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Flexible Alternating Current Transmission Systems (FACTS) represents a vast development in the area of power system operation and control. As we know that under heavily loaded conditions our power system is at high risks of consequent voltage instability problem. This paper gives an overview about application of series connected Flexible alternating current transmission system (FACTS) for improvement of power system performance like transfer stability, secure voltage profile and reduce the system losses etc. FACTS devices require huge capital investment. Therefore, heuristic techniques are used for optimal location and sizing of series FACTS controllers like Genetic Algorithm (GA), Particle Swarm Optimization (PSO) etc. These techniques are used to solve the optimization problem. This paper gives details of optimal placement and sizing of FACTS devices based on different evolutionary techniques which is used for minimization of transmission loss, enhancement of stability of power system. In this study one of the FACTS devices is used as a scheme for enhancement of power system stability.Proper installation of FACTS devices also results in significant reduction of transmission loss. In this review,TCSC is selected as the compensation device.

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Load flow study is done to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state working condition of a power system. It is important and most frequently carried out study performed by power utilities for power system planning, optimization, operation and control. In this paper a Particle Swarm Optimization Neural Network (PSO-ANN) is proposed to solve load flow problem under different loading/ contingency conditions for computing bus voltage magnitudes and angles of the power system. A multilayered feed-forward neural network is trained by using PSO technique. The results show the effectiveness of the proposed PSO-ANN based approach for solving power flow problem having different loading conditions and single-line outage contingencies in IEEE 14 bus system

Modern restructured power systems sometimes operate with heavily loaded lines resulting in power system to work under condition of higher power loss and higher voltage deviation, which may result in insecure operation of power system; even sometimes it may lead to voltage instability or system collapse. It is mainly due to continuous and uncertain growth and demand of electrical power. This paper presents a methodology to solve a multi-objective optimization problem to find optimal location and size of Static VAR Compensator (SVC); in order to minimize real power loss (RPL)& load bus voltage deviation (VD) and also enhancing voltage securityusing Continuous Genetic Algorithm (CGA). The effectiveness of the proposed method is demonstrated on a standard IEEE 30-bus system. The results obtained reveal effectiveness of CGA in handling multi objective optimization problem efficiently and successfully.