What is the challenge? What is our innovation? What have we learned so far? Why is this important for our nation? The 21 st century electric power grid is experiencing a rise in the insertion of new technologies (i.e. wind and solar power generation, hybrid electric vehicles, computerized sensors, and smart meters). These technologies pose a number of complex challenges. Combine optimization and power models to improve the realism of power system expansion planning (Bent, Berscheid, and Toole: AAAI 2010) Greater efficiency The results of our project have yielded numerous significant findings to date, including how to upgrade the nation’s grid, new failure points, and the effectiveness of local control. This project seeks to address these challenges through the combination of sophisticated techniques from power engineering, optimization and control theory, computer science, information theory and statistics. The nation is investing a considerable amount of money in purchasing smart grid hardware and technology. This project provides the science of how to use that technology most effectively Expand and upgrade the grid to accommodate wind and solar generation Better control the daily operations of the grid, Mitigate intermittent effects associated with renewable generation Improve stability Improving stability Better system design Reduce carbon emissions Reduce dependence on foreign oil Reduce the frequency of large scale black outs Reduce consumer energy costs More robust and secure power network Integrating renewable energy Integrate physics based rare events analysis to provide better predictions of failure points in the power grid (Chertkov, Pan, and Stepanov: 2010) Design distributed reactive control over Photo-Voltaic – rich feeder Turitsyn, Sulc, Backhaus, Chertkov: IEEE PES 2010 & SmartGridComm 2010) Develop non-convex optimization technique for grid expansion planning (Johnson, Chertkov: IEEE CDC 2010) Estimation of the cost to upgrade power networks to meet nation’s 2030 renewable energy goals. (Toole, Fair Berscheid, and Bent: IEEE TD 2010) Discovery of new metrics for measuring distance to failure in real and synthetic power grids (Chertkov, Pan, and Stepanov: 2010) Robust Broadcast-Communication Control of Electric Vehicle Charging (Turitsyn, Sinitsyn, Backhaus, Chertkov: SmartGridComm 2010) Analysis of PHEV battery swapping stations for renewable energy storage (Pan, Bent, Berscheid, and Izrealevitz: 2010) For example: we address optimization and control challenges related to integration of Plug-in-Hybrid EV in US grid Support Energy Renewable Penetration Goals Contribute Algorithms for Homeland Security Address strategic problems at the intersection of energy, climate and infrastructure Support Missions of LANL Energy Security Center and Information Science and Technology Center Design of Distributed Algorithm for Efficient Switching over meshed power distribution system (Zdeborova, Decelle, Backhaus, Chertkov: PRE 2010 & HICCS 2010)