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 (6.34 MB)


Wind/energy resource assessment, the importance of the data quality used, test case


An accurate wind/energy resource assessment plays key role in the efficient planning and the securing of the financing of a wind farm. Results and uncertainty levels of the assessment depend strongly on the quality of the data used. Comparing the results of the wind/energy resource assessment with the real energy production of an operating wind farm leads to very useful conclusions.


This study attempts to quantify the relation between the quality of the data used and the accuracy of the wind/energy resource assessment. In order to do that a wind farm with many years of operation has been selected. The real annual energy production of the operating wind farm is compared with the results of the wind/energy resource assessment that is calculated each time using artificially modified data.

Main body of abstract

The wind farm is located in the island of Euboea in Greece has a total capacity of 1,5 MW (2 x 0,75 MW windturbines of 44m hub height) and has been operating for 14 years. Wind measurements are available from a 20m mast installed inside the wind farm area for a total period of 3 years, the wind data availability is 99%. Wind/energy calculation are performed using WindPRO 3.0 and WAsP 11.02 (wind farm design tools) and are long-term corrected by the use of high quality reanalysis data, furthermore uncertainty is also calculated. The quality of the original data set of wind data (3 years, 99% data availability) is artificially reduced by manually removing an amount of data in order to simulate a reduced data availability of the data set by a step of 5% at a time. For each (reduced data availability) data set a new wind/energy resource assessment is calculated together with the P(75) and P(90) production probability values. The results are then compared with the real annual energy production of the Windfarm. Furthermore the original data set long term correction is performed by using different reanalysis data with different correlation factors. A new wind/energy resource assessment is performed per case and the new production probability values P(50) – P(75) – P(90) are compared with the real energy production of the wind farm.


The wind/energy resource assessment seems to overestimate the energy production, while P(75) and P(90) probability values seem closer to reality. Reduced availability of wind measurements has an influence in the accuracy of the results. The use of high quality reanalysis data improves the accuracy and seems to reduce the uncertainty of the results.

Learning objectives
The quality of the data used plays an important role when assessing the energy and hence the financial returns of a wind energy project. The deviation of the assessment has some possible reasons that have been named. The industry should continue to investigate the factors that lead to reduced accuracy and/or higher uncertainty of the assessment. Moreover, stakeholder should take special consideration of those factors while developing a wind project.