Abstract
In this paper Genetic Algorithm (GA) is used as an evolutionary tecthniques for the optimal placement of flexible AC transmission systems (FACTS) devices in an interconnected power system. Here two types of FACTS devices has been discussed nemely, Thyristor Controlled Series Capacitor (TCSC) and Static Var Compensator (SVC) for the economic operation and to reduce the transmission loss. Reactively loading of the system is taken from base to 200% of base loading and the system performance is observed without and with FACTS devices. Optimal placement of FACTS devices in the system is determined by calculating active and reactive power flow in lines. FACTS devices along with reactive generation of generators and transformer tap setting are used for the power transfer capacity using GA. The proposed approach is applied on IEEE 14 and IEEE 30-bus test systems. Finally the effectiveness of the proposed GA based method of placement of FACTS devices is established by comparing the results with another standard method of optimization like Particle Swarm Optimization (PSO) technique.
Highlights
Due to increase in power demand, restriction on the construction of new lines, environment, unscheduled power flows in lines creates congestion in the transmission network and increases transmission loss
Solution of optimal power flow using Genetic Algorithm (GA) is presented by Osman et al in [7]
If reactive power flow is a significant portion of the total flow of the limiting transmission line, either a Thyristor Controlled Series Capacitor (TCSC) device in the line or a Static Var Compensator (SVC) device located at the end of the line that receives the reactive power, may be used to reduce the reactive power flow, thereby increasing the active power flow capacity
Summary
Due to increase in power demand, restriction on the construction of new lines, environment, unscheduled power flows in lines creates congestion in the transmission network and increases transmission loss. Authors have discussed Genetic Algorithm based approach for the placement of different types of FACTS devices in [8]. Computational Intelligence based algorithm is presented in [9] to determine the optimal placement and parameter setting of TCSC for enhancing the security of power system under single line contingency. In [11] GA based technique is discussed for the placement of FACTS devices in some test systems. Timization method is used in [14] that combines the reliability and the efficiency of radial power distribution systems to reduce the active power loss, through a process of network reconfiguration. Effect of implementation of Genetic Algorithm for the determination of locations and size of the FACTS controller is discussed in [15]. Ci: weight coefficient for each term, pbesti: pbest of agent i, gbesti: gbest of agent i
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