Supervisors: Dr S Zachary and Dr V Shneer (Heriot-Watt University) and Prof G Harrison (Edinburgh University)
Sponsoring Company: National Grid plc.
PhD Student: Evgeny Vylegzhanin
Electrical power grids are complex networked systems in which demand and supply must be balanced both on a minute-by-minute basis and with respect to geographical location. However, the need to reduce carbon emissions and provide increased energy security means that in the future there will be a much greater reliance on renewable sources of energy, such as wind power, whose outputs are highly variable, and often unpredictable even on relatively short timescales. Thus, if excessive costs are to be avoided, there will be a need for a much greater reliance on both storage of electrical energy and time-shifting of demand (the latter may be achieved through, for example, the use of smart-grid technology), both to smooth out the greater variability in supply, and to cope with its much increased uncertainty.
The aim of the present project is to develop the necessary mathematical and statistical techniques for the management of such complex energy systems. This requires the development of sophisticated stochastic models for the behaviour of future networks, of statistical models for accurate dynamic prediction in the presence of uncertainty, and of optimization, game theory and microeconomic techniques for the management of the markets.