Abstract
Intermittent generations such as large-scale renewable energy increases the risk of instability in a power grid. In this paper, we introduce the concept of observability and its computational algorithms for power networks equipped with synchrophasors. The goal is to estimate the angles and its derivatives around unstable trajectories, the information that is critical for the detection of power network instabilities. The algorithm is developed to determine the number and the siting of synchrophasors in a power network so that the state of the system can be accurately estimated in the presence of instability. An unscented Kalman filter (UKF) is adopted as a tool to estimate the states that are not directly measured by synchrophasors. The theory and its computational algorithms are illustrated by using a 9-bus model with three generators.
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