Model Predictive Control of Coal Fired Organic Rankine Cycle Systems

Zariro Manzungu; Victor Kuno

doi:10.71097/IJSAT.v16.i2.6379

Model Predictive Control of Coal Fired Organic Rankine Cycle Systems

Author(s)	Zariro Manzungu, Victor Kuno
Country	Zimbabwe
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.
Keywords	Organic Rankine Cycle (ORC), Model Predictive Control, Superheat Control, Coal-Fired Power, Dynamic Modelling, PID Control
Field	Computer > Automation / Robotics
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-06-18
DOI	https://doi.org/10.71097/IJSAT.v16.i2.6379
Short DOI	https://doi.org/g9qqxm

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Model Predictive Control of Coal Fired Organic Rankine Cycle Systems

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