Wind resource modelling in complex terrain using different mesoscale–microscale coupling techniques

Abstract

Wind resource evaluation in two sites located in Portugal was performed using the mesoscale modelling system Weather Research and Forecasting (WRF) and the wind resource analysis tool commonly used within the wind power industry, the Wind Atlas Analysis and Application Program (WAsP) microscale model. Wind measurement campaigns were conducted in the selected sites, allowing for a comparison between in situ measurements and simulated wind, in terms of flow characteristics and energy yields estimates.Three different methodologies were tested, aiming to provide an overview of the benefits and limita -tions of these methodologies for wind resource estimation. In the first methodology the mesoscale model acts like ''virtual'' wind measuring stations, where wind data was computed by WRF for both sites and inserted directly as input in WAsP. In the second approach, the same procedure was followed but here the terrain in fluences induced by the mesoscale model low resolution terrain data were removed from the simulated wind data. In the third methodology, the simulated wind data is extracted at the top of the planetary boundary layer height for both sites, aiming to assess if the use of geostrophic winds (which, by definition, are not influenced by the local terrain) can bring any improvement in the models performance.The obtained results for the abovementioned methodologies were compared with those resulting from in situ measurements, in terms of mean wind speed, Weibull probability density function parameters and production estimates, considering the installation of one wind tur bine in each site. Results showed that the second tested approach is the one that produces values closest to the measured ones, and fairly acceptable deviations were found using this coupling technique in terms of estimated annual production. However, mesoscale output should not be used directly in win d farm sitting projects, mainly due to the mesoscale model terrain data poor resolution. Instead, the use of mesoscale output in microscale models should be seen as a valid alternative to in situ data mainly for preliminary wind resource assessments, although the application of mesoscale and microscale coupling in areas with complex topography should be done with extreme caution.

Using 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterranean

“…As mentioned, Carvalho et al recently showed for the Iberian Peninsula that ERAI should be considered the best reanalysis for nesting inside these results mesoscale wind simulations [18,20,21,22,23] with the NCEP-FNL and NCEP-GFS analysis being the best alternatives to ERAI [21]. Therefore, on this point concerning the use of ERAI as the best reanalysis that can be used to test a mesoscale model, we have revisited the sensitivity of the results in the estimation of potential offshore wind energy to the use of (or lack of) 3DVAR data assimilation every 6 hours in the D experiment (or no use of 3DVAR in the case of the N experiment).…”

“…In onshore wind resource prediction, these studies show that the WRF mesoscale model performs well when it is coupled with microscale models such as WAsP (Wind Atlas Analysis and Application Program), carefully taking into account those areas with a complex topography [18].The grid nudging and integration times of the simulations have also been tested for WRF, and the results suggest that errors can be minimized by choosing a suitable numerical and physical configuration with high resolution terrain data [19]. WRF sensitivity to different planetary boundary layer parametrization schemes has also been studied, and the best onshore or offshore evaluation results are associated with specific parametrization schemes [20].…”

“…Its performance has been evaluated for different onshore or offshore wide areas [18,19,20,21,22,23], and even for turbulence and wake studies around specific wind farms [24,25]. Additionally, WRF has been recently used for wind forecasting in short and lon-term, which currently constitutes a very important aspect of wind industry's electricity production and sales [26,27,28,29].…”

Wind Forecasting Based on the HARMONIE Model and Adaptive Finite Elements

“…In this paper, we propose a method for wind forecasting by coupling the HARMONIE mesoscale model with a local mass-consistent wind model specially suited for complex terrain ; similar coupling methods have been proposed by GASSET et al (2012) and CARVALHO et al (2013). HARMONIE is used experimentally at AEMET with promising results (NAVASCUÉ S et al 2013).…”

On the Improvement of Wind Power Predictions Based on Terrain Characteristics and Measurements of the Annual Energy Production

“…Carvalho et al [4] showed that these characteristics are significantly enhanced when dealing with a complex terrain, where the wind predictions are more difficult to achieve. Thus, the estimation of the wind resource, and more specifically the annual energy production (AEP) using the wind speed distribution of the IEC 61400-12-1 standard, might lead to significant uncertainties [5].…”