Engineering Mathematics for Energy System Analysis and Design

Applications are invited for postgraduate research leading to a PhD degree in Engineering Mathematics for Energy System Analysis and Design

Mathematical and computational methods are essential for the design and control of the integrated and interconnected energy systems of the future. Mathematical models are used for the analysis of experimental data to gain insight into different physical effects and to extract device and process parameters. For example, by using models for the heat transfer in domestic buildings the effect of various insulation materials can be simulated. Furthermore, mathematical models are used in combination with computational methods to optimise experiments over a wide range of parameters and configurations. This is often faster and more cost effective than by experiments alone. However, to get the most from mathematical modelling it is crucial to have a good understanding of the engineering application and to validate the models against experimental data.

In this project, the successful candidate will apply mathematical modelling and simulation to the optimal design, operation and control of energy systems. The particular problem can come from a large number of research topics in the School of Engineering. Possible areas are Carbon Capture, low carbon heating, hybrid renewable energy systems (see the attached figure) and energy storage. Depending on the chosen problem, the mathematical models will draw on different modelling techniques, such as empirical, semi-empirical or first principles. An important aspect of the project will be the efficient use of computational methods in the solution of the mathematical models and the feedback to the experimentalists. These methods could be numerical schemes for differential equations, numerical optimisation or analysis of large experimental data sets.

The successful candidate will develop a wide range of skills in the development and application of mathematical and computational methods for the analysis, optimisation and design of real-world energy systems. These skills will be widely applicable to the successful candidate’s future career.