Optimisation of HAT-Cycles – With and Without CO2 Capture

In a world where distributed power generation and deregulation of energy markets are on everyone’s agenda, the need for highly efficient power plants with short lead times is greater than ever. Although at present combined cycles provide a solution, development of ever more advanced machines to increase efficiency and lower the environmental impact has led to high maintenance costs and a decrease in availability. The Humid Air Turbine (HAT) represents a different approach, suitable for distributed power generation in the medium power range. The HAT cycle, and other wet gas turbine cycles, which have been extensively studied during the last ten years, show as high an efficiency as that of combined cycles, but at a lower specific cost and, with inherently low emissions of NOx. Despite all research done no full-scale plant has been built as yet. CO2 capture is another concept widely studied in recent years. In the present study three HAT cycle configurations are investigated, two of them connected to a post-combustion CO2-capture plant. Thermodynamic and thermoeconomic optimisation of the plants was performed using genetic algorithms (GA), a robust optimisation technique based on Darwinian evolution theories. The three configurations studied were 1) a standard inter-cooled HAT cycle, referred to as the reference cycle, 2) the reference cycle together with an integrated CO2-capture plant taking the energy needed for the CO2 separation from the exhaust heat of the turbine, and 3) the reference cycle together with a CO2 capture plant, in which the energy is supplied by a separate bio-fuelled boiler. This third configuration enables all fossil-based CO2 to be separated. All power cycles were modelled using IPSEpro, a heat- and mass-balance software, employing advanced component models developed by the authors. It has an interface for optimisation and the possibility of employing user-defined objective functions. The impact of CO2 taxation was studied to determine showing which configuration is the most economical at the current fuel-price and tax-level.