Using 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterranean

In this article, offshore wind energy potential is measured around the Iberian Mediterranean coast and the Balearic Islands using the WRF meteorological model without 3DVAR data assimilation (the N simulation) and with 3DVAR data assimilation (the D simulation). Both simulations have been checked against the observations of six buoys and a spatially distributed analysis of wind based on satellite data (second version of Cross-Calibrated Multi-Platform, CCMPv2), and compared with ERA-Interim (ERAI). Three statistical indicators have been used: Pearson’s correlation, root mean square error and the ratio of standard deviations. The simulation with data assimilation provides the best fit, and it is as good as ERAI, in many cases at a 95% confidence level. Although ERAI is the best model, in the spatially distributed evaluation versus CCMPv2 the D simulation has more consistent indicators than ERAI near the buoys. Additionally, our simulation’s spatial resolution is five times higher than ERAI. Finally, regarding the estimation of wind energy potential, we have represented the annual and seasonal capacity factor maps over the study area, and our results have identified two areas of high potential to the north of Menorca and at Cabo Begur, where the wind energy potential has been estimated for three turbines at different heights according to the simulation with data assimilation.This work has been funded by the Spanish Government’s MINECO project CGL2016-76561-R (MINECO/FEDER EU), the University of theBasque Country (project GIU14/03) and the Basque Government (Elkartek 2017 INFORMAR project). SJGR is supported by a FPIPredoctoral Research Grant (MINECO, BES-2014-069977). The ECMWFERA-Interim data used in this study have been obtained from the ECMWF-MARS Data Server thanks to agreements with ECMWF and AEMET. The authors would like to express their gratitude to the Spanish Port Authorities (Puertos del Estado) for kindly providing data for thisstudy. The computational resources used in the project were providedby I2BASQUE. The authors thank the creators of the WRF/ARW and WRFDA systems for making them freely available to the community. NOAA_OI_SST_V2 data provided by the NOAA/OAR/ESRL PSD,Boulder, Colorado, USA, through their web-site athttp://www.esrl.noaa.gov/psd/was used in this paper. National Centers for Environmental Prediction/National Weather Service/NOAA/U.S.Department of Commerce. 2008, updated daily. NCEP ADP GlobalUpper Air and Surface Weather Observations (PREPBUFR format), May1997–Continuing. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory.http://rda.ucar.edu/datasets/ds337.0/were used. All thecalculations have been carried out in the framework of R Core Team(2016). R: A language and environment for statistical computing. RFoundation for Statistical Computing, Vienna, Austria. URLhttps://www.R-project.org/

Historical wave energy trends in the Bay of Biscay

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Using open software to teach resource assessment of renewable energies

[EN] The students of the Faculties of Engineering of the Universitty of Basque Country (Gipuzkoa-Eibar and Bilbao) in the last years of their studies, before becoming engineers, have the opportunity to select a block of subjects intended to enhance their knowledge on Wind Energy, Ocean Energy, Biomass and Hydraulic Energy. These subjects are devoted to different aspects of the water cycle management, and geographical representations of wind, ocean and biomass energy resource. Apart from the transmission of good practices, the focus is practical and is based on hands-on computer real-life exercises, which involves not only intensive programming using high-level software, but also the spatial representation of results. To that purpose three main open source codes are used: EPANET (https://www.epa.gov/water-research/epanet), QGIS (https://www.qgis.org/) and R (https://www.cran.r-project.org/). Students learn how to address real-life problems regarding the correct calculation of water distribution networks with EPANET, geographical representation of wind and ocean energy resource with R, and spatial representation of biomass resource with QGIS.Ulazia, A.; Urresti, A.; Antxustegi, M.; Gonzalez, M.; Campos, A.; Ibarra-Berastegui, G.; Garcia Arribas, R. (2017). Using open software to teach resource assessment of renewable energies. En Proceedings of the 3rd International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 584-591. https://doi.org/10.4995/HEAD17.2017.5296OCS58459

Historical wave energy trends in the Bay of Biscay

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Wave energy resource variation off the west coast of Ireland and its impact on realistic wave energy converters’ power absorption

Wave energy converters are specifically designed to extract the maximum energy from a given location. To that end, wave data statistics based on past measures at the given location are commonly used, neglecting any possible future wave trend. This paper studies the variations of the wave energy resource off the west coast of Ireland over the 20th century via the atmospheric reanalyses created by the European Centre for Medium-Range Weather Forecasts. In particular, the European Re-Analysis ERA20 is calibrated via quantile-matching against the new European Re-Analysis ERA-Interim for the period 1979–2010. In addition, the calibrated ERA20 reanalysis is validated against buoy measurements in the area of interest. Results show a significant increase of the wave energy resource along the last century (an increase of over 40%), for which the largest increase is observed within the last 20 years (an increase of 18% between 1980 and 2000). The paper shows that these variations considerably affect the power absorption of realistic devices, showing a power surplus of up to 15% within the lifespan of a wave energy converter. Finally, an increase of extreme events over the last century is also observed, highlighting its impact on power production due to the need of wave energy converters to switch into survival mode during extreme events

Historical wave energy trends in the Bay of Biscay

Abstract included in text

Historical wave energy trends in the Bay of Biscay

Abstract included in text

Reduction of the capture width of wave energy converters due to long-term seasonal wave energy trends

This paper presents a pioneering attempt to evaluate the impact of long-term seasonal wave energy trends on hydrodynamic capture by wave energy converters (WECs) over the 20th century. The ERA20c reanalysis generated by the European Centre for Medium-Range Weather Forecasts is calibrated against the ERA-Interim reanalysis via the quantile matching technique, and validated against buoy measurements across the Northeast Atlantic Ocean. The study focus is the seasonal variation of wave resources over the 20th century, so the calibration is performed using seasonally classified reanalysis and measured data. Results show that wave energy flux increased to 3 and 2 kW/m per decade in winter and spring/autumn, respectively, and that the frequency of off-limit events, defined as sea-states with significant wave height of over 5 m, has doubled over the 20th century. The impact of such wave energy trends is analysed in this paper using an oscillating wave surge converter, which shows steadily increasing power absorption over the 20th century. However, as a result of higher decadal trends and the increase in off-limit events, the hydrodynamic efficiency of the WEC, referred to as the capture width ratio, decreases up to 20%

Wave energy trends over the Bay of Biscay and the consequences for wave energy converters

This is one of the pioneer and preliminary attempt to study the influence of wave energy trends on the absorbed power of wave energy converters. For that purpose, the reanalysis of the past century ERA20 has been calibrated via quantile-matching against the reanalysis ERA-Interim in their intersection period (1979–2010). The validation against four buoys in the Bay of Biscay is presented in this paper, showing a better agreement of ERA-Interim-WAM model when compared to the original ERA20. In addition, calibrated ERA20 shows a significant error reduction compared to the original ERA20. Hence, calibrated ERA20 presents an increment of the wave energy resource, more than 1 kW/m per decade, in the area of study and a general increment of the wave height and wave period throughout the analyzed decades. Finally, using the calibrated series at a given gridpoint in the bay, power absorption of a generic wave energy converter (WEC) is examined, combining the power matrix of the WEC and the two-variable (wave height and period) probability density functions (PDF) of the five do-decades of the past century. Results show important variations of the PDF, which results in significant differences, up to a 15% increase between two do-decades, in the annual mean power production