In addition to overcoming this notorious non-convexity barrier, our theory-inspired approach also highlights the importance of network connectivity for energy storage and electric vehicle charging. We show that there are clearly benefits in a joint optimization of energy storage and the power flow. Energy storage at demand buses can absorb the transients while the power loads are rebalanced. When the power price is low, energy can be stored in electric vehicle batteries. On the other hand, when the power price is high, users can first draw energy locally from the electric vehicle batteries before consuming the energy directly from the power grid network. The electric vehicle batteries play an interestingly dual role: they represent a new type of demand load to be managed and also as new energy storage resources (when power flows from the vehicle to grid) for smoothing the aggregate load in the system. This dual role can be realized by our distributed control algorithms in the Smart Grid and mobile computing software that run on wireless communication networks. The research innovations in this project have immense scientific value and have been published in top-tiered journal publications (the IEEE Transactions on Power Systems, the IEEE Journal of Selected Topics in Signal Processing and the IEEE Journal on Selected Areas in Communications).

Research into this joint flow and charging dynamic control and optimization has led to various collaborations around the world. Together with the California Institute of Technology (Caltech) and a Californian utility, we have studied how the power flow optimization and distributed control algorithms can be used for experimentation on a power microgrid installed on Catalina Island located southwest of Los Angeles, California. The impact of this project is even larger on its applicability to modern electric power smart grids as the society's reliance on sustainable energy continues to expand tremendously.