Voltage Stability Evaluation using Modal Analysis and Deep Learning Technique for the Tunisian Power System Integrating Large-Scale RES Power Plants

Abstract

The voltage stability of the Tunisian power system, which includes 1750 MW of renewable energy resources power plants, is evaluated and analyzed. The study is based on a developed stability analysis tool based on an eigen-analysis approach and employs the concept of mode stability. The system model is the Tunisian 225 kV system, which a 23-bus equivalent model represents. The base case and the case of increased renewable energy resource power penetration are presented, compared, and predicted using Recurrent Neural Networks (RNNs). The main focus here is on the unavoidable consequences of the latter case on overall voltage decrease or increase. Each case study presents the critical mode’s characterizations, the power system element’s participation in each mode, and the generator PV-PQ state transitions.