Application of genetic algorithm in optimization of unified power flow controller parameters and its location in the power system network

This work demonstrates the application of Genetic Algorithm (GA) technique for the simultaneous stabilization of power systems using a Unified Power Flow Controller (UPFC). The GA is applied to find the optimal location of the UPFC and to tune its control parameters under different operating conditions. The problem is formulated as a multiobjective optimization problem which aims at maximizing the damping ratio of the electromechanical modes using different lines fitted with the UPFC. The approach is successfully tested on the 16-machine 68-bus New England–New York interconnected system and on the Iraqi National Super Grid System (INSGS) to validate its effectiveness in the damping of local and inter-area modes of oscillations. In addition, the proposed approach demonstrated better performance when compared to a fuzzy-based UPFC damping controller.

► We present a multiobjective optimization to stabilize power systems using a UPFC.
► The UPFC location and its control parameters are optimized using GA.
► The optimization will maximize the damping ratio of the electromechanical modes.
► The resulting stabilizer is tested on two systems under various operating conditions.
► We validated the approach effectiveness in damping modes of oscillations.