An Improved Analysis Method for Organic Rankine Cycles Based on Radial-Inflow Turbine Efficiency Prediction

Abstract

The organic Rankine cycle (ORC) has been demonstrated to be an effective method for converting low-grade heat energy into electricity. This paper proposes an improved analysis method for the ORC system. A coupling model of the ORC system with a radial-inflow turbine efficiency prediction model is presented. Multi-objective optimization was conducted for a constant turbine efficiency ORC system (ORCCTE) and a predicted turbine efficiency ORC system (ORCDTE), and the optimization results were compared. Additionally, a sensitivity analysis was conducted with respect to the heat source temperature and the ambient temperature. It can be found that the predicted turbine efficiency decreases with the increasing evaporation temperature, and increases with the increasing condensation temperature. The turbine efficiency is not constant and it varies with operating conditions. The distribution of the Pareto frontier for ORCCTE system and ORCCTE system is different. Compared with the ORCCTE system, the ORCDTE system has a lower optimal evaporation temperature, but a higher optimal condensation temperature. The deviation between the predicted turbine efficiency and the constant turbine efficiency increases with the increasing heat source temperature but decreases with the increasing ambient temperature. Thus, the difference in the theoretical analysis results between ORCCTE system and ORCDTE system increases with the increasing heat source temperature but decreases with the increasing ambient temperature.

Keywords

• organic Rankine cycle
• predicted turbine efficiency
• turbine efficiency prediction model
• multi-objective optimization
• sensitivity analysis