Organisers: Stan Zachary (Heriot-Watt), David Lenaghan (National Grid plc), Robert Leese (Industrial Mathematics KTN), Andrew Richards (National Grid plc), Sergey Foss (Heriot-Watt), James Cruise(Heriot-Watt), Chris Dent (Durham)

Background

A key feature of electrical energy systems is that supply and demand must be balanced on a minute-by-minute basis. They must further be spatially balanced to the extent that the capacity of the transmission network is not exceeded. At present these objectives are largely achieved, both in Britain and elsewhere, by predicting demand to within an unavoidable small error, and then scheduling generation so as to manage it.

However, wind power and other sources of renewable energy are highly variable and unpredictable sources of supply, and a likely future significant dependence on these will create major challenges for the energy industry. We require the capacity of these uncertain resources to be effectively utilised, resulting in a reduction in conventional generation when renewable capacity is available, without compromising either adequacy of supply or the means to transmit it. Further energy markets in such an uncertain environment need to be structured in such a way as to minimise incidences of transient market power and maximise economic benefit to the consumer.

These problems require the assistance of mathematics, and present major new challenges for mathematics itself – some of the latter arising from the complexity of time scales on which generation is scheduled and from the constraints imposed by transmission networks.

This workshop will provide an introduction to current modelling challenges in power systems for the benefit of systems mathematicians. It will begin with two days of technical tutorial talks from modelling experts already working in the field, followed by industrial problem-scoping and networking sessions.

The aims of the meeting are:

1. To address and make progress with some of the difficult problems now arising in large electrical energy networks (e.g. that supplying Great Britain) and concerned with the management of variability and uncertainty in these systems. These problems are primarily:
   
   
   1. the characterisation and prediction of complex patterns of variability, such as those arising from an increased reliance on renewables;
   
   
   2. the management of the system in response to uncertainty, via scheduling, the use of storage, and possible time-shifting of demand;
   
   
   3. the design of market mechanisms so as to ensure economically efficient operation of the overall system.
   
   
   The solution of these problems requires the expert application of systems mathematics, i.e. probability and stochastic modelling, statistics and optimization, together with strong computational expertise in these areas (further details are given below).



2. To set up sustainable and lasting industrial-academic partnerships in these areas, and also to obtain a greater mutual understanding between industry and academia of how they may better combine their respective approaches to work for the common good.

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