Offshore Wind Energy Resource Assessment for Alaska

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.

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Exploring the Grid Value of Offshore Wind Energy in Oregon

Energies ◽

10.3390/en14154435 ◽

2021 ◽

Vol 14 (15) ◽

pp. 4435

Author(s):

Travis C. Douville ◽

Dhruv Bhatnagar

Keyword(s):

Wind Energy ◽

Cost Model ◽

Energy Resource ◽

Energy Resources ◽

Offshore Wind ◽

Offshore Wind Energy ◽

Renewable Energy Resources ◽

Energy Potential ◽

Resource Complementarity ◽

Wind Energy Potential

The significant offshore wind energy potential of Oregon faces several challenges, including a power grid which was not developed for the purpose of transmitting energy from the ocean. The grid impacts of the energy resource are considered through the lenses of (i) resource complementarity with Variable Renewable Energy resources; (ii) correlations with load profiles from the four balancing authorities with territory in Oregon; and (iii) spatial value to regional and coastal grids as represented through a production cost model of the Western Interconnection. The capacity implications of the interactions between offshore wind and the historical east-to-west power flows of the region are discussed. The existing system is shown to accommodate more than two gigawatts of offshore wind interconnections with minimal curtailment. Through three gigawatts of interconnection, transmission flows indicate a reduction of coastal and statewide energy imports as well as minimal statewide energy exports.

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Climate change impacts on the future offshore wind energy resource in China

Renewable Energy ◽

10.1016/j.renene.2021.05.001 ◽

2021 ◽

Author(s):

X. Costoya ◽

M. deCastro ◽

D. Carvalho ◽

Z. Feng ◽

M. Gómez-Gesteira

Keyword(s):

Climate Change ◽

Wind Energy ◽

Energy Resource ◽

Climate Change Impacts ◽

Offshore Wind ◽

Offshore Wind Energy ◽

The Future

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Offshore Wind Energy Resource Assessment across the Territory of Oman: A Spatial-Temporal Data Analysis

Sustainability ◽

10.3390/su13052862 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2862

Author(s):

Amer Al-Hinai ◽

Yassine Charabi ◽

Seyed H. Aghay Kaboli

Keyword(s):

Data Analysis ◽

Wind Energy ◽

Wind Turbines ◽

Energy Resource ◽

Wind Farms ◽

Offshore Wind ◽

Wind Data ◽

Offshore Wind Energy ◽

Offshore Wind Turbines ◽

Wind Potential

Despite the long shoreline of Oman, the wind energy industry is still confined to onshore due to the lack of knowledge about offshore wind potential. A spatial-temporal wind data analysis is performed in this research to find the locations in Oman’s territorial seas with the highest potential for offshore wind energy. Thus, wind data are statistically analyzed for assessing wind characteristics. Statistical analysis of wind data include the wind power density, and Weibull scale and shape factors. In addition, there is an estimation of the possible energy production and capacity factor by three commercial offshore wind turbines suitable for 80 up to a 110 m hub height. The findings show that offshore wind turbines can produce at least 1.34 times more energy than land-based and nearshore wind turbines. Additionally, offshore wind turbines generate more power in the Omani peak electricity demand during the summer. Thus, offshore wind turbines have great advantages over land-based wind turbines in Oman. Overall, this work provides guidance on the deployment and production of offshore wind energy in Oman. A thorough study using bankable wind data along with various logistical considerations would still be required to turn offshore wind potential into real wind farms in Oman.

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Micro-scale classification of offshore wind energy resource ——A case study of the New Zealand

Journal of Cleaner Production ◽

10.1016/j.jclepro.2019.04.082 ◽

2019 ◽

Vol 226 ◽

pp. 133-141 ◽

Cited By ~ 5

Author(s):

Chong-wei Zheng ◽

Chong-yin Li ◽

Jian-jun Xu

Keyword(s):

New Zealand ◽

Wind Energy ◽

Energy Resource ◽

Offshore Wind ◽

Offshore Wind Energy ◽

Micro Scale ◽

Scale Classification

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Offshore wind energy – South Africa’s untapped resource

Journal of Energy in Southern Africa ◽

10.17159/2413-3051/2020/v31i4a7940 ◽

2020 ◽

Vol 31 (4) ◽

pp. 26-42

Author(s):

Gordon Rae ◽

Gareth Erfort

Keyword(s):

South Africa ◽

Wind Energy ◽

South African ◽

Electricity Generation ◽

Wind Farm ◽

Energy Resource ◽

Electricity Consumption ◽

Offshore Wind ◽

Offshore Wind Energy ◽

Multi Criteria Evaluation

In the context of the Anthropocene, the decoupling of carbon emissions from electricity generation is critical. South Africa has an ageing coal power fleet, which will gradually be decommissioned over the next 30 years. This creates substantial opportunity for a just transition towards a future energy mix with a high renewable energy penetration. Offshore wind technology is a clean electricity generation alternative that presents great power security and decarbonisation opportunity for South Africa. This study estimated the offshore wind energy resource available within South Africa’s exclusive economic zone (EEZ), using a geographic information system methodology. The available resource was estimated under four developmental scenarios. This study revealed that South Africa has an annual offshore wind energy production potential of 44.52 TWh at ocean depths of less than 50 m (Scenario 1) and 2 387.08 TWh at depths less than 1 000 m (Scenario 2). Furthermore, a GIS-based multi-criteria evaluation was conducted to determine the most suitable locations for offshore wind farm development within the South African EEZ. The following suitable offshore wind development regions were identified: Richards Bay, KwaDukuza, Durban, and Struis Bay. Based on South Africa’s annual electricity consumption of 297.8 TWh in 2018, OWE could theoretically supply approximately 15% and 800% of South Africa’s annual electricity demand with offshore wind development Scenario 1 and 2 respectively.

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