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OPTIMIZED EFFICIENCY MAPS AND NEW CORRELATION FOR PERFORMANCE PREDICTION OF ORC BASED ON RADIAL TURBINE FOR SMALL-SCALE APPLICATIONS


Go-down asme-orc2015 Tracking Number 190

Presentation:
Session: Session 7: Small-scale ORC's
Room: 1B Europe
Session start: 16:20 Mon 12 Oct 2015

Kiyarash Rahbar   kxr965@bham.ac.uk
Affifliation: University of Birmingham

Saad Mahmoud   mahmousm@bham.ac.uk
Affifliation: University of Birmingham

Raya Al-Dadah   r.k.al-dadah@bham.ac.uk
Affifliation: University of Birmingham


Topics: - System Design and Optimization (Topics), - Turbines (Topics), - Simulation and Design Tools (Topics), - Working Fluids (Topics), - I prefer Oral Presentation (Presentation Preference)

Abstract:

The expander is considered as the most critical component of the ORC. Radial inflow turbine exhibits unique advantages of high efficiency, compact structure and light weight compared to the axial turbine when employed in the small-scale applications such as distributed CHP systems. In most of the ORC studies the turbine efficiency is assumed as a constant input for the optimization of cycle without assuring that the specified turbine efficiency can be achieved by the imposed thermodynamic conditions. In addition, atypical properties of the high-density working fluid and the near-critical operating condition of the ORC requires the turbine design procedure and parameters to be customized for the ORC. This study presents the optimization of a radial ORC turbine for maximum efficiency using mean-line modelling and genetic algorithm (GA). In contrast to the previous studies, real gas equation of state and the most advanced and recent loss models are employed in the code to capture the non-ideal behaviour of the working fluid. The optimized turbine efficiency is achieved by the GA for a wide range of operating conditions and for four organic fluids (R123, R245fa, R1233zd and isobutane). Such results are presented through new generalized maps based on the non-dimensional parameters as the flow and loading coefficients, specific speed and specific diameter. Using regression analysis a new correlation for the turbine efficiency is also presented. These new maps and the correlation are preliminary steps toward improving the previous constant turbine efficacy assumption and have great potential to be integrated with the general optimization methods of the ORC.