Offshore wind energy assessment for the Iberian coasts using remotely sensed data

Salvação, N.; Soares, C; Bentamy, Abderrahim

doi:10.1201/b18973-35

Cited by 6 publications

(14 citation statements)

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“…The initial α exponent value (i.e., 0.1) was chosen based on the validation experience with the updated offshore wind maps for the US and is within the range of 0.08 to 0.14 reported in other analyses for the same region [25]. In a similar study of the creation of a wind resource map for the Iberian Coast using remotely sensed data, a power law was also used with a shear exponent value J of 0.1 [27,34] (Table 4). Given the characteristics of the Portuguese continental shelf, it is expected that floating platforms for harnessing wind will be installed offshore and in waters greater than 50 m deep.…”

Section: Discussionmentioning

confidence: 99%

“…A wind speed shear exponent of ~0.1 has been used in previous studies [25,27] for extrapolating offshore wind speeds using a power law at a height of 90 m. Thus, in the present study and for an initial assessment of the wind resource at the APLF, a value for J of 0.1 is used for a hub height of 80 m. The value is then adjusted using a validation procedure by comparing the results of the model with those of the meteorological mast station located inside the APLF (refer to sub-section 3.3 for further details).…”

Section: Wind Model and In Situ Datamentioning

confidence: 99%

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An evaluation of offshore wind power production by floatable systems: A case study from SW Portugal

Pacheco

Gorbeña

Sequeira

et al. 2017

Energy

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The challenge for floating offshore wind structures is to reduce costs. The industry needs a wind turbine support solution that can be fabricated and deployed from existing shipyards and port facilities, while investors need accurate estimations and forecasts of wind resources and quantified information on the inherent variability in wind power generation. This paper merges hindcast model data with observed in situ data to characterize the wind resource potential off the SW coast of Portugal. The validation procedure adopted allows an estimation of the coefficient used for power-law extrapolation of the wind measurements and a reduction in the uncertainty of the power density calculations. Different types of turbine model are compared and site metocean characteristics are examined as a basis for choosing between existing wind floatable solutions. The calculations using four different wind turbine models indicate a preferable installed capacity of 3-4 MW for a hub height of 90-120 m (i.e., representing the best capacity factor and load hours). There is a consistent difference in power density of about 20% from a location 5 nautical miles (NM) offshore to one 10 NM offshore, which represents an increment of 20%-25% in energy production depending on the particular wind turbine capacity factor.

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Section: Discussionmentioning

confidence: 99%

Section: Wind Model and In Situ Datamentioning

confidence: 99%

An evaluation of offshore wind power production by floatable systems: A case study from SW Portugal

Pacheco

Gorbeña

Sequeira

et al. 2017

Energy

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“…(cf. [9]). The wind power density formula [8] (Equation ( 2)) was then applied to the mean wind speed in order to produce an estimate of the wind energy available in Ireland's offshore waters.…”

Section: Wind Extrapolation and Ireland's Wind Energy Density Mapmentioning

confidence: 99%

“…Moreover, inland renewable energy projects can have reduced site availability due to multiple stakeholder interactions, environmental constraints, as well as aesthetic factors, while offshore sites may be more easily situated near coastal population centres [2,4,5,8]. Consequently, the offshore wind energy market grew by 34% in the European Union in 2013, in comparison with 12% for its land-based counterpart [9]. Furthermore, the offshore wind industry has undergone important development during the past ten years to increase energy capacity, as well as to develop structures that can be sited further offshore.…”

Section: Introductionmentioning

confidence: 99%

The Potential of Advanced Scatterometer (ASCAT) 12.5 km Coastal Observations for Offshore Wind Farm Site Selection in Irish Waters

et al. 2019

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The offshore wind industry has seen unprecedented growth over the last few years. In line with this growth, there has been a push towards more exposed sites, farther from shore, in deeper water with consequent increased investor risk. There is therefore a growing need for accurate, reliable, met-ocean data to identify suitable sites, and from which to base preliminary design and investment decisions. This study investigates the potential of hyper-temporal satellite remote sensing Advanced Scatterometer (ASCAT) data in generating information necessary for the optimal site selection of offshore renewable energy infrastructure, and hence providing a cost-effective alternative to traditional techniques, such as in situ data from public or private entities and modelled data. Five years of the ASCAT 12.5 km wind product were validated against in situ weather buoys and showed a strong correlation with a Pearson coefficient of 0.95, when the in situ measurements were extrapolated with the log law. Temporal variations depicted by the ASCAT wind data followed the same inter-seasonal and intra-annual variations as the in situ measurements. A small diurnal bias of 0.12 m s−1 was observed between the descending swath (10:00 to 12:00) and the ascending swath (20:30 to 22:30), indicating that Ireland’s offshore wind speeds are slightly stronger in the daytime, especially in the nearshore areas. Seasonal maps showed that the highest spatial variability in offshore wind speeds are exhibited in winter and summer. The mean wind speed extrapolated at 80 m above sea level showed that Ireland’s mean offshore wind speeds at hub height ranged between 9.6 m s−1 and 12.3 m s−1. To best represent the offshore wind resource and its spatial distribution, an operational frequency map and a maximum yield frequency map were produced based on the ASCAT wind product in an offshore zone between 20 km and 200 km from the coast. The operational frequency indicates the percentage of time during which the observed local wind speed is between cut-in (3 m/s) and cut-out (25 m/s) for a standard turbine. The operational frequency map shows that the frequency of the wind speed within the cut-in and cut-off range of wind turbines was between 92.4% and 97.2%, while the maximum yield frequency map showed that between 40.6% and 59.5% of the wind speed frequency was included in the wind turbine rated power range. The results showed that the hyper-temporal ASCAT 12.5 km wind speed product (five consecutive years, two observations daily per satellite, two satellites) is representative of wind speeds measured by in situ measurements in Irish waters, and that its ability to depict temporal and spatial variability can assist in the decision-making process for offshore wind farm site selection in Ireland.

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“…In fact, the perspectives of the Wind Europe, for Spain, for 2020 in terms of offshore wind is only 5 MW [7], which is the power of an offshore wind turbine installed in a port in the Canary islands to be tested as offshore wind turbine, but still not deployed at sea. Therefore, it is important to boost the offshore wind sector in the future [8] in order to achieve the success that can be found in the onshore wind sector, including its operational issues such as the safety [9] availability [10,11] and maintenance [12,13], its integration in the grid [14], its offshore wind resource [15][16][17][18], its layout optimization [19], or its resource prediction [20].…”

Section: Introductionmentioning

confidence: 99%

Economic Feasibility of Floating Offshore Wind Farms in the North of Spain

Castro-Santos

Bento

Silva

et al. 2020

JMSE

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This paper assesses the economic feasibility of offshore wind farms installed in deep waters considering their internal rate of return (IRR), net present value (NPV), and levelized cost of energy (LCOE). The method proposed has three phases: geographic phase, economic phase, and restrictions phase. The purpose of the geographic step is to obtain the input values, which will be used in the economic phase. Then, the economic parameters are calculated considering the inputs provided previously. Finally, the bathymetric restriction is added to the economic maps. The case study focused on the Cantabric and North-Atlantic coasts of Spain, areas that have not been studied previously in economic terms regarding floating offshore wind technology. Moreover, several alternatives have been considered, taking into account the type of floating offshore wind structure and the electric tariff. Results indicate which is the best floating offshore wind structure with respect to LCOE, IRR, and NPV, and where is the best location for the connection of a floating offshore wind farm in the region selected.

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Offshore wind energy assessment for the Iberian coasts using remotely sensed data

Cited by 6 publications

References 0 publications

An evaluation of offshore wind power production by floatable systems: A case study from SW Portugal

An evaluation of offshore wind power production by floatable systems: A case study from SW Portugal

The Potential of Advanced Scatterometer (ASCAT) 12.5 km Coastal Observations for Offshore Wind Farm Site Selection in Irish Waters

Economic Feasibility of Floating Offshore Wind Farms in the North of Spain

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