Address the grid data challenge by investigating statistical properties of realistic grids and developing a generative model to build appropriate synthetic grid test cases.

Produce power grid test cases with salable network size featuring the same kind of small-world topology and electrical characteristics found in realistic grids.

Study the uncertainty modeling of renewable generation and smart grid loads.

Examine their impacts on grid vulnerability to cascading failures.

Explore optimal approaches to encourage renewable integration by using energy storage, smart grid technology, and demand controls.

Study the impacts of distributed generation of renewable energy on the distribution network.

Identify the optimal placement of DG regarding both siting and sizing, and evaluate the maximum penetration threshold.

Examine the interdependence of local renewable source and load profiles, and determine the optimal approaches of voltage and frequency controls.

Explore the optimal load scheduling in the presence of dynamic electricity pricing in a distribution network with locally available solar PV or wind-base renewable generation.

Reduce the electricity cost and encourage installation of distributed renewables with consideration of power quality constraints and customer convenience.