The number of distributed energy resources (DERs) and flexible loads such as photovoltaic (PV) panels, electric vehicles (EVs), and energy storage systems (ESSs) are rapidly growing at the consumer end. These small distributed devices connect to low voltage power distribution grids via power electronic interfaces that can support bi-directional power flows. Despite being small in size, if aggregated, these devices a provide significant portion of the energy and ancillary services (e.g., reactive power support, frequency regulation, load following) necessary for reliable and secure operation of electric power grids. In future distribution grids, with numerous such small active devices, real-time control and aggregation will entail computational challenges. The computational challenges further increase when the aggregation requires coordination with legacy grid control actions which involve integer decision variables, such as load tap changers, capacitor banks, and network switches. This CAREER project concentrates around solving operational and computational issues for distribution grids with large penetration of DERs and flexible loads. This CAREER project aims to develop: i) novel mixed-integer second order cone programming (MISOCP) models of distribution optimal power flow and aggregation, which are computationally tractable for practical-sized power grids with thousands of aggregation nodes, ii) distributed control algorithms in dispatching active and reactive power of DER and flexible loads in real time, and iii) a probabilistic dispatch model of the assets at the grid level and at the DER aggregation level that minimizes expected constraint violation of distribution grid operations. These distributed optimization and control models will provide dispatch solutions sufficiently fast that the aggregation at the distribution level could easily track grid signals for applications ranging over various time resolutions. The educational and outreach activities of this CAREER project include: i) to design advanced curriculum on distributed control and optimization to train on-campus and online undergraduate and graduate level power engineering students, ii) to motivate K-12 students in pursuing science, technology, engineering, and math (STEM) by providing them opportunities to participate on several activities at Michigan Tech's Smart Grid Operations Center (SGOC), and iii) to reach out to Hispanic students in Texas and Native American students in South Dakota through active demonstration of fundamental power engineering concepts by using Michigan Tech's Mobile Microgrid Laboratory.