Search

This paper proposes a novel method to find the optimal location of the shunt connected Flexible AC Transmission Systems (FACTS) such as Static Var Compensator (SVC) or Static Synchronous Compensator (STATCOM) to the power system for regulating voltage levels of all buses. Three indices include Voltage Drop Index (VDI), Total Voltage Drop Index (TVDI), and Total Voltage Drop of Network Index (TVDNI) are presented to find the location of the SVC. Also, to minimize the solution space, a ranking list will be established. For the case studies, the IEEE 14-bus test system is selected, and an SVC is located in the system. Simulations are done in two cases: network loads increase with constant coefficient and randomly. According to simulation results in both cases, the proposed method can identify the optimal placement of SVC, and the voltage drop due to increasing the load will be compensated. For the IEEE 14-bus test system, the optimal location of the SVC is bus 9. Variable loads are considered for 24 h, and SVC is installed at bus 9 to validate the introduced method. Results show the voltage level for all buses is compensated so that the voltage levels are higher than the minimum voltage level, i.e. 95%. [ABSTRACT FROM AUTHOR]

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]