Exploring the role of reanalysis data in simulating regional wind generation variability over Northern Ireland

Kubik, M. L., Brayshaw, D. J. ORCID: https://orcid.org/0000-0002-3927-4362, Coker, P. J. and Barlow, J. F. (2013) Exploring the role of reanalysis data in simulating regional wind generation variability over Northern Ireland. Renewable Energy, 57. pp. 558-561. ISSN 0960-1481 doi: 10.1016/j.renene.2013.02.012

Abstract/Summary

As wind generation increases, system impact studies rely on predictions of future generation and effective representation of wind variability. A well-established approach to investigate the impact of wind variability is to simulate generation using observations from 10 m meteorological mast-data. However, there are problems with relying purely on historical wind-speed records or generation histories: mast-data is often incomplete, not sited at a relevant wind generation sites, and recorded at the wrong altitude above ground (usually 10 m), each of which may distort the generation profile. A possible complimentary approach is to use reanalysis data, where data assimilation techniques are combined with state-of-the-art weather forecast models to produce complete gridded wind time-series over an area. Previous investigations of reanalysis datasets have placed an emphasis on comparing reanalysis to meteorological site records whereas this paper compares wind generation simulated using reanalysis data directly against historic wind generation records. Importantly, this comparison is conducted using raw reanalysis data (typical resolution ∼50 km), without relying on a computationally expensive “dynamical downscaling” for a particular target region. Although the raw reanalysis data cannot, by nature of its construction, represent the site-specific effects of sub-gridscale topography, it is nevertheless shown to be comparable to or better than the mast-based simulation in the region considered and it is therefore argued that raw reanalysis data may offer a number of significant advantages as a data source.