OPF-Based Optimal Power System Network Restoration Considering Frequency Dynamics

Due to recent blackout and system split incidents in power grids worldwide, as well as increased system complexity in view of the energy transition, there has been increasing interest in re-evaluating existing Power System Restoration (PSR) plans. In restoration scenarios, due to low island inertia, it is necessary to ensure not only the static, but also the dynamic stability of the system. In this paper, we pose and solve a formulation of the optimal PSR problem including frequency dynamics. We validate the switching constraints for global optimality within a static version of the formulation using a brute-force tree search method. We apply the dynamic problem formulation to the IEEE 9-Bus model, and show that the optimal switching sequence using the static formulation would violate dynamic constraints, illustrating the importance of dynamic considerations in PSR planning.

Identification of Power System Dynamic Model Parameters using the Fisher Information Matrix

The expected decrease in system inertia and frequency stability motivates the development and maintenance of dynamic system models by Transmission System Operators. However, some dynamic model parameters can be unavailable due to market unbundling, or inaccurate due to aging infrastructure, non-documented tuning of controllers, or other factors. In this paper, we propose the use of a numerical approximation of the Fisher Information Matrix (nFIM) for efficient inference of dynamic model parameters. Thanks to the proposed numerical implementation, the method is scalable to Electromagnetic Transient (EMT) models, which can quickly become computationally complex even for small study systems. Case studies show that the nFIM is coherent with parameter variances of single- and multi-parameter least-squares estimators when applied to an IEEE 9-bus dynamic model with artificial measurements.