Event-Triggered State Estimation for variable energy resources management

In recent years, the power generation portfolio has expanded to include variable energy resources (VERs) such as wind and solar generation to meet increasing energy demand and environmental objectives. These sources inject uncertain amounts of power at time scales faster and generally dissimilar to that previously found in typical load profiles. As a result, in order to keep the balance of load and generation, the state of all power system buses becomes highly variable. Conventional measurement and state estimation (SE) techniques under these conditions may introduce errors which may impede the acquisition of an accurate picture of the system state. This paper considers an Event Triggered State Estimation (ETSE) for power networks incorporating VER. The proposed framework represents an improvement over Classical State Estimation (CSE) as it captures the variability associated with the VER while maintaining a high fidelity of the power network states. The effectiveness of the ETSE is demonstrated as compared to existing CSE on a standard IEEE 14 bus system.