The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential

Hywind-Scotland is a wind farm in Scotland that for many reasons is at the leading edge of technology and is located at a paradigmatic study area for offshore wind energy assessment. The objective of this paper is to compute the Capacity Factor ( CF ) changes and instantaneous power generation changes due to seasonal and hourly fluctuations in air density. For that reason, the novel ERA5 reanalysis is used as a source of temperature, pressure, and wind speed data. Seasonal results for winter show that CF values increase by 3% due to low temperatures and denser air, with economical profit consequences of tens of thousands (US$). Hourly results show variations of 7% in air density and of 26% in power generation via FAST simulations, emphasizing the need to include air density in short-term wind energy studying.This work was financially supported by the Spanish Government through the MINECO project CGL2016-76561-R, (MINECO/ERDF, UE) and the University of the Basque Country (UPV/EHU, GIU 17/002). ERA5 hindcast data were downloaded at no cost from the Copernicus Climate Data Store. All the calculations and plots were made using R: https://www.r-project.org

Study of ocean and wind energy potential with R: an innovative experience in the classroom

[EN] The Engineer School of Eibar initiated the Grade of Engineering in Renewable Energies four years ago. This pioneering educational project has shown many challenges to the teachers of the new grade. Among the different software skills used in this project, R programming language has been a very important one because of its capacity for spatio-temporal analysis and graphical visualization of wind energy and wave energy potential. A quarter of the subject's program in Wind Energy and Ocean Energy has been used via Problem Based Learning for the application of statistical calculus with R. The aim of this contribution is to show some paradigmatic problems solved by the students and the results obtained. Finally, the opinion of the students about the use of R and its learning potentiality have been gathered and analysed.Ulazia, A.; Ibarra-Berastegi, G. (2016). Study of ocean and wind energy potential with R: an innovative experience in the classroom. En 2nd. International conference on higher education advances (HEAD'16). Editorial Universitat Politècnica de València. 9-17. https://doi.org/10.4995/HEAD16.2015.2421OCS91

Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula

A constant value of air density based on its annual average value at a given location is commonly used for the computation of the annual energy production in wind industry. Thus, the correction required in the estimation of daily, monthly or seasonal wind energy production, due to the use of air density, is ordinarily omitted in existing literature. The general method, based on the implementation of the wind speed’s Weibull distribution over the power curve of the turbine, omits it if the power curve is not corrected according to the air density of the site. In this study, the seasonal variation of air density was shown to be highly relevant for the computation of offshore wind energy potential around the Iberian Peninsula. If the temperature, pressure, and moisture are taken into account, the wind power density and turbine capacity factor corrections derived from these variations are also significant. In order to demonstrate this, the advanced Weather Research and Forecasting mesoscale Model (WRF) using data assimilation was executed in the study area to obtain a spatial representation of these corrections. According to the results, the wind power density, estimated by taking into account the air density correction, exhibits a difference of 8% between summer and winter, compared with that estimated without the density correction. This implies that seasonal capacity factor estimation corrections of up to 1% in percentage points are necessary for wind turbines mainly for summer and winter, due to air density changes.This work has been funded by the Spanish Government’s MINECO project CGL2016-76561-R (AEI/FEDER EU) and the University of the Basque Country (UPV/EHU funded project GIU17/02). The ECMWF ERA-Interim data used in this study have been obtained from the ECMWF-MARS Data Server. The authors wish to express their gratitude to the Spanish Port Authorities (Puertos del Estado) for being kind enough to provide data for this study. The computational resources used in the project were provided by 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 at http://www.esrl.noaa.gov/psd/ were used in this paper. National Centres for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce. 2008, updated daily. NCEP ADP Global Upper Air and Surface Weather Observations (PREPBUFR format), May 1997—continuing. Research Data Archive at the National Centre for Atmospheric Research, Computational and Information Systems Laboratory. http://rda.ucar.edu/datasets/ds337.0/ were used. All the calculations have been carried out in the framework of R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org

Global estimations of wind energy potential considering seasonal air density changes

The literature typically considers constant annual average air density when computing the wind energy potential of a given location. In this work, the recent reanalysis ERA5 is used to obtain global seasonal estimates of wind energy production that include seasonally varying air density. Thus, errors due to the use of a constant air density are quantified. First, seasonal air density changes are studied at the global scale. Then, wind power density errors due to seasonal air density changes are computed. Finally, winter and summer energy production errors due to neglecting the changes in air density are computed by implementing the power curve of the National Renewable Energy Laboratorys 5 MW turbine. Results show relevant deviations for three variables (air density, wind power density, and energy production), mainly in the middle-high latitudes (Hudson Bay, Siberia, Patagonia, Australia, etc.). Locations with variations from −6% to 6% are identified from summers to winters in the Northern Hemisphere. Additionally, simulations with the aeroelastic code FAST for the studied turbine show that instantaneous power production can be affected by greater than 20% below the rated wind speed if a day with realistically high or low air density values is compared for the same turbulent wind speed.This work was funded by the Spanish Government's MINECO project CGL2016-76561-R (AEI/FEDER EU) and the University of the Basque Country (UPV/EHU-funded project GIU17/02). The ECMWFERA-5 data used in this study were obtained from the Copernicus Climate Data Store. All the calculations were carried out in the framework of R Core Team (2016). More can be learnt about R, alanguage and an environment for statistical computing, at the website of the R Foundation for Statistical Computing, Vienna,Austria (https://www.R-project.org/)

Pitch Angle Misalignment Correction Based on Benchmarking and Laser Scanner Measurement in Wind Farms

In addition to human error, manufacturing tolerances for blades and hubs cause pitch angle misalignment in wind turbines. As a consequence, a significant number of turbines used by existing wind farms experience power production loss and a reduced turbine lifetime. Existing techniques, such as photometric technology and laser-based methods, have been used in the wind industry for on-field pitch measurements. However, in some cases, regular techniques have difficulty achieving good and accurate measurements of pitch angle settings, resulting in pitch angle errors that require cost-effective correction on wind farms. Here, the authors present a novel patented method based on laser scanner measurements. The authors applied this new method and achieved successful improvements in the Annual Energy Production of various wind farms. This technique is a benchmarking-based approach for pitch angle calibration. Two case studies are introduced to demonstrate the effectiveness of the pitch angle calibration method to yield Annual Energy Production increase.This work is funded by the Council of Gipuzkoa (Gipuzkoako Foru Aldundia, Basque Country, Spain) within the R&D subsidy for the project DIANEMOS on the identification of defective anemometers in wind turbines, and the University of the Basque Country (UPV/EHU, GIU 17/002)

Optimal strategies of deployment of far offshore co-located wind-wave energy farms

[EN] The most profitable offshore energy resources are usually found away from the coast. Nevertheless, the accessibility and grid integration in those areas are more complicated. To avoid this problematic, large scale hydrogen production is being promoted for far offshore applications. The main objective of this paper is to analyze the ability of wave energy converters to maximize hydrogen production in hybrid wind and wave far offshore farms. To that end, wind and wave resource data are obtained from ERA5 for different locations in the Atlantic ocean and a Maximum Covariance Analysis is proposed for the selection of the most representative locations. Furthermore, the suitability of different sized wave energy converters for auxiliary hydrogen production in the far offshore wind farms is also analysed. On that account, the hydrodynamic parameters of the oscillating bodies are obtained via simulations with a Boundary Element Method based code and their operation is modelled using the software tool Matlab. The combination of both methodologies enables to perform a realistic assessment of the contribution of the wave energy converters to the hydrogen generation of an hybrid energy farm, especially during those periods when the wind turbines would be stopped due to the variability of the wind. The obtained results show a considerable hydrogen generation capacity of the wave energy converters, up to 6.28% of the wind based generation, which could remarkably improve the efficiency of the far offshore farm and bring important economical profit. Wave energy converters are observed to be most profitable in those farms with low covariance between wind and waves, where the disconnection times of the wind turbines are prone to be more prolonged but the wave energy is still usable. In such cases, a maximum of 101.12 h of equivalent rated production of the wind turbine has been calculated to be recovered by the wave energy converters.This paper is part of project PID2020-116153RB-I00 funded by MCIN/AEI/ 10.13039/501100011033. Authors also acknowledge financial support by the University of the Basque Country under the contract (UPV/EHU, GIU20/008)

Satelite bidezko itsas gainazaleko tenperatura eta klorofila kontzentrazioen berreraikitzea. Azken hamarkadetako eta urtaroen zikloaren bilakaera Bizkaiko Golkoan

Satelite bidezko itsas gainazaleko tenperatura eta klorofila kontzentrazio irudiei lainoek eragindako zuloak betetzeko DINEOF teknika aplikatu zaie, zulorik gabeko eguneroko maiztasuneko hamarkadetako irudi sortak sortzeko asmoarekin. Irudi sorta horien azterketa egin da ondoren bi aldagaietan urtaroen zikloa aztertzeko, bai bere anplitudeari zein bere faseari dagokienez. Azterketak erakusten du tenperaturaren urtaro zikloaren anplitudeak 0,11 °C/hamarkada balioko joera gorakor adierazgarria duela baina ez horrela klorofila kontzentrazioarenak. Faseari dagokionez, berriz, ez da joera adierazgarririk detektatu bi aldagaietako batean ere.; Satellite sea surface temperate and chlorophyll concentration images have been processed using DINEOF technique to fill the gaps created by the presence of clouds in satellite images. This set of satellite temperature and chlorophyll images have then been used to analyse their respective seasonal cycles, both regarding the amplitude of the cycle and its phase. The results show a significant growing trend in the amplitude of the seasonal cycle with a value of 0.11 ºC/decade in the case of the temperature, but no significant trend for chlorophyll. Again, no significant trend is observed in the phase of the cycle in both variables

Changes in the simulation of atmospheric instability over the Iberian Peninsula due to the use of 3DVAR data assimilation

The ability of two downscaling experiments to correctly simulate thermodynamic conditions over the Iberian Peninsula (IP) is compared in this paper. To do so, three parameters used to evaluate the unstable conditions in the atmosphere are evaluated: the total totals index (TT), convective available potential energy (CAPE), and convective inhibition (CIN). The Weather and Research Forecasting (WRF) model is used for the simulations. The N experiment is driven by ERA-Interim's initial and boundary conditions. The D experiment has the same configuration as N, but the 3DVAR data assimilation step is additionally run at 00:00, 06:00, 12:00, and 18:00 UTC. Eight radiosondes are available over the IP, and the vertical temperature and moisture profiles from the radiosondes provided by the University of Wyoming and the Integrated Global Radiosonde Archive (IGRA) were used to calculate three parameters commonly used to represent atmospheric instability by our own methodology using the R package aiRthermo. According to the validation, the correlation, standard deviation (SD), and root mean squared error (RMSE) obtained by the D experiment for all the variables at most of the stations are better than those for N. The different methods produce small discrepancies between the values for TT, but these are larger for CAPE and CIN due to the dependency of these quantities on the initial conditions assumed for the calculation of a lifted air parcel. Similar results arise from the seasonal analysis concerning both WRF experiments: N tends to overestimate or underestimate (depending on the parameter) the variability of the reference values of the parameters, but D is able to capture it in most of the seasons. In general, D is able to produce more reliable results due to the more realistic values of dew point temperature and virtual temperature profiles over the IP. The heterogeneity of the studied variables is highlighted in the mean maps over the IP. According to those for D, the unstable air masses are found along the entire Atlantic coast during winter, but in summer they are located particularly over the Mediterranean coast. The convective inhibition is more extended towards inland at 00:00 UTC in those areas. However, high values are also observed near the southeastern corner of the IP (near Murcia) at 12:00 UTC. Finally, no linear relationship between TT, CAPE, or CIN was found, and consequently, CAPE and CIN should be preferred for the study of the instability of the atmosphere as more atmospheric layers are employed during their calculation than for the TT index.The computational resources were provided by I2BASQUE, and the authors thank the creators of WRF/ARW and WRFDA systems. Authors also thank the anonymous reviewers for their comments, which have helped to improve the paper. Finally, most of the calculations were carried out with R (R Core Team, 2020), and the authors want to thank all the authors of the packages used for it

Sensitivity Studies for a Hybrid Numerical–Statistical Short-Term Wind and Gust Forecast at Three Locations in the Basque Country (Spain)

This study evaluates the performance of statistical models applied to the output of numerical models for short-term (1–24 h) hourly wind forecasts at three locations in the Basque Country. The target variables are horizontal wind components and the maximum wind gust at 3 h intervals. Statistical approaches such as persistence, analogues, linear regression, and random forest (RF) are used. The verification statistics used are coefficient of determination (R2) and root mean square error (RMSE). Statistical models use three inputs: (1) Local wind observations; (2) extended EOFs (empirical orthogonal functions) derived from past local observations and ERA-Interim variables in a previous 24-h period covering a domain around the area of study; and (3) wind forecasts provided by ERA-Interim. Results indicate that, for horizons less than 1–4 h, persistence is the best model. For longer predictions, RF provides the best forecasts. For horizontal components at 4–24 h horizons, RF slightly outperformed ERA-Interim wind forecasts. For gust, RF performs better than ERA-Interim for all the horizons. Persistence is the most influential factor for 2–5 h. Beyond this horizon, predictors from the ERA-Interim wind forecasts led the contribution. Hybrid numerical–statistical methods can be used to improve short-term wind forecasts.This work was supported by the Spanish Government, MINECO project CGL2016-76561-R (MINECO/EU ERDF), and the University of the Basque Country (project GIU17/02)

Historical Evolution of theWave Resource and Energy Production off the Chilean Coast over the 20th Century

The wave energy resource in the Chilean coast shows particularly profitable characteristics for wave energy production, with relatively high mean wave power and low inter-annual resource variability. This combination is as interesting as unusual, since high energetic locations are usually also highly variable, such as the west coast of Ireland. Long-term wave resource variations are also an important aspect when designing wave energy converters (WECs), which are often neglected in resource assessment. The present paper studies the long-term resource variability of the Chilean coast, dividing the 20th century into five do-decades and analysing the variations between the different do-decades. To that end, the ERA20C reanalysis of the European Centre for Medium-Range Weather Forecasts is calibrated versus the ERA-Interim reanalysis and validated against buoy measurements collected in different points of the Chilean coast. Historical resource variations off the Chilean coast are compared to resource variations off the west coast in Ireland, showing a significantly more consistent wave resource. In addition, the impact of historical wave resource variations on a realistic WEC, similar to the Corpower device, is studied, comparing the results to those obtained off the west coast of Ireland. The annual power production off the Chilean coast is demonstrated to be remarkably more regular over the 20th century, with variations of just 1% between the different do-decades.The authors with the Centre for Ocean Energy Research in Maynooth University are supported by Science Foundation Ireland under Grant No. 13/IA/1886. It is also supported by grant CGL2016-76561-R, MINECO/ERDF, UE. Additional funding was received from the University of Basque Country (UPV/EHU, GIU17/002)