Genetic algorithm-based fuzzy multi-objective approach to congestion management using FACTS devices

This paper investigates a novel optimization-based methodology for placement of Flexible AC Transmission Systems (FACTS) devices in order to avoid congestion in the transmission lines while increasing static security margin and voltage profile of a given power system. The optimizations are carried out on the basis of location, size, and number of FACTS devices. Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC) are two FACTS devices which are implemented in this investigation to achieve the determined objectives. The problem is formulated according to Sequential Quadratic Programming (SQP) problem in the first stage to accurately evaluate static security margin with congestion alleviation constraint in the presence of FACTS devices and estimated annual load profile. In the next stage a Genetic Algorithm (GA)-based fuzzy multi-objective optimization approach is used to find the best trade-off between conflicting objectives. The IEEE 14-bus test system is selected to validate the proposed approach.