Real-time spatio-temporal trend and level (T&L) filtering scheme for early detection of voltage instability
Discovering early signatures of voltage instability can enhance situational awareness and facilitate emergency control. Such signatures usually appear as decaying trends in load voltages and increase in reactive power output of generators. Discrete control actions such as frequent switching of load tap changer (LTC) and capacitor banks, that are otherwise unmonitored, can also be crucial indicators of a voltage problem. Hence, the authors propose a unified early warning scheme (EWS) for detecting voltage instability. To quantify and correlate spatial, temporal (spatio-temporal) trends and level changes, the authors use a multivariate, adaptive trend and level (T&L) filter. A unique feature of the proposed scheme is the signature authentication, by verifying simultaneity in T&L changes across multivariate time series. The authors show that, by extrapolating trends, limit violations in bus voltages and generator reactive power output can be estimated well in advance. Further, the level-change detection logic is shown to have the ability to detect frequent LTC-actions directly from the bus voltage time series. While the T&L filtering scheme is validated on field phasor measurement unit (PMU) datasets, EWS and emergency control is demonstrated on the classical 10-bus voltage stability test system.
