CMIP6 projections for global offshore wind and wave energy production (2015–2100)

Three-hourly CMIP6 projections have been used in conjuction with the CSIRO WaveWatchIII wave model to calculate the global trends in offshore wind and wave energy for the SSP585 and SSP126 scenarios until 2100. The results indicate that moderate yet significant changes are expected in the theoretical electricity generated from wind and waves at fewer than 10–15% of coastal locations. While this implies a generally stable outlook for the future, certain coastal regions with existing or planned wind farms may experience a slight reduction in production by 2100. Regarding wave energy, given its early stage of development, a more cautious approach is advisable, although a similar conclusion may be reached. Considering the decreasing installation costs on the horizon and accounting for both climatic scenarios, this provides a reliable context for most ongoing feasibility studies, technological developments, and offshore facility investments.This study is part of project PID2020-116153RB-I00 funded by the Spanish Ministry of Science and Innova- tion/National Research Agency MCIN/AEI/ 10.13039/501100011033. The authors acknowledge funding for the research groups by the University of the Basque Country (UPV/EHU, GIU20/08). All the authors have contributed equally to this paper

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

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

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/

Extension and improvement of synchronous linear generator based point absorber operation in high wave excitation scenarios

[EN]The exploitation of marine wave energy resource has led to the design of numerous Wave Energy Converter (WEC) configurations. The power absorption of a WEC is tightly related to its physical properties and the characteristics of the incoming wave front. Additionally, the operational range of a WEC is limited to certain characteristics of the incoming waves. These restrictions are usually related to limitations in the maximum force of the Power Take-off (PTO) system and the safety of the WEC. As a result, the power production of the WEC must be stopped during sea states of high wave elevation. With the objective of improving the operation of a WEC during these sea states, a Field Weakening (FW) control functionality is proposed to be implemented in the control system of a single-body linear in heave oscillating point absorber with a Permanent Magnet Synchronous Linear Generator (PMSLG) based electrical PTO system. The aim of the aforementioned functionality is to attenuate the magnetic flux in the PMSLG during sea states of high wave elevation. The influence of the size of a WEC on the benefits of the proposed FW functionality is also studied. To that end, two point absorbers with different size are analysed with NEMOH and a wave-to-wire (W2W) model of each WEC is developed. This W2W model enables analysis of the performance and power production of the WECs at different sea states of interest. The obtained results show a remarkable improvement of the operation of a WEC with the implementation of the FW strategy during sea states of high excitation, which leads to an extension of its operation and subsequent additional energy/hydrogen generation.Authors acknowledge financial support by the Spanish Ministry of Science and Innovation, Agencia Espanola de Investigacion (grant PID2020-116153RB-I00/AEI/10.13039/501100011033) and the University of the Basque Country under the contract (UPV/EHU, GIU20/008)

Floating wind turbine energy and fatigue loads estimation according to climate period scaled wind and waves

Offshore wind power is one of the fastest-growing renewable energy sources, as it is expected to play a major role in the transition towards sustainability and net zero emissions. Despite its potential, the interaction of the turbines with the oceanic waves, especially in case of floating turbines, is one of the main drawbacks associated to it. In fact, mechanical oscillations caused by the waves could potentially alter the operation and lifetime of the turbines. Hence, while the characterization of the wind is sufficient for the long-term design of onshore wind turbines, the procedure is more complex in case of offshore turbines, since the height, period and direction of the waves will affect the lifetime of the turbine. In this paper, a methodology for the evaluation of the energy generation and fatigue mechanical loads of a Floating Offshore Wind Turbine (FOWT) considering a 30-year period is proposed. To that end, meteorological data from 1991 to 2020 are characterized using a cluster analysis and reduced into a computationally affordable number of simulation cases. Results show negligible energy loss of a FOWT due to interaction with the oceanic waves. However, a substantial increment of the mechanical fatigue in the side-side and fore-aft bending moments of the tower are detected. Such analyses might be applied for the predictability of the lifetime of an offshore wind turbine, as well as the selection of potential optimal wind farm locations, based on climatic patterns and the evolution of meteorological data.The authors acknowledge grant PID2020-116153RB-I00 funded by MCIN/AEI/10.13039/501100011033 and, as appropriate, by “ERDF A way of making Europe”, by the “European Union” or by the “European Union NextGenerationEU/PRTR”. Additionally, financial support by the University of the Basque Country under the contract (UPV/EHU project GIU20/008) has been received

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)

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/)

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)

Paradigmatic case of long-term colocated wind–wave energy index trend in Canary Islands

Previous studies based on remote sensing data and reanalysis have identified strong historical increments of wind speed in the area around the Canary Islands (Spain) without appreciating any increment of wave height. This decoupling of long-term trends for wind and wave data is not very common, and can be considered paradigmatic for an innovative study, with important implications for wind and wave hybrid or co-located energy production. In this study, wind and wave data from ERA5 reanalysis in the area around the Canary Islands have been used to compute a wind–wave energy co-location feasibility index between 1981–2020 showing an increment of the index above ＋5%/decade. Furthermore, realistic wind and wave energy production has been calculated at an interesting hot-spot using a specific floating wind turbine co-located aside a oscillating buoy type wave energy converter. The corresponding capacity factor trend for wind energy (＋0.8%/decade) and capture width ratio evolution for wave energy (−1.5%/decade) shows also the wind–wave decoupling, which constitutes a significant result for an original approach.This paper is part of project PID2020-116153RB-I00 funded by MCIN/AEI, Spain/10.13039/501100011033 and has also received funding from the University of the Basque Country, Spain (UPV/EHU project GIU20/08)