Conference programme

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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
Konstantinos Gkarakis HWEA/TEI Athens, Greece
Konstantinos Loukidis (1) F
(1) ENTEKA SA, Athens, Greece

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Presenter's biography

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

Konstantinos Gkarakis graduated from the Technological Educational Institute of Athens (TEI Athens) and has Master Science in Energy from Heriot Watt University in Scotland. His employment experience included the Umweltkontor Hellas, WRE Energy, Acciona Energiaki, Elica (Copelouzos - Samaras Group of Companies), AirEnergy, Intracom Constructions. His special fields of interest include wind resource - energy estimations in wind energy projects and wind energy plants development. Now, he is free-lancer wind engineer and wind energy expert for the control of wind measurement laboratories in Hellenic Accreditation System S.A. Also, he is scientific associate in RES Lab, Energy Technology Department, in TEI Athens.


Poster Download poster (25.92 MB)


Finance grade wind measurements with masts and lidars in complex terrain


On site wind speed measurements constitute a major potential source of uncertainty when predicting the annual energy production for a prospective wind farm. In particular, significant uncertainty exists in the vertical extrapolation of measured wind data. The use of remote sensing device is rapidly gaining momentum due to various advantages over the installation of permanent wind mast. The latter is generally characterized by lower measurement heights compared to lidar. Lidar measurements enable the reduction of shear extrapolation uncertainties through the direct measurement at hub height and beyond as well as the reduction of uncertainty in fitted shear models.


Lidars are often used for short term campaigns and their data are applied to extrapolate the long term mast data to higher heights. This is critical in energy yield assessment computations as the knowledge of the wind conditions at the wind turbine hub height (or even higher) can significantly decrease the assessment uncertainty. Also, this knowledge contributes to the overall site assessment and turbine selection process, by accurately defining the candidate turbine characteristics and installation location.

Main body of abstract

The objective of the implications of the use of measurements from two masts and two lidars as the primary data source in wind energy projects is quantified in financial terms in the context of a typical finance grade onshore energy yield analysis in complex terrain. This is based upon data collected by IEC compliant masts and co located ZephIR wind lidar in Greece. The financing terms agreed between lending institutions and wind farm developers are a critical element in determining the financial success of an operational wind farm. Terms are negotiated based upon a number of project specific details used to model the financial viability of the project. From those details one of the most significant is the projected annual revenue. In this study we aim to demonstrate the equivalence of projected annual revenue based on high quality mast measurements (30m and 45m agl) with duration of one year and lidar measurements (40m, 62m, 80m, 110m, 140m) for duration of four months (using MCP Matrix method with 45m mast measurements to expand to one year – excellent correlation) for two windfarms of total capacity of 34MW (2MW windturbines with hub height of 80m). The research team examines the financial benefits of using hub - and higher than hub height - measured data compared to using sub-hub height mast measurements. The financial analysis is based on long term corrected energy yield assessment calculations (WAsP and WindPro software packages), using measurements from masts and lidars with the above mentioned measurement heights.


The uncertainty analysis will be done for P50, P75 and P90 confidence level and the deviation of the seven different scenarios (two level of measurements from mast and five levels from lidar – MCP with 45m level of mast) will be extracted. Additionally, the uncertainty will be calculated for one, ten and twenty years. Finally, the financial measures of IRR, NPV for twenty years period and payback period will be presented. The results demonstrate the ability of the lidar to measure finance grade wind data in complex terrain.

Learning objectives
Due to the continuously increase of the windturbines size and hub height it becomes difficult in a lot of cases (especially in mountainous areas) to install a hub or near hub height wind mast. As a result the installation of a relative sub-hub height mast combined with a lidar for an appropriate period of a few months can become a competitive and reliable solution. The portability, competitive costs and lack of planning requirements associated with lidar systems make their use an attractive option for wind resource assessment in complex terrain providing bankable quality of data and more realistic energy yield assessments.