## 6 Congestion Management
Meanwhile, the congestion cost reduction is lowest in the case of the UPFC. However, the SSSC secured second place while STATCOM leads in terms of reducing congestion costs. Therefore, it is concluded that generators are subject to lower values of up and down rescheduling with STATCOM. Consequently, congestion in deregulated power systems was reduced by optimally placed FACTS devices (SVC, TCSC, and UPFC) using sensitivity analysis [215]. It is concluded that the best optimal place for TCSCs is those transmission lines which have a higher value of the line stability index. Similarly, the best optimal location for SVCs in interconnected power systems is also the best optimal location for SVCs. networks is those weak buses which have higher voltage deviation in response to increases in load-ability. Finally, the same authors concluded that the UPFC is to be placed at those transmission lines having higher active power. Another study was conducted in [214] that was mainly focused on providing congestion management (based on congestion cost by optimal rescheduling of generator outputs) with FACTS devices (SSSC, STATCOM, and UPFC) ensuring an increase in voltage stability and loadability limits in deregulated systems. Results concluded that congestion costs are significantly reduced in the presence of an SSSC. The UPFC also reduces congestion costs (subject to lower rescheduling of generators) but less than the SSSC. However, with STATCOM the reduction in congestion cost is marginal. Furthermore, the same authors conclude that the UPFC provides a greater voltage stability margin, therefore providing more support for load-ability as compared to the SSSC and STATCOM. Furthermore, Table 5 also shows the role of various FACTS devices and their pros and cons in congestion management. Providing congestion management using FACTS devices is a challenging task itself. Irrespective of choosing the right FACTS device for a particular deregulated power network, the selection of optimization techniques that make FACTS devices beneficial to a deregulated power system plays an important role in this regard. Therefore, in the literature, there are four different groups of optimization techniques that are broadly discussed [104]. These groups include classical optimization methods, analytical or sensitivity index methods, meta-heuristics methods, and hybrid or mixed methods. Major classical optimization techniques include the Newton-Raphson (NR) algorithm, mixed integer linear programming algorithm, mixed integer non-linear programming, sequential quadratic programming algorithm, non-linear programming algorithm, mixed integer programming algorithm, etc. In [216] an SVC is used with the NR algorithm in the IEEE-5 bus system to provide power system security. In the literature [217], the TCSC and UPFC are used with the sequential quadratic programming algorithm in IEEE-14 and 30 bus systems to provide congestion management. In the literature [218], successive-quadratic-programming-technique-based FACTS devices (SSSC and STATCOM) are used in IEEE-14, 30, and 118 bus systems to alleviate congestion by finding the optimal placement and number of FACTS devices. In [219], mixed-integer-linear-optimization-based SVCs and TCSCs are used in the IEEE-118 bus system to reduce congestion (by improving power system security by utilizing power system load-ability). In [220] a mixed-integer-non-linear-programming-model-based TCSC and energy storage are implemented in the IEEE-18 and 30 bus systems to mitigate transmission congestion. In [200] a mixed integer programming optimization technique is used with SVCs, TCSCs, and generators for congestion management in a restructured environment. The authors of [104] concluded that the mixed integer linear programming method and mixed integer non-linear programming methods are widely used in large-scale power networks but are computationally expensive.