As the wind industry is developing, it is asking for more reliable short-term wind forecasts to better manage the wind farms’ operations and electricity production. Developing new wind farms also requires correct assessments of the long-term wind potentials to decide whether to install a wind farm at a specific location. This thesis is studying a new generation of numerical weather forecasting models, named mesoscale models, to see how they could answer those needs. It is held at the company Maïa Eolis which operates several wind farms in France. A mesoscale model, the Weather Research and Forecasting model (WRF), was chosen and used to generate high resolution forecasts based on lower resolution forecasts from NCEP’s Global Forecasting System. The stages for implementation of daily forecasts for the company’s wind farms were: explore and configure the model, automate the runs, develop post-processing tools and forecasts visualization software which was intended to be used by the management team. WRF was also used to downscale wind archives of NCEP’s Final Analysis and determine the possibility to use these in assessing wind potentials. Finally the precision of the model in both cases and for each wind farm was assessed by comparing attained data from the model with real power production.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-91322 |
| Date | January 2012 |
| Creators | Jourdier, Bénédicte |
| Publisher | KTH, Kraft- och värmeteknologi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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