Model Predictive Control of Coal Fired Organic Rankine Cycle Systems

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.

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Publication Details

Journal
International Journal on Science and Technology
Published
2025-06-18
DOI
https://doi.org/10.71097/ijsat.v16.i2.6379
Primary Topic
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Type
article
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article

Model Predictive Control of Coal Fired Organic Rankine Cycle Systems

Zariro Manzungu -, Victor Kuno -
International Journal on Science and Technology
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
article

Model Predictive Control of Coal Fired Organic Rankine Cycle Systems

Zariro Manzungu -, Victor Kuno -
article en

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.

International Journal on Science and TechnologyVol. 16(2)
Affordable and clean energy
Openalex Percentile: Top 86%
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
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