Browsing by Author "Fernandes, Miguel"
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- Impacte da assimilação de dados de vento provenientes de satélite em ambiente offshore: caso de estudo da BerlengaPublication . Fernandes, Miguel; Costa, Paula Silva; Estanqueiro, AnaCom o acentuado desenvolvimento da capacidade de produção de energia eólica onshore, onde Portugal já excede,actualmente, 3500 MW de capacidade instalada, é de esperar que este número ascenda a patamares muito elevados, tendo em conta os objectivos ambiciosos que a União Europeia planeia para o sector até 2020, prevendo-se que, em 2013, Portugal atinja a meta dos 5100M de capacidade instalada. No entanto, o recurso eólico onshore nacional não é infinito, tendo o LNEG já estimado uma meta nacional para a capacidade eólica sustentável onshore para Portugal Continental de, aproximadamente, 6000MW [1], capacidade só ultrapassável com a libertação de região actualmente protegidas ambientalmente de forma severa, bem como com a introdução de impactos naõ desprezáveis sobre as populações, que seria desejável evitar. Desta forma, e para um horizonte temporal além de 2013, há que fomentar e redireccionar as oportunidades de investimento do sector para outro nicho de mercado que se espera emergente, e que é o aproveitamento da energia eólica offshore que o País dispõe [2].
- Improving offshore atmospheric mesoscale model results : the case study of BerlengasPublication . Costa, Paula Silva; Fernandes, Miguel; Estanqueiro, Ana
- Improving offshore wind resource assessments using a data assimilation techniquePublication . Fernandes, Miguel; Costa, Paula Silva; Estanqueiro, AnaWind research and industry partners in collaboration with the EU have created the FP7 NORSEWInD project with the main objective of delivering to the North, Baltic and Irish Sea areas high quality wind atlases for offshore wind resource assessment. The state-of-the-art atmospheric mesoscale model WRF is used to map the wind resource at 90m a.g.l. for the North Sea area. A model domain with a spatial resolution of 20x20 km is used to simulate a winter and a summer month (November 2008 and July 2009). It is coupled with a Newtonian relaxation assimilation technique to ingest surface wind data provided from QuikSCAT (QS) satellite and sea surface temperature (SST) data from GHRSST Level 4 analysis. Wind results from the model are validated against observational data from the anemometric mast FINO1 and the spatial improvement of the average wind field at 90 m a.g.l is calculated. Improvements of more than 5% were obtained from using data assimilation on the overall domain. Each source has shown a distinct impact on the analyzed periods. The QS assimilation had higher impact during the summer period whereas SST assimilation was significant during the winter period. At FINO 1 location, improvements on the vertical wind profile were obtained from the SST assimilation. The MAE and RMSE statistical parameters were slightly improved.
- Offshore wind field: Application of statistical models as a spatial validation techniquePublication . Marujo, R.; Costa, Paula Silva; Fernandes, Miguel; Estanqueiro, AnaGenerally, atmospheric mesoscale models are used as tools to perform wind atlases. In recent decades, significant efforts have been applied to the development and improvement of this kind of models to reduce their systematic errors. These ones are assessed when model results are compared with observations. In practice, such errors could be statistically corrected if observational data was available for the same area. A deviation matrix of the wind field between WRF (Weather Research and Forecasting) mesoscale model and wind data retrieved from the QuiKSCAT satellite was obtained by the application of two statistical techniques – kriging interpolation and composite method. The spatial validation performance was evaluated with observational wind data from an anemometric mast installed on Berlengas islet since November 2006 to the present. The following are a preliminary assessment of the statistical methods as spatial validation techniques. These are a part of the spatial validation methodology to be used within the EU FP7 NORSEWInD project.
- PortugalPublication . Fernandes, Miguel; Simões, Teresa; Estanqueiro, AnaIn 2010 electric energy consumption grew 4.7% in Portugal reaching 52.2 TWh, the highest annual value recorded. The wind sector continued to grow although at half rate of 2009. Presently Portugal accounts for an installed capacity of 3,987 MW, which accounted for 17% of the country's electric demand.
- PortugalPublication . Fernandes, Miguel; Marujo, R.; Simões, Teresa; Estanqueiro, AnaDuring 2011, Portugal experienced a strong reduction of electricity demand. With a decrease of 2.3%, the total consumption was 50.5 TWh (1). Due to a mild winter season, the most relevant renewable generation facilities (hydro and wind) experienced a strong production reduction in comparison with 2010. In 2011, Portuguese wind farms produced 21 GWh less than the previous year. It is only because of the decrease in consumption that wind penetration achieved a value of 18%. The growth of the wind sector has maintained the pace of 2010, and 315 MW were added. This amounts to a total installed capacity of 4,302 MW, representing 22% of the electric system’s installed capacity (1). In November 2011, a milestone for Portuguese offshore wind development was achieved with the successful deployment of its first offshore floating wind turbine – WindFloat (opening photo).
- The contribution of a wind data assimilation scheme to improve offshore atmospheric mesoscale model results: The case study of BerlengasPublication . Costa, Paula Silva; Fernandes, Miguel; Estanqueiro, Ana
- Using data assimilation in mesoscale numerical modeling to map offshore wind resourcePublication . Fernandes, Miguel; Costa, Paula Silva; Simões, Teresa; Estanqueiro, Anadata from GHRSST Level 4 analysis have been ingested to an atmospheric mesoscale numerical model using a Newtonian relaxation assimilation technique. The mesoscale model WRF was used to map the wind resource at 90 m a.g.l. for the North Sea area. A model domain with a spatial resolution of 20x20 km was used to simulate a winter and a summer month, November 2008 and July 2009. The modeled wind results have been validated against observational data from the anemometric mast FINO1. A spatial improvement of the average wind field at 90 m a.g.l. from the observational data has been assessed. Each assimilated data source has shown a distinct impact. The QS assimilation had higher impact during the summer period while the SST assimilation during the winter period. Improvements of 5% and more were obtained from using data assimilation on the overall domain. Validation with the FINO1 anemometric mast shows improvements on the average vertical wind profile while error statistical parameters were only slightly improved.
- Using data assimilation in mesoscale numerical modeling to map offshore wind resourcePublication . Fernandes, Miguel; Costa, Paula Silva; Simões, Teresa; Estanqueiro, Ana
- Validation of an offshore wind atlas using the satellite data available at the coastal regions of PortugalPublication . Marujo, R.; Costa, Paula Silva; Fernandes, Miguel; Simões, Teresa; Estanqueiro, Ana