Publication Date



Open access

Degree Type


Degree Name

Master of Science (MS)


Electrical and Computer Engineering (Engineering)

Date of Defense


First Committee Member

Zhenhua Jiang

Second Committee Member

Michael Swain

Third Committee Member

Miroslav Kubat


This thesis describes a systematical study, including multidisciplinary modeling, simulation, control, and optimization, of a fuel cell - gas turbine hybrid power system that aims to increase the system efficiency and decrease the energy costs by combining two power sources. The fuel cell-gas turbine hybrid power systems can utilize exhaust fuel and waste heat from fuel cells in the gas turbines to increase system efficiency. This research considers a hybrid power system consisting of an internally reforming solid oxide fuel cell and a gas turbine. In the hybrid power system, the anode exhaust, which contains the remainder of the fuel, is mixed with the cathode exhaust as well as an additional supply of fuel and compressed air and then burned in a catalytic oxidizer. The hot oxidizer exhaust is expanded through the turbine section, driving an electric generator. After leaving the gas turbine, the oxidizer exhaust passes through a heat recovery unit in which it preheats the compressed air that is to be supplied to the fuel cell and the oxidizer. This research concentrates on multidisciplinary modeling and simulation of the fuel cell-gas turbine hybrid power system. Different control strategies for the power sharing between the subsystems are investigated. Also, the power electronics interfaces and controls for the hybrid power system are discussed. Two different power sharing strategies are studied and compared. Simulation results are presented and analyzed. Transient response of the hybrid energy system is studied through time-domain simulation. In addition, in this effort, Particle Swarm Optimization (PSO) is used to optimize the power sharing for the hybrid power system to increase the efficiency and decrease the fuel consumption.


Hybrid Power System; Fuel Cell; Gas Turbine; Multidisciplinary Modeling; Particle Swarm Optimization