Optimization of SVC Placement and Sizing in the Gorontalo Power System Using TLBO

This paper presents the application of the Teaching-Learning-Based Optimization (TLBO) algorithm to determine the optimal placement and sizing of a static var compensator (SVC) in the 150-kV Gorontalo transmission network. The optimization aims to minimize active power losses and installation costs while maintaining bus voltages within operational limits under both current and projected load conditions. The problem is formulated as a multi-objective model combining technical and economic criteria, solved using TLBO with no algorithm-specific parameters. Six simulation scenarios were analyzed, including existing and projected industrial load conditions with different SVC configurations. Results show that installing a single SVC at Bus 08 significantly improves voltage stability and reduces losses, achieving reductions of 1.8 under the current load and 3.0 under the projected demand. The dual-SVC configuration provides only marginal additional technical benefits at a substantially higher cost. Bus 08 is identified as the optimal location due to its high voltage sensitivity and strategic network position, enabling system-wide voltage recovery with minimal investment. The TLBO algorithm demonstrates fast and stable convergence across all scenarios and can be scaled to larger networks with minor parameter adjustments. The proposed installation is technically sound, operationally feasible, and economically justified, making it a suitable strategy for both current operation and anticipated system growth.