Performance enhancement of a small-scale organic Rankine cycle radial-inflow turbine through multi-objective optimization algorithm

An effective methodology that encompasses a mean-line design, three-dimensional CFD analysis and optimization and ORC system modelling of the small-scale ORC radial-inflow turbine is presented. Three-dimensional CFD analysis and a multi-objective optimization algorithm were achieved using ANSYS®17 CFX and Design Exploration based on 3D RANS with a k-omega SST turbulence model. The 3D optimization technique combines a design of the experiment, a response surface method and multi-objective method. The optimization of the blade geometry was performed using 20 design points for both nozzle and rotor blades, based on the B-splines’ technique to represent the blade angles and thickness distribution. The number of blades and rotor tip clearance were included as design parameters. The isentropic efficiency and power output were introduced as an optimization objective with two organic working fluids, namely isopentane and R245fa. The results of the optimized geometry with R245fa showed that the turbine's and cycle's thermal efficiencies were higher by 13.95% and 17.38% respectively, compared with a base-line design with a maximum power output of 5.415 kW. Such methodology is proved to be effective as it allows the enhancing of the turbine's and the ORC's system performance throughout to find the optimum blade shape of the turbine stage. •Small-scale radial-inflow turbine was designed and optimized.•ORC system modelling and optimization of radial-inflow turbine were integrated.•The 3D optimization based on Multi-objective genetic algorithm was conducted.•Higher turbine and thermal system efficiencies achieved with optimized turbine.