar use cases for the acquisition of high value data sets

Introduction

Remote sensing in general and lidar in particular have made available a much more extensive set of measurement techniques than were previously utilised by offshore wind power professionals. These allow wind conditions to be characterized in much more details and with much more accuracy than was previously possible.

Exploiting these new opportunities as effectively as possible requires a structured approach to the design of measurement campaigns involving lidar to ensure high value data are acquired. If lidar is only used to fulfil requirements previously met by more limited instrumentation then the full value offered by lidar will not be realised.


Approach

Unnecessary limitations in the value of lidar data can be avoided by considering lidar use cases when designing measurement campaigns.

Main body of abstract

The International Energy Agency (IEA) Wind Energy Task 32 has been set up to capture and codify the wind industry’s experience and expertise with respect to the use of lidar in wind power applications.

Key work packages within this task have adopted a lidar use case framework as the basis for describing the multiplicity of lidar techniques available. This framework looks at
• The combination of the lidar methods being employed,
• The data requirements that can be fulfilled using the data sets these methods make available, and
• The situations and sets of circumstances in which the performance of these procedures can be verified in terms of measurement accuracy.

A valid lidar use case entails the implementation of a method where
• The accuracy of the data is understood under the circumstances in which the method is used and
• The data set fulfils a purpose or requirement that arises sensibly in the context of the broader project aims and objectives

As a result it should be possible to calculate a quantifiable return on investment and integrate the acquisition of the data into financial models with greater transparency.


Conclusion

When designing a lidar campaign consider:

1. The data requirements
a. What does my project need? What question am I asking?
b. Can I quantify the benefit of fulfilling these requirements?

2. The lidar method
a. Have I adequately documented the measurement procedure?
b. Does the method answer my question and fulfil my data requirements?

3. And the situation in which the measurements are made
a. Do I understand the accuracy of the method under the circumstances in which it is used? Is it sufficient?
b. Can I do a complete and unbiased uncertainty analysis?



Learning objectives
1. Select the appropriate lidar measurement methodology for a given project data requirement with reference to the circumstances under which the data are being acquired

2. Define a complete, unbiased, open and transparent approach to measurement uncertainty with respect to lidar measurements such that IEA bankability requirements are met

3. Undertake offshore measurements that enable fuller characterisation of the complex offshore wind conditions that impact the productivity and longevity of offshore wind power assets