Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources

Jianzhou Wang, Shanshan Qin, Shiqiang Jin and Jie Wu

Renewable and Sustainable Energy Reviews, 2015, vol. 42, issue C, 26-42

Abstract: Offshore wind resources are more abundant and stronger and they blow more consistently than land-based wind resources. While gale force winds are easier to hit on the sea, the strong wind vibration and wind loads may exert severe damage and shock to wind turbines and wind power grids, even resulting in power grid collapse. Thus, to develop offshore wind power, apart from accurate quantitative wind energy potential assessments, it is necessary to effectively estimate extreme wind speeds. Toward this purpose, this paper investigates the current status of extreme wind speeds and wind energy assessment from literature review. It turns out that much work on wind energy estimation has been performed, whereas relatively little research involves extreme wind speeds, the main challenge stemming from the limited availability of derived extreme winds. Then a GH method based on artificial intelligence optimization algorithms is developed to re-analyze future samples of extreme wind speeds. On the basis of the re-analyzed extreme samples, as well as the Generalized Extreme Value (GEV) and Gumbel models optimized by Cuckoo Search (CS) and Chaotic Particle Swarm Optimization (CPSO) algorithms, the potential risks of extreme wind speeds are conducted based on 23-year (1990–2012) historic wind speeds. Thus, in terms of wind speeds, a comprehensive estimation for offshore wind energy is initially implemented in Bohai Rim, China. The assessment shows that the study areas have high-strength wind power but are rarely subjected to extreme wind speeds, which implies that it is suitable for wind farm construction.

Keywords: Comprehensive estimation; Offshore wind energy/power; Extreme wind speeds; Distributional function; Model optimization (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (33)

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DOI: 10.1016/j.rser.2014.09.042

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