  After major disturbances, power system behavior is governed by the dynamic
characteristics of its assets and protection schemes. Therefore, modeling
protection devices is essential for performing accurate stability studies.
Modeling all the protection devices in a bulk power system is an intractable
task due to the limitations of current stability software, and the difficulty
of maintaining and updating the data for thousands of protection devices. One
of the critical protection schemes that is not adequately modeled in stability
studies is distance relaying. Therefore, this paper proposes an algorithm that
uses two methods to identify the critical distance relays to be modeled in
stability studies: (i) apparent impedance monitoring, and (ii) the minimum
voltage evaluation (MVE). The algorithm is implemented in Python 3.6 and uses
the GE positive sequence load flow analysis (PSLF) software for performing
stability studies. The performance of the algorithm is evaluated on the Western
Electricity Coordinating Council (WECC) system data representing the 2018
summer-peak load. The results of the case studies representing various types of
contingencies show that to have an accurate assessment of system behavior,
modeling the critical distance relays identified by the algorithm suffices, and
there is no need for modeling all the distance relays.
