Transient Stability Improvement in a Transmission Line Using Neuro-Fuzzy Based Unified Power Flow Controller [Case Study of Adama II, Koka to Kality Substation]

Abstract

High-voltage transmission networks in Ethiopia are vulnerable to transient instability due to long lines and faults, causing power losses and voltage deviations. To meet increasing demand and ensure a secure power supply, the Ethiopian Electric Power office suggests enhancing transmission line capacity with the integration of Flexible AC Transmission System (FACTS) devices. This research proposes a Unified Power Flow Controller (UPFC) based on a Neuro-Fuzzy Inference System (NFIS) for high-voltage transmission networks. The UPFC will provide reactive power compensation quickly, and the optimal placement will be determined using Particle Swarm Optimization. The controller will be tested under fault scenarios and active power analysis across different transmission lines. When a three-phase ground fault occurs at the midpoint of the Koka to Kality East Industry transmission line, for example, the use of an ANFIS-based UPFC reduces the settling time of rotor angle deviation, rotor speed, rotor speed deviation, and output active power by 70.48%, 38%, 38%, and 44%, respectively, in comparison to a system without a UPFC. A PI-based UPFC reduces active power loss on the Koka to Kality East Industry transmission line by 54.54% at peak load, while an ANFIS-based UPFC reduces it by 72.72%. Similarly, at peak load, active power loss is decreased by 70% with an ANFIS based UPFC and by 50% with a PI-based UPFC for the Adama II, Koka, and Melka Wakena to Kality transmission line. In general, the UPFC based on ANFIS.