Posters

Abstract

A wind measurement campaign last generally only a couple of years and is used for a long-term energy estimation. These assessments are usually conducted before the installation or during the first years of operation. Having a reliable long-term source to put the short period of measured data into a long-term context is key. The approach can have significant consequences on the energy production prediction and is often one of the main sources of uncertainty. Being able to select the most representative reference data is considered a key step in every preconstruction or operational energy assessment. Until now, DNV considers in France the ground based Meteo France stations as preferential for their long period of measurement and use them as best approach to evaluate a site windiness. Over the last decade, reanalysis data sources such as ERA5 and MERRA-2 have significantly increased their acceptance due to the constant improvement and are now largely used in long-term wind speed correction. Additionally, high resolution mesoscale dataset have been created in the recent years such as Vortex Series and EMD Europe+ which are now commonly employed in the wind resource assessments due to their high spatial resolution. However, with the proliferation of new datasets and the increased period and representativeness of those sources, it is harder to clearly quantify the quality of the source and to associate an uncertainty to its use. DNV aims to perform a first independent comparative assessment in France and Italy of the main Reanalysis Data sources, Mesoscale Datasets and Ground Based Meteo Stations. A deep focus will be done over a large scale of time and geographical area. To ensure the validity of this comparative assessment, an extended meteorological masts database in France and in Italy will be employed. This validation will focus on windiness, correlations and consistency of the long-term data sources listed above. The outcomes of such validation will benefit the wind industry in determining a relative uncertainty to each long-term source employed as long-term reference, the inter-annual variability effect, and the overall wind speed trends per region.