| Historically, electric power distribution systems were considered passive subsystems served by the larger transmission grid. Recently, smart grid initiatives have driven the evolution of distribution systems into active systems with market-aware customers and distributed power generation. Along with more diverse and complex injections, contemporary distribution systems are equipped with additional sensing equipment, two-way communications networks, and advanced metering infrastructure (AMI). These are essential technologies that enable several core functions of a smart grid, including real-time monitoring and online control.;This thesis presents several tools for the online analysis and control of modern electric power distribution systems. "Online" refers to a control framework that can react to changing system conditions in order to maintain static security and meet different operating objectives. Specifically, the objective of this research is to integrate temporal information (i.e., forecasts) into distribution system analysis tools while maintaining fundamental engineering requirements by re-examining classical problems through a contemporary lens.;Connected by an underlying injection forecast model, three research topics are explored: 1) distribution load capability, 2) analytical time window selection for quasi-static time series (QSTS) analysis, and 3) distribution state estimation with explicit consideration of non-synchronized measurements. The work proposed here is a necessary step towards distribution system optimization in an online setting with uncertain and/or bidirectional power flows. |
