Unit commitment under Uncertainty

Abstract

This thesis aims to propose several mathematical formulations and solution algorithms to Unit Commitment (UC) problems in the presence of uncertainty. The UC problems determine the optimal start-up/shut-down schedules and generating capacities of all units over an operation horizon in order to minimize the total operating cost with subject to various system constraints. The thesis mainly focuses on two types of randomness, namely, the unavailability of generators and the variability of demand and renewable generation. The system uncertainties are incorporated into the UC formulation under different frameworks such as stochastic programming and robust optimization. Extensive numerical studies are conducted to evaluate and compare the computational experience and to investigate the impact of uncertainties on system reliability among different methodologies. It is shown that system reliability and algorithm efficiency can be enhanced when system uncertainties are effectively modeled. These results help to provide valuable insights for improving system operations.