Prediction models in complex terrain.

Prediction models in complex terrain.
I. Marti, Torben Skov Nielsen, Henrik Madsen, J. Navarro, C.G. Barquero
Abstract	The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence the performance of HIRLAM in particular with respect to wind predictions. To estimate the performance of the model two spatial resolutions (0,5 Deg. and 0.2 Deg.) and different sets of HIRLAM variables were used to predict wind speed and energy production. The predictions of energy production for the wind farms are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy production and HIRLAM predictions. The statistical models belong to the class of conditional parametric models. The models are estimated using local polynomial regression, but the estimation method is here extended to be adaptive in order to allow for slow changes in the system e.g. caused by the annual variations of the climate. The results show that HIRLAM wind speed predictions can be improved by considering other HIRLAM variables that wind speed e.g. pressure gradients, and increasing the spatial resolution of the HIRLAM model.
Keywords	Forecasting methods, Statistics, HIRLAM, Downscaling
Type	Conference paper [Without referee]
Conference	European Wind Energy Conference 2001, Copenhagen
Year	2001 Month July Vol. 1 No. 1 pp. 1248 Ed. Peter Helm
Publisher	WIP-Renewable Energies/ETA
Address	Sylvensteinstr.2, D-81369 Munchen/Piazza Savonarola, 10, I-50132 FLorence
ISBN / ISSN	88-900442-9-2/3-936338-09-4
BibTeX data	[bibtex]
IMM Group(s)	Mathematical Statistics