Model-Based Estimation of Large-Scale Interconnected Power Systems with Moving PHEV Loads

Power system dynamics change because of variations in distribution circuit, performance of power generation and behavior of load. An estimation of these dynamical behaviors can be achieved using mathematical models. Interconnected systems with shared state variables require specific models to demonstrate the influence of parameter variations on all areas. Estimation is particularly difficult when the system is influenced by random load variations such as moving plug-in hybrid electric vehicle (PHEV) loads. This paper introduces a new model-based estimation technique designed for large scale interconnected systems. This high performance state estimation demonstrated an accurate effective, realtime and computationally efficient approach. State estimations and their transient behavior were successfully obtained for a power system with random loads as high as 327 level-1 charging vehicles at various storage device charge levels.