Genetic Algorithm-Based Optimal Placement of SVC and TCSC in the Nigerian Power Grid

Olalekan OGUNBIYI; Andee Olasubomi OLAYINKASCOTT; Lambe Mutalub ADESINA

Genetic Algorithm-Based Optimal Placement of SVC and TCSC in the Nigerian Power Grid

Olalekan OGUNBIYI, Andee Olasubomi OLAYINKASCOTT, Lambe Mutalub ADESINA

Abstract

Nigeria’s power system continues to suffer from voltage instability, high transmission losses, and poor resilience under contingency conditions. Expanding grid infrastructure is capital-intensive; therefore, optimising existing transmission assets provides a cost-effective alternative. This paper develops a Genetic Algorithm–based coordinated optimization scheme for the optimal placement and sizing Flexible AC Transmission System (FACTS) devices, specifically the Static VAR Compensator (SVC) and Thyristor-Controlled Series Capacitor (TCSC), for improved voltage stability and reduced transmission losses in Nigerian transmission network. The proposed method was evaluated under normal operation, generator outage, line outage, and overload conditions (130% and 150% loading). Simulation results reveal that, without compensation, critical buses experienced voltage violations reaching up to 1.07 p.u. GA-optimised deployment of SVCs (−29.8 to −51.6 MVAr) and TCSCs (29%–54.7% compensation) successfully regulated all bus voltages within acceptable limits. Reactive power losses were reduced by up to 17.9%, while real power losses decreased by up to 1.22% under severe loading conditions. The coordinated application of SVC and TCSC consistently outperformed individual device deployment, significantly improving system robustness under N−1 contingency conditions. The results validate the capability of the GA-based FACTS optimization approach to enhance reliability and operational performance within Nigeria’s power grid.

Keywords

Genetic Algorithm, FACTS, Static VAR Compensator, Thyristor-Controlled Series Capacitor, Voltage Stability, Power Loss Reduction

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