Compact modelling of Organic Rankine Cycle for waste heat recovery

Waste heat accounts for 20% to 50% of industrial energy input, and recovery of waste heat has attracted substantial interests worldwide from both academia and industry. Organic Rankine Cycle (ORC) can achieve better performance to recover low grade waste heat and an accurate ORC model is a key for the design of proper management and control strategy for ORC systems. In this paper, compact ARX and NARX models for ORC are built using a new identification method, namely Fast Recursive algorithm (FRA). Training and validation results on experimental data confirm that the developed compact ORC models can achieve good modelling accuracy and satisfactory generalization performance.