Experimental study of Predictive Control strategies for optimal operation of Organic Rankine Cycle systems

In this paper the performance of Model Predictive Control (MPC) and PID based strategies to optimally recover waste heat using Organic Rankine Cycle (ORC) technology is investigated. First the relationship between the evaporating temperature and the output power is experimentally evaluated, concluding that for some given heat source conditions there exists an optimal evaporating temperature which maximizes the energy production. Three different control strategies MPC and PID based are developed in order not only to maximize energy production but to ensure safety conditions in the machine. For the case of the MPC, the Extended Prediction Self-Adaptive Control (EPSAC) algorithm is considered in this study as it uses input/output models for prediction, avoiding the need of state estimators, making of it a suitable tool for industrial applications. The experimental results obtained on a 11kWe pilot plant show that the constrained EPSAC-MPC outperforms PID based strategies, as it allows to accurately regulate the evaporating temperature with a lower control effort while keeping the superheating in a safer operating range.