Book chapter
Space-time trajectories of wind power generation: Parameterized precision matrices under a Gaussian copula approach
Siemens A/S1
Department of Electrical Engineering, Technical University of Denmark2
Department of Applied Mathematics and Computer Science, Technical University of Denmark3
Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark4
CITIES - Centre for IT-Intelligent Energy Systems, Centers, Technical University of Denmark5
Emphasis is placed on generating space-time trajectories of wind power generation, consisting of paths sampled from high-dimensional joint predictive densities, describing wind power generation at a number of contiguous locations and successive lead times. A modelling approach taking advantage of the sparsity of precision matrices is introduced for the description of the underlying space-time dependence structure.
The proposed parametrization of the dependence structure accounts for important process characteristics such as lead-time-dependent conditional precisions and direction-dependent cross-correlations. Estimation is performed in a maximum likelihood framework. Based on a test case application in Denmark, with spatial dependencies over 15 areas and temporal ones for 43 hourly lead times (hence, for a dimension of n = 645), it is shown that accounting for space-time effects is crucial for generating skilful trajectories.
Language: | English |
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Publisher: | Springer |
Year: | 2015 |
Pages: | 267-296 |
Proceedings: | International Workshop on Industry Practices for Forecasting |
Series: | Lecture Notes in Statistics |
ISBN: | 3319187317 , 3319187325 , 9783319187310 and 9783319187327 |
ISSN: | 09300325 and 21977186 |
Types: | Book chapter |
DOI: | 10.1007/978-3-319-18732-7_14 |
ORCIDs: | Madsen, Henrik |