Date of Award
Level of Access Assigned by Author
Doctor of Philosophy (PhD)
Electrical and Computer Engineering
Mohamad T. Musavi
Second Committee Member
Third Committee Member
Many interconnected power systems are constructed to meet the ever increasing electric power transfer demand. These systems must be operated below established thermal, voltage, and stability limits. However in order to recover from random disturbances, two critical components of system stability are the voltage phase angles at the generator buses and voltage magnitudes, which can be considered as indicators of stability margin. The current practice for ensuring power system stability is to monitor the power transfer in selected interfaces and keep them within stability limits. With the advent of Phasor Measurement Unit (PMU) devices, power system operators now have access to synchronized phase angles and voltage magnitudes in fractions of a second. Therefore, instead of monitoring the power transfers, this dissertation proposes a real-time methodology using synchronized phase angles and voltage magnitudes to observe system stability. This is accomplished by developing an algorithm to directly correlate the phase angle separation of critical generator bus pairs and critical voltage sag buses to the stability margin using interface power flow as the variable. These critical bus pairs/buses are selected systematically through transient stability simulations. Furthermore, a real-time Artificial Neural Network based prediction model is also proposed, which can be used to predict the postfault transient oscillation of phase angles of critical buses by using several samples after fault clearing. The above methods can be employed by operators and planners of large-scale power systems for enhanced real-time operational awareness and security decision-making. The Eastern North American power system is used as a platform to illustrate the utility of the proposed methods.
Wu, Yunhui, "Stability Assessment of Interconnected Electric Power Grid Using Synchrophasor Data" (2015). Electronic Theses and Dissertations. 2310.