Modeling, Simulation and Operation Optimization of Molten Carbonate Fuel Cell System

Abstract

Molten Carbonate Fuel Cell (MCFC) has been emerging as a promising power system substituting conventional combustion engines. However, it is still challenging to comprehend its complex dynamics and operate the MCFC to meet varying demands due to its nonlinearity. This research develops a mathematical dynamic model for a MCFC system and PID auto-tuning control methodology. In Chapter 2, a MCFC system model is presented and validated with commercial data. The model consists of a MCFC stack model and mechanical balance of plant (M-BOP) models. Each model is developed based on mass balance and energy balance. The MCFC stack model has additional electrochemical model. Integrating the stack and M-BOP models, a MCFC system model is constructed and validated with commercial operation data. In Chapter 3, a MCFC operation optimization framework is proposed based on PID auto-tuning control using the MCFC system model. The MCFC system has complex dynamics and high nonlinearity due to its complicated configuration and interactive subsystems. To overcome such problem, a neural network model and gain scheduling technique are incorporated in the operation optimization PID control section. A case study is presented to illustrate the applicability of the control strategy.