Microgrid operation and planning under uncertainty

Abstract

The optimal planning and energy management of microgrids in the face of uncertain information is a challenging task. Microgrids have the ability to improve economical operation, reliability, and power quality of electric power systems. They offer excellent potential to mitigate inherent uncertainty and intermittency of renewable generation and facilitate higher penetration of these resources. In order to realize the potential benefits of microgrids, two requirements should be met. The first requirement is a practical model that captures the operational characteristics of a microgrid. This model then should be integrated with an efficient decision-making algorithm under uncertainty to effectively improve the economical operation and power quality. These requirements are the motivation behind this thesis. The objective of this thesis is first examining different methods for decision-making under uncertainty and comparing their characteristics. The second objective is proposing a detailed model that incorporates the operational and power quality constraints necessary for realistic modeling and secure operation of microgrids. These objectives are followed in the context of different planning problems including electric vehicles parking lot placement, reconfiguration, and day-ahead operation planning of microgrids.