Wind Energy Assessment for Renewable Energy Communities

Author(s):
Araveti, Sandeep; Quintana, Cristian Aguayo; Kairisa, Evita; Mutule, Anna; Adriazola, Juan Pablo Sepulveda; Sweeney, Conor; Carroll, Paula
Publication title: Wind
2022
 | Volume: 2 | Issue: 2
2022
DOI: 10.3390/wind2020018
Abstract:
Renewable and local energy communities are viewed as a key component to the success of the energy transition. In this paper, we estimate wind power po… Renewable and local energy communities are viewed as a key component to the success of the energy transition. In this paper, we estimate wind power potential for such communities. Acquiring the most accurate weather data is important to support decision-making. We identify the most reliable publicly available wind speed data and demonstrate a case study for typical energy community scenarios such as a single commercial turbine at coastal and inland locations in Ireland. We describe our assessment methodology to evaluate the quality of the wind source data by comparing it with meteorological observations. We make recommendations on which publicly available wind data sources, such as reanalysis data sources (MERRA-2, ERA-5), PVGIS, and NEWA are best suited to support Renewable Energy Communities interested in exploring the possibilities of renewable wind energy. ERA5 is deemed to be the most suitable wind data source for these locations, while an anomaly is noted in the NEWA data. more
Application Atmosphere CM-SAF Climate Data Records

Winter Arctic sea ice thickness from ICESat-2: upgrades to freeboard and snow loading estimates and an assessment of the first three winters of data collection

Author(s):
Petty, Alek A.; Keeney, Nicole; Cabaj, Alex; Kushner, Paul; Bagnardi, Marco
Publication title: Cryosphere
2023
 | Volume: 17 | Issue: 1
2023
DOI: 10.5194/tc-17-127-2023
Abstract:
NASA's ICESat-2 mission has provided near-continuous, high-resolution estimates of sea ice freeboard across both hemispheres since data collection sta… NASA's ICESat-2 mission has provided near-continuous, high-resolution estimates of sea ice freeboard across both hemispheres since data collection started in October 2018. This study provides an impact assessment of upgrades to both the ICESat-2 freeboard data (ATL10) and NASA Eulerian Snow On Sea Ice Model (NESOSIM) snow loading on estimates of winter Arctic sea ice thickness. Misclassified leads were removed from the freeboard algorithm in the third release (rel003) of ATL10, which generally results in an increase in freeboards compared to rel002 data. The thickness increases due to increased freeboards in ATL10 improved comparisons of Inner Arctic Ocean sea ice thickness with thickness estimates from ESA's CryoSat-2. The upgrade from NESOSIM v1.0 to v1.1 results in only small changes in snow depth and density which have a less significant impact on thickness compared to the rel002 to rel003 ATL10 freeboard changes. The updated monthly gridded thickness data are validated against ice draft measurements obtained by upward-looking sonar moorings deployed in the Beaufort Sea, showing strong agreement (r2 of 0.87, differences of 11 ± 20 cm). The seasonal cycle in winter monthly mean Arctic sea ice thickness shows good agreement with various CryoSat-2 products (and a merged ICESat-2-CryoSat-2 product) and PIOMAS (Pan-Arctic Ice-Ocean Modeling and Assimilation System). Finally, changes in Arctic sea ice conditions over the past three winter seasons of data collection (November 2018-April 2021) are presented and discussed, including a 50 cm decline in multiyear ice thickness and negligible interannual differences in first-year ice. Interannual changes in snow depth provide a notable impact on the thickness retrievals on regional and seasonal scales. Our monthly gridded thickness analysis is provided online in a Jupyter Book format to increase transparency and user engagement with our ICESat-2 winter Arctic sea ice thickness data. © 2023 Alek A. Petty et al. more
Application Climate Data Records Cryosphere OSI-SAF Ocean

Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years

Author(s):
Yang, Dazhi; Bright, Jamie M.
Publication title: SOLAR ENERGY
2020
 | Volume: 210 | Issue: SI
2020
DOI: 10.1016/j.solener.2020.04.016
Abstract:
Gridded solar radiation products, namely satellite-derived irradiance and reanalysis irradiance, are key to the next-generation solar resource assessm… Gridded solar radiation products, namely satellite-derived irradiance and reanalysis irradiance, are key to the next-generation solar resource assessment and forecasting. Since their accuracies are generally lower than that of the ground-based measurements, providing validation of the gridded solar radiation products is necessary in order to understand their qualities and characteristics. This article delivers a worldwide validation of hourly global horizontal irradiance derived from satellite imagery and reanalysis. The accuracies of 6 latest satellite-derived irradiance products (CAMS-RAD, NSRDB, SARAH-2, SARAH-E, CERES-SYN1deg, and Solcast) and 2 latest global reanalysis irradiance products (ERAS and MERRA-2) are verified against the complete records from 57 BSRN stations, over 27 years (1992-2018). This scope of validation is unprecedented in the field of solar energy. Moreover, the importance of using distribution-oriented verification approaches is emphasized. Such approaches go beyond the traditional measure-oriented verification approach, and thus can offer additional insights and flexibility to the verification problem. more
Atmosphere CM-SAF Climate Data Records Validation

Which gridded irradiance data is best for modelling photovoltaic power production in Germany?

Author(s):
Kenny, Darragh; Fiedler, Stephanie
Publication title: SOLAR ENERGY
2022
 | Volume: 232
2022
DOI: 10.1016/j.solener.2021.12.044
Abstract:
Model estimates of expected photovoltaic (PV) power production rely on accurate irradiance data. Reanalysis and satellite products freely provide irra… Model estimates of expected photovoltaic (PV) power production rely on accurate irradiance data. Reanalysis and satellite products freely provide irradiance data with a high temporal and spatial resolution including locations for which no ground-based measurements are available. We assess differences in such gridded irradiance data and quantify the subsequent bias propagation from individual radiation components to capacity factors in a contemporary PV model. PV power production is simulated based on four reanalysis (ERAS, COSMO-REA6, COSMO-REA6pp, COSMO-REA2) and three satellite products (CAMS, SARAH-2, CERES Syn1Deg). The results are compared against simulations using measurements from 30 weather stations of the German Weather Service. We compute metrics characterizing biases in seasonal and annual means, day-to-day variability and extremes in PV power. Our results highlight a bias of -1.4% (COSMO-REA6) to +8.2% (ERAS) in annual and spatial means of PV power production for Germany. No single data set is best in all metrics, although SARAH-2 and the postprocessed COSMO-REA6 data (COSMO-REA6pp) outperform the other products for many metrics. SARAH-2 yields good results in summer, but overestimates PV output in winter by 16% averaged across all stations. COSMO-REA6pp represents day-to-day variability in the PV power production of a simulated PV fleet best and has a particularly small bias of 0.5% in annual means. This is at least in parts due to compensating biases in local and seasonal means. Our results imply that gridded irradiance data should be used with caution for site assessments and ideally be complemented by local measurements. more
Atmosphere CM-SAF Climate Data Records Validation
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