Providing expertise in the fundamentals of modelling stochastic problems, stability analysis of power systems and optimisation that can be utilized by the other strands.
Strand Lead: Prof Federico Milano
This strand provides platform research in mathematical modelling, for use by other strands and Cluster partners. Many quantities of interest to SEES Cluster partners are characterised by variability and uncertainty, e.g., carbon prices, fuel prices and wind power output. Stochastic processes describe the evolution of such quantities over time using suitably distributed and correlated random variables.
The objective is to provide expertise in the fundamentals of modelling stochastic problems that can be utilized by all partners within the Cluster. The theoretical directions within this strand are motivated by the application areas in the Cluster, and are pursued in close collaboration with the users of the modelling tools. This is facilitated by the SEES postdocs within this strand, who regularly visit collaborators within the Cluster, and work with them to understand their requirements for mathematical modelling.
The mathematical work in the strand is currently focused on stochastic processes (particularly stochastic differential equations and branching processes), stability assessment and optimisation problems. Goals include the development of tools for time domain and frequency analysis, unit commitment and security-constrained optimal power flow calculations, modelling of consumer behaviour, and investment decision-making under uncertainty.