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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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https://doi.org/10.5194/wes-2020-7
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2020-7
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 28 Jan 2020

Submitted as: research article | 28 Jan 2020

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This preprint is currently under review for the journal WES.

Offshore Wind Energy Resource Assessment from Satellite Data Observations and WRF in Porto Santo Island

Fabiola S. Pereira1,2 and Carlos S. Silva2,3 Fabiola S. Pereira and Carlos S. Silva
  • 1AREAM – Regional Energy and Environmental Agency of Madeira Autonomous Region, Funchal, 9020-105, Portugal
  • 2MIT Portugal Program, Instituto Superior Técnico (IN+), Lisbon, 1049-001, Portugal
  • 3Center for Innovation, Technology and Policy Research (IN+), Instituto Superior Técnico, Lisbon, 1049-001, Portugal

Abstract. The vast majority of isolated electricity production systems such as Islands depends on fossil fuels. Porto Santo Island, a Portuguese UNESCO Biosphere Reserve candidate from Madeira Archipelago situated in the Atlantic Ocean, aims to become a sustainable territory in order to reduce its carbon footprint. A sustainable pathway goes through the integration of renewable energy in the electricity production system, in particular, the potential of offshore wind energy.

The scope of this work has three main purposes: (1) the offshore wind resource assessment in Porto Santo Island, (2) the determination of a zone of interest regarding the combination of different parameters such us the bathymetry, distance to the coastline and integrated in the national situation plan of maritime space (3) the estimation of the annual energy production from the best-fitted Weibull Distribution.

In the first place, a methodology for data analysis was defined processing netcdf data regarding a ten year wind hindcast from WRF (Weather Research and Forecasting) atmospheric model at 100 m above mean sea level from Ocean Observatory, annual and monthly mean offshore wind energy resource maps were created and a comparison with about 20 year times series of surface winds derived from remotely satellite scatterometer observations at different locations was made. Results show that the average annual mean wind speeds reach the range of 6.6–7.6 m/s in specific areas, situated in the northern part of Porto Santo Island with a Weibull distribution shape parameter (k) of 2.4–2.9. Based on the results, the wind resource assessment, the estimation of the annual wind energy production and capacity factors were calculated from the best-fitted Weibull distribution for each of the geographical coordinates selected.

Comparisons with observational data show that WRF model is a proficient wind generating tool. The technical energy production potential and a priority zoning for offshore wind power development is performed using wind turbine generators of 3.3 MW–8.0 MW capacity, that could generate between 12 and 26 GWh of energy per year, while avoiding CO2 emissions. The results show that an offshore wind farm plan is an eligible choice, with an average annual wind power density reaching about 300  W/m2 at 100 m height in the north region.

Fabiola S. Pereira and Carlos S. Silva

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Fabiola S. Pereira and Carlos S. Silva

Fabiola S. Pereira and Carlos S. Silva

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Latest update: 16 Feb 2020
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Short summary
The work outlines a methodology for combining 20-year time series of surface winds derived from remotely scatterometer observations with results from 10-year wind hindcast from WRF model, in order to acquire and validate reconstructed offshore winds for offshore wind energy resource assessment. The spatial distribution of the mean wind speeds shows that the northern part of the portuguese Porto Santo Island, is characterized by the most interesting wind resource for electricity generation.
The work outlines a methodology for combining 20-year time series of surface winds derived from...
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