Nonlinear Model Predictive Control of an Autonomous Power System Based on Hydrocarbon Reforming and High Temperature Fuel Cell

Alexandros Kafetzis, Chrysovalantou Ziogou, Simira Papadopoulou, Spyridon Voutetakis and Panos Seferlis
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Alexandros Kafetzis: Chemical Process and Energy Resources Institute, Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Chrysovalantou Ziogou: Chemical Process and Energy Resources Institute, Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Simira Papadopoulou: Department of Industrial Engineering and Management, International Hellenic University, 57001 Thessaloniki, Greece
Spyridon Voutetakis: Chemical Process and Energy Resources Institute, Centre for Research and Technology Hellas, 57001 Thessaloniki, Greece
Panos Seferlis: Department of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

Energies, 2021, vol. 14, issue 5, 1-23

Abstract: The integration and control of energy systems for power generation consists of multiple heterogeneous subsystems, such as chemical, electrochemical, and thermal, and contains challenges that arise from the multi-way interactions due to complex dynamic responses among the involved subsystems. The main motivation of this work is to design the control system for an autonomous automated and sustainable system that meets a certain power demand profile. A systematic methodology for the integration and control of a hybrid system that converts liquefied petroleum gas (LPG) to hydrogen, which is subsequently used to generate electrical power in a high-temperature fuel cell that charges a Li-Ion battery unit, is presented. An advanced nonlinear model predictive control (NMPC) framework is implemented to achieve this goal. The operational objective is the satisfaction of power demand while maintaining operation within a safe region and ensuring thermal and chemical balance. The proposed NMPC framework based on experimentally validated models is evaluated through simulation for realistic operation scenarios that involve static and dynamic variations of the power load.

Keywords: high temperature polymer electrolyte membrane fuel cell; power system; LPG reforming; nonlinear model predictive control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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