Research paper wins national prize

The paper 'Transient CO2 capture for open-cycle gas turbines in future energy systems' has won the Siemens PSE Model-Based Innovation 2021 runners-up prize.

Electricity Pylons

Siemens Process Systems Engineering (PSE) is a pioneer in provision of advanced process modelling tools and services for the emerging technologies of Model-Based Innovation and Model-Based Engineering.  Their gPROMS advanced process modelling software is widely used to provide quantification in support of academic research, particularly in areas of novel technology.  In acknowledgement of the role of gPROMS modelling in academic research, Siemens PSE offers annual prizes totalling €5000 for the best papers describing the use.  

Researchers Mathew WilkesSanjay Mukherjee and Dr Sol Brown have won the runners-up prize for their paper 'Transient CO2 capture for open-cycle gas turbines in future energy systems' published in Energy.

Energy systems globally are transitioning away from conventional fossil fuels. It is well known that the transition from a carbon-intense energy system requires balancing capacity, due to the realistic constraints created by a high penetration of intermittent renewables.  One such constraint is the need for increased system flexibility. The flexibility of an energy system is its ability to respond to fluctuations in generation and demand. In the UK, the National Grid has various reserve and balancing services used to correct generation imbalances and demand-side response. Electricity systems also rely on connected synchronous generators to provide grid inertia to minimise the frequency disturbances created by an imbalance between generation and demand. 

In complex electricity systems with a varied generation mix, the security of supply is important, and the quick-response nature of gas turbines is invaluable in providing system flexibility. Accompanied with post-combustion capture (PCC) of CO2, gas turbines can support the transition to a future low-carbon electricity system. This study presents the development and validation of a dynamic rate-based model of the benchmark CO2 absorption process, using 30 wt% monoethanolamine (MEA). The model is scaled up from pilot-scale to match the flue gas output from a modern small-scale gas turbine operating in open-cycle configuration. Simulations of various flexible operating scenarios shows the rapid transitioning between full and partial load is beneficial in delivering higher time-averaged CO2 capture rates, compared to the Baseload scenario where the PCC system is operated at full load for 5 h. Maintaining a constant liquid/gas (L/G) ratio results in 90.01% CO2 capture; however, this increases the energy demand due to constant reboiler steam flowrate. 

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