Spatial-Temporal Uncertainty in Energy Systems (SPATUS)
SPATUS is a Thematic Research Group funded by UiO:Energy
About the project
The reduction of carbon emission along with meeting increased demand for electricity is a major challenge in most power systems worldwide. The future carbon emission targets can only be met by an increased share of renewable power generation together with nuclear. Power generated by wind and photovoltaic (PV) are intermittent, and depend both on underlying weather factors like cloud cover and wind, as well as temperature which also is a fundamental driver of demand. In this TRG we propose to develop new and sophisticated dynamical models for temperature, wind and cloud cover which explains the uncertainty in their time and space evolution (so-called “spatial-temporal random fields”), in particular, the space-time dependencies and marginal distribution. The spatial-temporal random fields will combine physical dynamics with a quantification of the uncertainty inherent in weather dynamics. Furthermore, the TRG will have a particular view towards the stochastic modelling of clouds, a field vastly open for new and exciting mathematical modeling and analysis with impact on the forecasting and prediction of PV production. The new random models will be suitable for several applications to energy systems. We aim at studying the uncertain production from wind and PV installations based on the wind, temperature and cloud cover pattern. Further, in a geographically wider model we analyse the optimal spatial allocation of PV installations and wind parks under constraints on capacity and societal/political feasibility. The goal of the optimisation is to ensure the best possible stability in the production patterns from the locally intermittent energy generators. Such a study will heavily depend on the spatial correlation structure of the weather fields. Finally, we aim at upscaling our spatial-temporal models for the weather variables to analyse the optimal development of the energy system as a whole under given targets for emissions. Optimality will take into account economic and environmental restrictions as well as prospected demand pattern.
The TRG will be a collaboration between the Departments of Mathematics and Technology Systems, UiO. It will also involve a collaboration with experts in high-dimensional stochastics and energy systems from Universities of Vienna and Reading. A PhD and post doc will be trained in the TRG.
The SPATUS TRG is a collaboration between the Departments of Mathematics and Technology Systems (ITS), at the Faculty for Mathematics and Natural Sciences at UiO. The TRG is led by professor Fred Espen Benth (Mathematics), who is also a principal investigator in the TRG together with associate professor Marianne Zeyringer (ITS). The two-year program will involve active collaboration with associate professor Christa Cuchiero from Vienna University of Economics and Business, and associate professor David Brayshaw from Reading.
You can read the project description here.