Intelligent sense-making for smart grid stability

The power systems of the future - smart grids - will see an increase in both renewable energy sources and load demand, thus increasing the need for fast dynamic reconfiguration of system parameters to handle energy and load dispatches. Power systems will need to be monitored continuously to maintain stability under normal and abnormal operating conditions and when facing disturbances. A combination of system state prediction, dynamic power flow, system optimization, and solution stability checking will allow for a more reliable, affordable, efficient and clean power grid. The optimization and control systems on a smart grid will require a computational systems thinking capability to handle the uncertainties and variability that exist in a smart grid environment. The concept of sense-making based on computational intelligence methods, including neural networks, fuzzy logic and swarm intelligence, as well as online measurements from a smart grid to provide `situational´ awareness in the context of stability, is introduced in this paper.