Two Algorithms for the Reliable Estimation of Organic Rankine Cycle Performance

Abstract

As the demand grows for low-temperature waste heat recovery systems, organic Rankine cycles (ORCs), and other alternatives to traditional steam, Rankine cycles are becoming more common in industry. Although analytical tools exist that can predict the performance of a steam cycle in a given waste-heat application, the development of a similar tool for ORCs has been hampered by the large choice of possible working fluids. In this paper, two methods are presented with the aim of providing an estimate of the best performance possible for any ORC in a given industrial application. The first is a purely analytical approach assuming an idealized fluid, and the second compares real fluids through cycle simulations to select the most appropriate parameters for the application. The analytical approach provides a rough baseline for performance, while the simulation method refines the estimate to give predictions that are more consistent with the documented performance of ORC plants currently in operation. Together, the two approaches represent a robust means of quickly estimating the capability of an ORC plant and to allow quick comparisons with other technologies.