Organic
Rankine Cycles (ORCs) generate power from low temperature
heat. To make the best use of the diverse low temperature heat sources,
the cycle is tailored to each application. The objective is to maximize
process performance by optimizing both process parameters and the
working fluid. Today, process optimization and working fluid selection
are typically addressed separately in a two-step approach: working
fluids are selected using heuristic knowledge; subsequently, the process
is optimized. Such an approach can lead to suboptimal solutions, since
the optimal fluid might be excluded by the heuristics. We therefore
present a framework for the holistic design of ORCs enabling the simultaneous
optimization of the process and the working fluid based on process
performance. The simultaneous optimization is achieved by exploiting
the rich molecular picture underlying the PC-SAFT equation of state
in a continuous-molecular targeting approach (CoMT-CAMD). To allow
for the prediction of caloric properties, a quantitative structure–property
relationship (QSPR) for the ideal gas heat capacity is proposed that
relies on pure component parameters of PC-SAFT. The framework is used
for the optimization of a geothermal ORC in a case study. A sound
holistic design of process and working fluid is achieved.