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Durham University

Durham Energy Institute

Past Events

Find out about some of the previous events held by Durham Energy Institute:

Quantifying uncertainty in energy system models

3rd March 2016, 13:00 to 14:00, E245, School of Engineering & Computing Science, Dr Amy Wilson

Computer models of energy systems are widely used to help make evidence-based policy decisions in both industry and government. These decisions can be associated with large costs, for example the cost of a new support scheme for renewable energy, or the cost of securing extra generating capacity to improve the adequacy of electricity supply. It is therefore important to make the best decision possible with the information available and as part of this it is critical that any uncertainties associated with the outputs of a computer model are quantified and accounted for in the decision-making process.

Such uncertainties may arise because no computer model can perfectly replicate the complex real-world interactions making up an energy system. In addition, outputs from computer models are often heavily dependent on uncertain inputs (e.g. electricity demand in future years).

This talk will present a general framework for quantifying uncertainty in large computer models. A study of the uncertainties associated with one particular model will be discussed. This model, known as the Dynamic Dispatch Model (DDM), was used by DECC and National Grid to set the maximum support available to different renewable technologies in the 2015 contract for difference auction.

Amy Wilson is a post-doctoral research associate in the department of mathematical sciences at Durham University and a DEI fellow. She is a researcher on an EPSRC project which aims to improve methods for quantifying uncertainty in energy system models. Prior to joining Durham University, Amy completed a PhD in forensic statistics at the University of Edinburgh in collaboration with Mass Spec Analytical Ltd., a private forensic science provider.

Amy's research is in the area of statistical modelling for energy systems, with a focus on the modelling of uncertainty in large computer models. Particular applications she has worked on include the development of methods for capacity adequacy assessment in Great Britain and the study of the effect of uncertainties on the outputs of a generation investment computer model used by the Department for Energy and Climate Change.

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