Industrial and social level modelling
Process integration of chemical processes focuses on the design, optimization, operational optimization and control of chemical and biochemical processes. This relates to processes in the petroleum, petrochemical, chemical, pharmaceutical and food processing industries. The emphasis is on a holistic approach to the process, rather than concentrating on individual operations, or the phenomena occurring in individual operations. The Process Integration group in the Department of Chemical Engineering and Analytical Science is active both in developing new methodologies and in applying these to industrial processes.
Resilient energy system modelling
Ensuring the integrity and performance of complex energy networks and infrastructure.
Researchers working in this field develop and analyse complex models to capture the behaviour from individual energy system assets such as generators or power electronic converters, all the way through the emergent dynamic properties of interconnected and interdependent devices. We can’t play with the real systems so we are completely reliant on having high quality models that we can trust to develop our solutions with.
The modelling timescales can vary from capturing wave phenomena propagating in microseconds, through the dynamic variations and oscillations between various rotating machinery on a second by second basis, through to seasonal or yearly variations across entire systems.
Increasing dependence on renewable energy resources is leading to greater volatility and uncertainty in our networks and we exploit various statistical models to capture and explore this behaviour. These range from Monte Carlo (MC) simulations through to importance sampling and Markov Chain modelling to assess system reliability.
Process control is an important aspect of any industrial system. Control theory is an important area of research in the Department of Electrical and Electronic Engineering.
Sustainability is another key issue at this level of modelling. The Sustainable industrial systems group in the Department of Chemical Engineering and Analytical Science helps identify sustainable solutions for industrial systems on a life cycle basis, taking into account economic, environmental and social aspects.