Optimization Of Organic Rankine Cycle System And Investigaton On Performance Of Radial Flow Turbine

With the increase of energy demand and the reduction of fossil fuel reserves, more and more attention has been placed to the utilization of low-grade heat sources. Organic Rankine cycle (ORC) can effectively recover the low-grade waste heat. This paper mainly researched the analyzation and optimization of system parameters, and the thermal design and optimization of key equipment axial flow turbine.Based on the energy equation in the heat transfer process between the heat source and working fluid and the derivative analyzation of temperature difference between hot side and cold side, the variation of the position of pitch point temperature difference (PPTD) with the system parameters was obtained and the heat transfer model between the heat source and working fluid was established. The heat transfer model showed that the position of PPTD can be directly determined by using the heat source temperature and characteristic temperature regarded as constant for one kind of work fluid. When the heat source temperature was greater than characteristic temperature, the PPTD was at the inlet temperature of working fluid in the evaporator. When the heat source temperature was less than characteristic temperature, the PPTD was at the evaporation temperature of working fluid.According to the heat transfer model, approximate or experience thermodynamic formulas and basic ORC model, the thermodynamic theoretical model of the ORC was established. Based on this theoretical model, the effects of the evaporation temperature, condensation temperature, superheat degree, internal heat exchanger and heat source temperature on the net power output and thermal efficiency were analyzed. The comparison results calculated by using the theoretical model and simulation method verified the accuracy of the model. The results showed that the effects of the system parameters on the system performance were dependent on the position of PPTD. By simplifying the theoretical model, the simplified theoretical model was obtained. The optimal evaporation temperature was deduced from the simplified theoretical model. The comparison results calculated by using the theoretical model and simulation method verified the accuracy of the formulas. Based on the parameters analyzation above, the analyzation and optimization of the evaporation temperature, condensation temperature and heat source temperature were performed. The results of ORC system analyzation found that the increase of superheat degree couldn’t improve the net power output and thermal efficiency. The internal heat exchanger could improve the thermal efficiency and had small effect on the net power output. The thermal efficiency increased with the increase in the evaporation temperature. When the heat source temperature was greater than characteristic temperature, the net power output increased with the increase in the evaporation temperature; when the heat source temperature was less than characteristic temperature, there existed optimal evaporation temperature to maximize the net power output. There existed the optimal condensation temperature to maximize the net power output and thermal efficiency.The expansion characters of working fluid relating to the Mach number, flow area and near critical expansion were analyzed. The AMDCKO loss predication model was selected according to the expansion characters. The blade structure parameters analyzation was performed and 8 structure parameters requiring to be optimized were obtained:relative pitch of nozzle, relative pitch of rotor blade, incidence of nozzle, incidence of rotor blade, blade inlet angle of nozzle, degree of reaction, speed ratio and diameter ratio. Based on the AMDCKO loss predication model, fitting the relevant charts in the model and selecting the interstage efficiency as optimization objective, the 8 parameters optimization of the axial flow turbine were performed by using the genetic algorithm. Then the method to determine the real throat position and local speed of sound was presented by using real working fluid physical property and loss value.Finally, based on the MATLAB and the body content, this paper wrote the functions correlating the processes of ORC and composed the ORC tool by all process functions. Using the ORC tool, the functions could be called to perform the analyzation and optimization of system parameters, and the thermal design and optimization of the axial flow turbine.