Model Predictive Control of fuel-cell-Car-based smart energy systems in the presence of uncertainty

Abstract

In this thesis, we design control algorithms for power scheduling of a fleet of fuel cell cars in a microgrid. Fuel cell cars are a relatively new type of vehicles. The driving force of these cars comes from an electrical motor and in order to generate the required electricity for the operation of the motor, the vehicle is equipped with a fuel cell system. The purpose of the fuel cell system is to convert the chemical energy of hydrogen into electricity. By considering the fact that fuel cell cars have the ability to generate electricity from hydrogen, these type of vehicles can be considered as a new type of flexible power plant. The idea of generating electricity inside a parking lot by using fuel cell cars is what we refer to as the Car as Power Plant (CaPP) concept. In this PhD thesis, we consider the power scheduling problem of a fleet of fuel cell cars in the CaPP concept. Several robust model predictive control methods are developed to determine the power generation schedule of the fuel cell cars inside the microgrid.