PMU-BASED MONITORING AND CONTROL OF POWER SYSTEM DYNAMICS

Guanqun Wang

For electric power systems, it is critical to maintain system stability following severe disturbances. In recent years, Phasor Measurement Units (PMUs), or synchrophasors, have been deployed in large scale on the power grids, providing unprecedented visibility into power system dynamics. The new and accurate measurement device is an enabling technology for power grids to perform wide area monitoring and control of system dynamics. This dissertation contributes to the development of advanced analytical methods for evaluation of dynamic performance based on PMU data over a time window, identification of potential instability conditions, and activation of remedial control actions to restore a stable operating condition. In the first part of this research, a theoretical foundation for observability of nonlinear power system dynamics with partial PMU measurements is proposed. An observability index is proposed to quantify the level of observability of a power grid under different PMU placement scenarios. A real-time dynamic monitoring technique called State Calculator (SC) is developed to estimate system trajectories using phasor measurement data. In the second part, a PMU-based technique for online monitoring of power system stability is proposed. The algorithm of Maximum Lyapunov Exponent (MLE) is used to determine if a power system swing leads to instability within a finite time window. Advanced models, e.g., the structure preserving model, are applied to consider the frequency dynamics of the loads and voltage dynamics of the generators. With this model, the entire power network topology is explicitly represented, and PMU measurements at load buses are fully incorporated. Additionally, the generator excitation is included in the model, which takes the voltage dynamics of generators into account. With the improvement of the model, the MLE technique achieves better performance in predicting system stability. Finally, a PMU-based wide area remedial control method is developed based on the MLE technique, by predicting the system stability in real-time and stabilizing the system through appropriate control actions. The Individual MLE (I-MLE) is defined for each state variable. It reflects how the perturbation at each variable contributes to system instability. Thus, the most oscillatory buses can be identified. A theoretical method is established for designing a feedback control to bring system MLE within an acceptable range. This feedback control is then connected with power system remedial control actions, such as generator tripping, generation re-dispatch, and load shedding. A remedial control scheme is proposed accordingly to automatically select appropriate control actions on those most vulnerable buses to stabilize the system. The effectiveness of the proposed techniques is validated with different power system models, e.g., 3-bus system, 179-bus WECC system, and 15,000-bus PJM system model.

PMU-BASED MONITORING AND CONTROL OF POWER SYSTEM DYNAMICS

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