Assessment of the offshore wind technical potential for the Brazilian Southeast and South regions

Tavares, Luiz Filipe de Assis; Shadman, Milad; Assad, Luiz Paulo de Freitas; Silva, Corbiniano; Landau, Luiz; Estefen, Segen F.

doi:10.1016/j.energy.2020.117097

Cited by 61 publications

(33 citation statements)

References 30 publications

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“…Regarding ERA5 wind and wave data, in [40] sea surface wind speed data over the Caspian Sea were evaluated in comparison with measurements from offshore platforms and showed good agreement for measurements greater than 2 m/s. In [41] wind speed data over the South and Southeast Brazilian coastline from ERA5 and two more reanalysis datasets were compared against in-situ measurements and concluded that ERA5 has a better performance. Furthermore, in [42], ERA5 wave data were compared to an observed wave dataset collected offshore in the swell-dominated region of the Oman coast in the western Arabian Sea.…”

Section: Era5 Datasetmentioning

confidence: 99%

Offshore Wind and Wave Energy Complementarity in the Greek Seas Based on ERA5 Data

2021

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In this work, 20 years (2000–2019) of ERA5 wave and wind data are analyzed and evaluated for the Greek Seas by means of in-situ measurements derived from the POSEIDON marine monitoring system. Four different statistical measures were used at six locations, where in-situ wind and wave measurements are available from oceanographic buoys. Furthermore, the ERA5 wind and wave datasets were utilized for the estimation of the available wind and wave energy potential for the Greek Seas, as well as for the assessment of complementarity and synergy between the two resources. In this respect, an event-based approach was adopted. The spatial distribution of the available wind and wave energy potential resembles qualitatively and quantitatively the distributions derived from other reanalysis datasets. Locations with high synergy and complementarity indices were identified taking into account water depth. Finally, taking into consideration a particular offshore wind turbine power curve and the power matrix of the PELAMIS wave energy converter, the estimation of the combined energy potential on a mean annual basis is performed.

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Section: Era5 Datasetmentioning

confidence: 99%

Offshore Wind and Wave Energy Complementarity in the Greek Seas Based on ERA5 Data

2021

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“…Overall the validation showed that the downscaling methodology proposed resulted in realistic atmospheric fields, especially for SLP, that represent well the atmospheric systems that modulate the climate over SBr. As the downscaling methodology is highly sensitive to the initial boundaries conditions, it is advisable further studies accessing this methodology, for example, with the new ERA5 Reanalysis, that showed promising results for SBr (Hersbach et al ., 2019, 2020; de Assis Tavares et al ., 2020; Fernandes et al ., 2021).…”

Section: Discussionmentioning

confidence: 99%

A hybrid regional climate downscaling for the southern Brazil coastal region

Souza

Silva

et al. 2022

Intl Journal of Climatology

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A hybrid method is applied to generate a high‐resolution regional downscaling of atmospheric conditions to the southern coast of Brazil. The method consists of applying a principal component analysis to daily fields of the sea level pressure (SLP) data from the NCEP‐CFSR reanalysis. A cluster analysis (K‐means) is then applied to the 87 principal components that explained 95% of the variance of the time series. Daily atmospheric conditions were clustered into 36 weather types which represent the most predominant conditions observed in the study area. The estimated weather types were able to represent the major atmospheric systems affecting local climate, including the cyclones and anticyclones that are usually present in this region. Then, we applied the numerical Ocean‐Land‐Atmosphere Model (OLAM) to dynamically downscale the atmospheric condition that is closest to the centroid of each cluster. The model was set with a global grid and a refining approach with 6 km grid spacing over the coastal region of south Brazil. This approach allowed us to represent simultaneously the planetary waves and the local mesoscale systems, and their mutual interactions. The results provided new high‐resolution atmospheric fields for the coastal region and showed that the model was capable of resolving the major local mesoscale features. The main advantage of applying such a method is in reducing the number of numerical simulations (lower computational cost) at the same time it represents the totality of the atmospheric conditions observed in the study area. The final results consist in detailed information of the local climate that can be related to injuries to the coastal area and thus is useful to support decision‐makers.

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“…This provides a simple way of visually showing how closely a pattern matches an observation, and it is a useful tool to easily compare different parameters at a glance using the same plot. This type of comparison is widely used when weather parameters are analyzed [28,[47][48][49][50][51]. Developed by Taylor in 2001, this diagram shows the correspondence between two patterns (in this case, third-party weather data as the test field (f ) and on-site weather data as the reference field (r)) using three statistical metrics: the correlation R, the centered root-mean-squared difference RMS di f f , and the standard deviation σ of the test and reference field.…”

Section: Weather Data Comparison Methodologymentioning

confidence: 99%

Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets

et al. 2020

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The use of building energy models (BEMs) is becoming increasingly widespread for assessing the suitability of energy strategies in building environments. The accuracy of the results depends not only on the fit of the energy model used, but also on the required external files, and the weather file is one of the most important. One of the sources for obtaining meteorological data for a certain period of time is through an on-site weather station; however, this is not always available due to the high costs and maintenance. This paper shows a methodology to analyze the impact on the simulation results when using an on-site weather station and the weather data calculated by a third-party provider with the purpose of studying if the data provided by the third-party can be used instead of the measured weather data. The methodology consists of three comparison analyses: weather data, energy demand, and indoor temperature. It is applied to four actual test sites located in three different locations. The energy study is analyzed at six different temporal resolutions in order to quantify how the variation in the energy demand increases as the time resolution decreases. The results showed differences up to 38% between annual and hourly time resolutions. Thanks to a sensitivity analysis, the influence of each weather parameter on the energy demand is studied, and which sensors are worth installing in an on-site weather station are determined. In these test sites, the wind speed and outdoor temperature were the most influential weather parameters.

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Assessment of the offshore wind technical potential for the Brazilian Southeast and South regions

Cited by 61 publications

References 30 publications

Offshore Wind and Wave Energy Complementarity in the Greek Seas Based on ERA5 Data

Offshore Wind and Wave Energy Complementarity in the Greek Seas Based on ERA5 Data

A hybrid regional climate downscaling for the southern Brazil coastal region

Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets

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