Control of Supercritical Organic Rankine Cycle based Waste Heat Recovery System Using Conventional and Fuzzy Self-tuned PID Controllers
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This research develops a supercritical organic Rankine cycle (ORC) based waste heat recovery (WHR) system for control system simulation. In supercritical ORC-WHR systems, the evaporator is a main contributor to the thermal inertia of the system, which is greatly affected by transient heat sources during operation. In order to capture the thermal inertia of the system and reduce the computation time in the simulation process, a fuzzy-based dynamic evaporator model was developed and integrated with other component models to provide a complete dynamic ORC-WHR model. This paper presents two control strategies for the ORC-WHR system: evaporator temperature control and expander output control, and two control algorithms: a conventional PID controller and a fuzzy-based self-tuning PID controller. The performances of the proposed controllers are tested for set point tracking and disturbance rejection ability in the presence of steady and transient thermal input conditions. The robustness of the proposed controllers is investigated with respect to various operating conditions. The results show that the fuzzy self-tuning PID controller outperformed the conventional PID controller in terms of set point tracking and disturbance rejection ability at all conditions encountered in the paper.
KeywordsControl algorithms fuzzy logic organic Rankine cycle PID controller supercritical condition waste heat recovery
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