Controlled Islanding under PMU Data Uncertainties
The proliferation of phasor measurement units, albeit transformative to grid operations, increases the risk of cyber threats in power systems. One consequence of these cyber threats is incorrect operator actions based on misleading data. While a single wrong operator action might not result in a widespread blackout, a series of actions on critical lines and transformers, combined with pre-existing faults or scheduled maintenance, might. Traditionally, controlled islanding prevents cascading failures. However, it is only effective when the received measurements are trustworthy. This paper presents two multi-objective controlled islanding strategies that accommodate phasor measurement uncertainties under scenarios of lack of or partial knowledge of false data injection attacks. Under the lack of knowledge, the multi-objective optimization problem maximizes the observability of the islands using a minimum number of phasor measurement units. When partial knowledge of an attack is available, the size of the island with vulnerable measurements is minimized to contain the impacts of attacks. In both cases, additional objectives reduce the load-generation imbalance of the islands and the total line power flow disconnection. Simulations are conducted on synthetic Illinois 200-bus, South Carolina 500-bus, and Texas 2000-bus systems.
The detailed case descriptions, including the total number of secure and non-secure PMUs, and scalarization parameters for the optimization formulation are given in this dataset.