Statistical & Probabilistic Methodologies for Energy Systems
April 14th - 16th 2014, University of Warwick
Scope
On-going problems in both planning future capacity and the running of future power grids are producing many interesting statistical problems. The workshop will focus on developments in suitable stochastic (statistical and probabilistic) methodologies to address these problems.
A key feature of electrical energy systems is that supply and demand must be balanced on a minute-by-minute, or in some cases even a second-by-second, basis. They must further be balanced spatially to the extent that the capacity of the transmission network is not exceeded.
Changes to the generation mix driven by carbon dioxide reduction targets and the replacement of ageing gen¬eration capacity is making this increasingly difficulty. Wind power and other sources of renewable energy are highly variable and unpredictable, and a future dependency on these will create major challenges in the bal¬ancing of supply and demand. We require the capacity of these uncertain resources to be effectively utilised without compromising either adequacy of supply or the means to transmit it. In addition changes to electricity demand and metering technologies are exacerbating these problems, examples include the increased use of electric cars, smart meters and home generation.
Topics to be covered include:
- Real-time prediction of renewable-based energy and demand, focusing in particular on its spatiotemporal distribution.
- Development of computationally efficient real-time management methodologies of such large-scale systems.
- Stochastic methodologies to support decision making for planning of network reinforcement and generation capacity.
- Reliability analysis for future generation technologies.
- Stochastic modelling and analysis of relevant control algorithms for supply and demand side technologies.
Information
