Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
8-1-2019 12:00 AM
End Date
11-1-2019 12:00 AM
Description
This paper presents several enhancements on a mixed OPF-stochastic cascading failure model to study the impacts of renewable energy resource uncertainty on grid vulnerability. The improved quasi-steady state (QSS) cascading failure model incorporates AC power flow calculations thus allowing us to simulate voltage-related failures in the grid. The under-voltage load shedding (UVLS) relays are modeled along with a stochastic time-inverse overload relay to accurately simulate the protective system response. In addition, more realistic assumptions are considered in the modeling of wind power penetration using geographical information of grid topology and wind potential map for a given geographical area. The effectiveness of the proposed framework is evaluated on a 500-bus synthetic network developed based on the footprints of South Carolina. The enhanced model allows us to more accurately simulate cascades in the power system with high penetration of erratic renewables and identify weak points.
Enhanced AC Quasi-steady State Cascading Failure Model for Grid Vulnerability Analysis under Wind Uncertainty
Grand Wailea, Hawaii
This paper presents several enhancements on a mixed OPF-stochastic cascading failure model to study the impacts of renewable energy resource uncertainty on grid vulnerability. The improved quasi-steady state (QSS) cascading failure model incorporates AC power flow calculations thus allowing us to simulate voltage-related failures in the grid. The under-voltage load shedding (UVLS) relays are modeled along with a stochastic time-inverse overload relay to accurately simulate the protective system response. In addition, more realistic assumptions are considered in the modeling of wind power penetration using geographical information of grid topology and wind potential map for a given geographical area. The effectiveness of the proposed framework is evaluated on a 500-bus synthetic network developed based on the footprints of South Carolina. The enhanced model allows us to more accurately simulate cascades in the power system with high penetration of erratic renewables and identify weak points.
https://aisel.aisnet.org/hicss-52/es/renewable_resources/4