Mesoscale modelling for wind resource evaluation purposes.   A test case in complex terrain

Soares, Anderson; Pinto, Paulo; Pilão, Rosa

doi:10.24084/repqj08.433

Cited by 2 publications

(3 citation statements)

References 1 publication

(1 reference statement)

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“…WAsP is still the state of the art software code for microscale modelling of wind resources and overall wind assessment, with a 20 year track record of use by industry [6]. WAsP is especially designed for wind resource mapping, wind farm micro-sitting and energy estimate purposes.…”

Section: Wasp Microscale Modelmentioning

confidence: 99%

“…Currently, the state of the art in wind resource assessment is based on classical methods that use measured data recorded locally [6], and subsequently inserted as input in microscale models to assess the local wind resource. These methods are still the most reliable for an efficient and realistic planning of potential wind farm sites, meaning higher certainty in the expected available wind resource and lower associated investment risks, which are key prerequisites for the successful development of wind energy projects [7].…”

Section: Introductionmentioning

confidence: 99%

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

Carvalho

Rocha

Santos³

et al. 2013

Applied Energy

109

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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.

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Section: Wasp Microscale Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Carvalho

Rocha

Santos³

et al. 2013

Applied Energy

109

View full text Add to dashboard Cite

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“…Studies like Byrkjedal and Berge (2008), Chagas et al (2009) and Soares et al (2010) backup the interest of the use of meteorological models, and specifically the WRF model, in the wind simulation for wind energy purposes. These considerations show the importance of the wind power industry in Portugal, being also noticeable the lack of published literature that focuses on a detailed testing and analysis of these models performance on the wind simulation in Portugal, especially within a wind power context.…”

Section: Introductionmentioning

confidence: 99%

A sensitivity study of the WRF model in wind simulation for an area of high wind energy

Carvalho

Rocha

Gómez‐Gesteira

et al. 2012

Environmental Modelling & Software

280

150

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The performance of the Weather Research and Forecast (WRF) model in wind simulation was evaluated under different numerical a nd physical options for an area of Portugal, located in complex terrain and characterized by its significant wind energy resource. The grid nudging and integration time of the simulations were the tested numerical options. Since the goal is to simulate the near-surface wind, the physical parameterization schemes regarding the boundary layer were the ones under evaluation. Also, the influences of the local terrain complexity and simulation domain resolution on the model results were also studied. Data from three wind measuring stations located within the chosen area were compared with the model results, in terms of Root Mean Square Error, Standard Deviation Error and Bias. Wind speed histograms, occurrences and energy wind roses were also used for model evaluation. Globally, the model accurately reproduced the local wind regime, despite a significant underestimation of the wind speed. The wind direction is reasonably simulated by the model especially in wind regimes where there is a clear dominant sector, but in the presence of low wind speeds the characterization of the wind direction (observed and simulated) is very subjective and led to higher deviations between simulations and observations. Within the tested options, results show that the use of grid nudging in simulations that should not exceed an integration tim e of 2 days is the best numerical configuration, and the parameterization set composed by the physical schemes MM5eYonsei UniversityeNoah are the most suitable for this site. Results were poorer in sites with higher terrain complexity, mainly due to limita-tions of the terrain data supplied to the model. The increase of the simulation domain resolution alone is not enough to significantly improve the model performance. Results suggest that error minimization in the wind simulation can be achieved by testing and choosing a suitable numerical and physical con figuration for the region of interest together with the use of high resolution terrain data, if available.

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Mesoscale modelling for wind resource evaluation purposes. A test case in complex terrain

Cited by 2 publications

References 1 publication

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

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

A sensitivity study of the WRF model in wind simulation for an area of high wind energy

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