Multi-objective optimisation of the humid air turbine

Optimisation of the Humid Air Turbine (HAT) power cycle has proven an interesting challenge in multi-variate and multi-objective optimisation. A multi-objective Tabu Search optimisation algorithm, developed in the Cambridge Engineering Design Centre, has been applied to this humid power cycle. A tradeoff surface is generated to investigate the impact of nine primary system control variables on the performance (efficiency, specific work and cost of electricity) of the system. This optimisation tool was chosen for its proven robustness and flexibility in handling highly constrained, multi-variate problems. The algorithm generates a Pareto-set of optimal candidate designs, allowing the designer to analyse the trade-off between performance measures such as efficiency and cost when selecting the ultimate system operating point. The study is primarily a global optimisation, with attention being paid to the primary system control variables: pressure ratio, turbine inlet temperature, IP/HP pressure split, water flow-rate distribution and heat exchanger effectiveness.