Economic Model Predictive Control of Organic Rankine Cycle Based Waste Heat Energy Conversion Systems

EasyChair Preprint 3474

Abstract

Organic Rankine cycle (ORC) has been widely used in low-grade waste heat recovery. Besides the safety and effectiveness issues, the economic operation and control of Organic Rankine cycle (ORC) systems have is becoming increasingly important. In this paper, an economic model predictive controller (EMPC) is developed, which directly uses an economic index of the organic Rankine cycle (ORC) system as the controller objective and realizes the economic optimization while maintaining the dynamic tracking performance. Compared with the traditional two-layer supervisory control, two main contributions can be achieved: (1) The online dynamic optimization is achieved which maximizes the unit net power recovery; (2) The single-layered architecture further enhances the real-time control performance and reduces the complexity of controller design. The numerical simulation results confirm the efficacy of the proposed controller design, meeting the industrial requirements while decreasing the payback time of the upfront installation costs.

Keyphrases: Economic Model Predictive Control, Energy, Organic Rankine Cycle, Rankine cycle, Waste heat recovery, control performance, controller design, economic cost function, economic efficiency, heat energy conversion, heat recovery

@booklet{EasyChair:3474,
  author    = {Shawn Li and Kang Li and Mingming Lin and Jinzhu Pu and Jianhua Zhang},
  title     = {Economic Model Predictive Control of Organic Rankine Cycle Based Waste Heat Energy Conversion Systems},
  howpublished = {EasyChair Preprint 3474},
  year      = {EasyChair, 2020}}