WP3 – Dynamic control and optimization

Research partners: University of Liège – Energy Systems, Ghent University – SYSTeMS

In this work package a generalised knowledge about the control strategies of Organic Rankine Cycle systems is obtained for different applications (waste heat recovery, solar power production, biomass, geothermal,…). Also a detailed model based on physical insight and identified sub-models (i.e. grey models) for simulation purposes of an ORC is developed. This model should be able to capture both subcritical, as well as supercritical operating conditions. A simplified version of this simulator will be used for prediction purposes in a model-based control strategy (MPC), such as EPSAC (Extended Prediction Self-Adaptive Control). This simplified model can then be easily adapted online to offer useful information to the controller on changing process dynamics.

Further, useful/suitable input output variables are defined such that optimal performance, as defined by the user and boundary conditions, is obtained. This implies integrated design control methodology.

A MPC control strategy is developed. This control must be adapted to a wide range of working conditions and to transient operation. The goal is to exploit the two available degrees of freedom in order to achieve excellent part-load performance, and to maximise the heat recovery in transient conditions.

And a control strategy for fully automated start-up and shut down is developed, so the ORC module should be able to perform these tasks without the intervention of an operator. This control strategy should be integrated with the MPC during operating conditions, such that a smooth operation of the plant is ensured.

Finally, insight and general recommendations is provided on the dynamic behavior of ORCs, especially for supercritical operation. This knowledge is integrated into a handbook providing guidelines for the optimal control of ORC cycles.