Optimization Control Of Organic Rankine Cycle Based Waste Heat Recovery Processes

Low temperature waste heat has widely existed in various industrial processes. Waste heat recovery has an important significance for improving utilization efficiency of energy. Organic Rankine Cycle (ORC), based on engineering thermodynamics, is the cycle in which an organic fluid (or a mixture)with low boiling point instead of water is adopted as working fluid to realize low-grade heat recovery. The ORC based waste heat recovery system can not only achieve energy recycling but also has a great meaning for environment protection, which has attracted widespread attention.In this paper, the optimization control of ORC based waste heat recovery processes has been fully researched and analyzed. The nonlinear model of ORC system is presented in detail. The model is linearized at a given operating point and after model order reduction, a low-order space model suitable for the design of control system is finally obtained.Taking into consideration the fluctuation of heat source, the conventional control method with constant set-point can not make full use of waste heat. Thus, the supervisory predictive control based process optimization control is proposed. The simulation experiments are carried out in the MATLAB environment, and the simulation shows that this algorithm can adjust and follow the set point in time according to the change of heat sources. Also, the simulation results show that, compared with the ordinary PI control, supervisory predictive control can further improve the economic efficiency of the system.