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Flexible Alternating Current Transmission Systems (FACTS) play a very prominent role in enhancing the performance of power system networks and in the quality up-gradation of power system by stabilizing the system parameters like voltage deviation, system security, power loss and system load-ability being a few to name. This work therefore handles two of the important performance parameters of a power system network namely power flow which is modeled as the System Load-ability (SL) and voltage profile which is represented as Voltage Stability Index (VSI). In this paper the maximization of VSI and SL of IEEE 30 Bus and 57 Bus networks have been exploited through the optimal placement of Thyristor Controlled Series Capacitor (TCSC), Static VAR Compensator (SVC) and Unified Power Flow Controller (UPFC) in the networks using the proposed and enhanced form of a recently developed meta-heuristic technique named as Salp Swarm Optimization (SSO). The outcomes of the simulations have been scrutinized with an established swarm-based optimization procedure. [ABSTRACT FROM AUTHOR]

In this article, the optimal allocation of compensation devices in power systems is determined using Improved Moth-flame Optimization (IMFO) algorithm. The main objective of this study is to maximize power system loadability, reduce total power system losses and enhance the voltage profile through finding the optimal locations and sizes of Static VAR Compensator (SVC) and Thyristor Controlled Compensator (TCSC). The methodology of this article is based on Continuation Power Flow (CPF) which is merged with IMFO in Optimum Power Flow (OPF) problem restricted by equality and inequality constraints. The proposed algorithm is implemented to regulate the required control variables. Both of single and multi-objective functions are applied on 57-IEEE bus test system to prove the performance of the proposed algorithm. The acquired simulation results by IMFO are compared with Moth Flame Optimization technique (MFO) and Multi Verse Optimizer (MVO) to emphasize the robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]