Simultaneous Cycle Optimization and Fluid Selection for ORC Systems Accounting for the Effect of the Operating Conditions on Turbine Efficiency

Frontiers in Energy Research

White, Martin T.¹ 

[1] Department of Mechanical Engineering and Aeronautics, School of Mathematics, Computer Science and Engineering, City University of London, United Kingdom

关键词: Organic Rankine cycle (ORC);    ORC (Organic Rankine Cycle);    Small-scale;    Multi-objective optimisation;    Fluid selection;    CAMPD;    Radial turbine;   

DOI  :  10.3389/fenrg.2019.00050

学科分类：能源（综合）

来源: Frontiers

【 摘 要 】

The design of optimal organic Rankine cycle (ORC) systems requires the simultaneous identification of the optimal cycle architecture, operating conditions and working fluid, whilst accounting for the effect of these parameters on expander performance. In this paper, a novel method for predicting the design-point efficiency of a radial turbine is developed, which can predict the achievable efficiency based only on the thermodynamic conditions. This model is integrated into an optimisation framework in which the working fluid is modelled using the Peng-Robinson equation of state and the fluid parameters (i.e., critical temperature) are simultaneously optimised alongside the cycle conditions. This framework can evaluate recuperated and transcritical cycles, whilst heat-transfer area requirements are estimated based on representative overall heat-transfer coefficients. For a range of heat sources, a single-objective optimisation is first completed in which power output is maximised, which is then followed by a multi-objective optimisation in which the trade-off between power output and total heat-transfer area is investigated. It is demonstrated that the optimisation framework can simultaneously optimise the working fluid and cycle parameters, and identify whether a subcritical or transcritical cycle, with or without a recuperator, is best suited for a particular application, whilst accounting for the effect of these variables on the expander performance. This information is critical to identify optimal cycle configurations and working fluids that result in the best thermodynamic performance, yet exist in the design space in which feasible turbines can be designed. It is found that the optimal critical temperature does not vary significantly between different cycle architectures considered, and is not affected by whether a single or multi-objective optimisation is completed. However, including the expander performance model results in significantly different cycles to optimal thermodynamic cycles.

【 授权许可】

CC BY