Hybrid system models and control: putting together the pieces of the energy jigsaw
The planned expansion of the different national energy-related systems (generation, transportation, distribution, transformation) and the production of electricity from renewable sources entail significant challenges due to the unique characteristics of the sector worldwide. The dynamics of energy networks (including renewable generation sources) are highly nonlinear, combine continuous and discrete, smooth and abrupt dynamics, and are subject to discontinuous operation and a wide range of external impacts. Under this scenario, there is a need to analyse the structural vulnerability of the energy network and recommend ways to maintain its robustness despite contingencies (for example, changes in the supply, imbalances between generation and load, random equipment failures, and targeted attacks or damage to the infrastructure).
The aim of this research is to model and analyse different scenarios in complex energy grids, with the ultimate goal of identifying behaviour patterns that degrade the performance of the entire network. The theoretical framework to use is that of hybrid systems, which brings together dynamical analysis tools, control engineering methods and computational models (mainly, hybrid automata). Since one of the purposes is to automate as much as possible the decision-making and monitoring processes, advanced monitoring systems can be derived from formal verification techniques, and used in order to test the performance of the network, and, if necessary to modify its behaviour or topology to meet desired specifications. Contributions of this project are envisaged as mainly theoretical, and key scenarios will be simulated. This work will be a stepping stone for future research in large-scale distribution networks. This research would be part of the project DYVERSE (DYnamical-driven VERification of Systems with Energy considerations).
Candidates who have been offered a place for PhD study in the School of Computer Science may be considered for funding by the School. Further details on School funding can be found at: http://www.cs.manchester.ac.uk/study/postgraduate-research/programmes/phd/funding/school-studentships/.
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