Browsing by Author "Pinto, P."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
- Evaluation of MCP correlation algorithms applied to wind data seriesPublication . Moreira, A.; Rocha, T.; Mendonça, J.; Pilão, R.; Pinto, P.(Objectives) This work aimed to develop methodologies for analyzing statistical correlations among wind data series using various Measure-Correlate-Predict (MCP) methods, with the goal of selecting the most suitable method for extrapolating long-term data with minimal associated uncertainty. Furthermore, the study intends to investigate how the concurrent period used to build the correlation can affect the performance indicators of MCP methods.
- Insights on the use of wind speed vertical extrapolation methodsPublication . Pintor, A.; Pinto, C.; Mendonça, J.; Pilão, Rosa Maria; Pinto, P.The present work aims to study the influence of using different methods for wind speed extrapolation in energy production calculations. A dataset of 21 meteorological masts from several landscape characteristics and locations, with at least one year of 10-minute wind speed/direction data, was used as the basis for calculations. Both the power law through estimation of wind shear coefficients, and the logarithmic-based profile using WAsP, were used as mathematical models for predicting wind shear. Wind speed extrapolation was performed either from the top-most height, using a distance method that incorporated all measurement heights, or using the function for wind shear coefficient prediction. It was found that using the logarithmicbased profile was the less reliable of all studied methods. The study showed that the most accurate method was the power law with wind shear coefficients estimated from the two upper heights closest to the extrapolation height, by wind direction sector of 30º, and the wind speeds extrapolation from the topmost height of the two. It is suggested that the use of this method reduces uncertainty in AEP estimates.
- Representative period of measurements for wind regime characterization in Dobrogea region, RomaniaPublication . Pilão, R.; Pinto, P.; Guedes, R.The proposed work aims to characterize the inter-annual variability of the mean wind speed for the Dobrogea region of Romania in order to determine the minimum local wind measurements period for its wind regime characterization. To achieve this, wind data from local wind measurements at meteorological stations in operation over the past 6 years and installed in different sites of the region were analyzed. In a second stage, the NCEP/NCAR reanalysis data base for that region was validated by comparison with the local measurements and the last 20 years were used for the characterization of the inter-annual variability of the mean wind velocity. As expected, the data from local wind measurements indicate that the maximum deviation of the mean wind speed decreases continually with the increasing of the period used in their determination, although at a decreasing rate. The use of reanalysis data for the period of the measurements made in the different sites showed that data from the NCEP/NCAR represent in an acceptable way the mean inter-annual variability for the measurement sites tested. The findings point out that the industry standard figures for annual wind variability can be conservative for the Dobrogea region. This will have a direct impact on pre-construction estimates of wind farm production and on financing and debt rising for the projects. For the Dobrogea region, the studied data pointed out that the inter-annual variability of mean annual wind speed could be much lower than typical wind industry standard figures. Moreover, the evolution of inter-annual variability with the number of consecutive years of data appears slightly less conservative than the evolution typically assumed by the industry. The test case presented highlighted the significant drop in the overall uncertainty on wind farm energy yield estimates between 1 and 2 years of observed wind data. This study should be repeated for other regions with wind farm developments, quite specially those more distant from Central Europe/UK (where the industry standard practices were primarily derived). NCEP/NCAR reanalysis can be a very useful tool for this kind of studies (being freely available and global) but its use for inter-annual wind variability should be tested in each case.