Year: 2025
Type: article
Abstract: Organic Rankine Cycle (ORC) systems generate power from low to medium grade heat sources using organic working fluids instead of water [1]. In coal-fired applications, an ORC can be integrated to recover waste heat from flue gas or serve as a bottoming cycle, improving overall plant efficiency [2]. A principal control challenge in Organic Rankine Cycle systems involves regulating turbine inlet superheat within optimal bounds to simultaneously ensure operational integrity (preventing liquid droplet impingement through strict maintenance of vapor-phase working fluid) and maximize energy recovery efficiency [3]. This paper presents a comparative analysis of conventional Proportional-Integral-Derivative (PID) control and Model Predictive Control (MPC) frameworks for thermal regulation in a coal-fired Organic Rankine Cycle (ORC) system. A control-oriented dynamic model is developed based on the system’s thermodynamics, using a moving boundary evaporator model for accurate two-phase dynamics prediction [4]. This study demonstrates how Model Predictive Control (MPC) employs system dynamics modeling to forecast future states and enforce operational constraints such as temperature thresholds and pressure limits for performance optimization [5]. Simulation results under transient conditions, including heat input step changes and load ramps, reveal that MPC achieves superior regulation of working fluid superheat at the evaporator outlet, exhibiting 20-30% reductions in overshoot, 40% shorter settling times, and 35% lower integral absolute error compared to PID control. Furthermore, MPC maintains tighter set point tracking during ramp disturbances, with deviation magnitudes reduced by 50-65%. The findings establish MPC's capability to enhance superheat control stability while ensuring safer turbine operation through rigorous constraint enforcement in coal-fired Organic Rankine Cycle systems, ultimately improving cycle efficiency by 3-5% during transient operation.
Authors: Zariro Manzungu -, Victor Kuno -
Institution: Harare Institute of Technology
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411463456