A Framework for Distributed Decision Making in Electric Energy Systems with Intermittent Resources

This thesis is motivated by the fact that the increasing presence of intermittent energy resources such as wind and photovoltaic power has raised many challenging questions to the electric energy system operations. Given that (1) most of these intermittent resources are geographically disperse, and (2) sensing and actuation devices are more affordable, a distributed decision-making framework becomes not only possible, but necessary for future electric energy systems. In the proposed framework, a group of energy converting components in the system is considered a module and is represented in terms of its local variables and the interaction variables between the modules and the transmission system. The dynamics of generator modules are characterized based on first principles, whereas dynamics of load modules are characterized based on the fast sampling data collected from from the Phasor Measurement Units (PMU). By incorporating the dynamics of load modules, the proposed dynamical model preserves the structure of the interconnected power system, which lends itself to online distributed analysis and control. This is contrasted by the conventional off-line simulation-based approach to integrating disperse intermittent resources. Based on the proposed model, we show that both the short term stabilization and longer term scheduling problems are solvable using a