Voltage Stability Enhancement of Nigeria 330 kV Grid Using UPFC Facts ANN and Particle Swarm Optimization Technique (PSO)

Obasi, R.U.; Okonkwo, I.I.; Obinwa, C.I.

doi:10.55524/ijirem.2025.12.4.6

Abstract

The Nigerian Power system network in recent times has witnessed various power system distortions and frequent voltage violations leading to voltage collapse arising from inadequate reactive power support. The paper deals with enhancement of voltage stability in 330 kV Nigeria transmission network using Artificial Neural Network (ann) and Particle Swarm Optimization (PSO) techniques; UPFC FACTS tuned by ANN and determination of weak buses and its transmission line location via PSO optimization algorithm were implemented. By addressing the voltage stability issues in the network, the study aimed to contribute to system reliability and efficiency. Power flow was carried out using PSAT in steady state without UPFC, then with UPFC, and subsequently with ANN and PSO. Without UPFC FACTS, the following buses had least voltages which is a violation. The buses are 3, 6, 7, 8, 11, 22, 30, 34, 40, 54 and 55. Their recorded voltages were (301.26, 300.97, 302.78, 305.46, 301.57, 300.357, 301.71, 300.46, 300.34, 301.62 and 301.1) kV with an average of 301.6 kV. With UPFC, the bus voltages improved to (323.4, 322.25, 322.73, 321.48, 323.43, 321.53, 322.66, 322.75, 321.15, 320.55, 321.29) with an average of 322.09 kV. With the introduction of ANN, the bus voltages improved to (326.5, 327.69, 328.33, 329.99, 329.27, 326.13, 326.45, 326.71, 325.47 and 327.99 kV with an average bus voltage of 327.5472 kV. seventy percent 70% of the data obtained was for the training of the ANN based on Levenberg Marquadt back propagation algorithm and fifteen percent 15% each was for testing and validation. The average steady state voltage improvement with UPFC FACTS is 6.7% whereas with ANN it was 8.6%. In steady state, ANN performed better than UPFC FACTS. In dynamic state, at the generation stations of hydro and gas turbines UPFC performed better than ANN as the amplitude of ANN voltages experienced serious instability and fluctuations; whereas UPFC had a stable voltage of 7.5 kV. The implication is reduced insulation requirements and dimensions of synchronous alternators resulting to lower cost of alternator manufacturing.

Keywords

Unified Power Flow Controller (UPFC), Artificial Neural Network (ANN), Particle Swarm Optimization (PSO), Load Flow, Voltage Stability, Bus, Voltage Profile.

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Cites this article as

O. R.U., O. I.I., O. C.I., "Voltage Stability Enhancement of Nigeria 330 kV Grid Using UPFC Facts ANN and Particle Swarm Optimization Technique (PSO)", International Journal of Innovative Research in Engineering and Management (IJIREM), Vol-12, Issue-4, Page No-30-38, 2025. Available from: https://doi.org/10.55524/ijirem.2025.12.4.6