Discerning the spatial variations in offshore wind resources along the coast of China via dynamic downscaling

Yichao Liu, Daoyi Chen, Sunwei Li and P.W. Chan

Energy, 2018, vol. 160, issue C, 582-596

Abstract: An improved dynamic downscaling method is introduced in the present study to discern the spatial variations in offshore wind resources over the China coastal waters. In the improved method, the authors develop a novel pre-processing technique to provide the lateral boundary and initial conditions for the main dynamic downscaling process. In detail, the multivariate orthogonal decomposition is employed, at first, to extract the time-independent componential wind fields from the 30-year regional ECMWF meteorology data, which are then used to run the Weather Research and Forecast (WRF) model to produce the offshore wind field with high spatial resolutions from dynamic downscaling. Given the contribution of each componential wind field estimated in the decomposition, the WRF simulation results are subsequently recomposed into the final wind field showing wind resources along the coast of China. It has been found that the offshore wind resources are abundant over the South and East China Sea, especially in the Taiwan Strait where the maximum annual wind power density ∼ 800W/m2 is observed at the 90m height. Via the improved dynamic downscaling method, the small-scale features of the localized offshore wind fields are improved by ∼13% after comparing to the raw ERA-Interim data, which is used to facilitate the siting of offshore wind farms.

Keywords: Dynamic downscaling method; Multivariate orthogonal function; Wind power density; WRF simulation (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:160:y:2018:i:c:p:582-596

DOI: 10.1016/j.energy.2018.06.205

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