A novel accelerated genetic algorithm-based technique for optimal placement of multiple FACTSDEV in power systems under N-1 contingency

Abstract

The liberalization of the energy market has led to a surge in unforeseen power exchanges, which could jeopardize the security of the power system by overloading transmission lines. Flexible AC transmission system devices (FACTSDEV) has been developed in order to improve voltage profiles, reduce losses, and solve power system instability. However, because FACTSDEV devices have such high initial costs, careful planning and ideal placement are essential to maximizing their benefits. This paper proposes a genetic algorithm-based approach to arrange multiple FACTSDEV devices in a power system optimally under N-1 contingency conditions. The IEEE standard (IEEESTD) 14 bus network is where FACTSEDV are located using this optimization technique. The study makes use of MATLAB simulations to evaluate how different FACTSDEV and their placements affect the performance of the power system. The results of the generator and line outage simulations show how FACTDEV have an impact on generation costs, system loss components, and line loss reduction. The cost-optimized placement findings for FACTSDEVs in the IEEESTD 14 bus system are satisfactory and show an improvement in generation cost and system loss component with appropriate positioning and sizing of FACTDEVs.