IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 11, Issue 4 Ver. I (Jul. – Aug. 2016), PP 33-43 www.iosrjournals.org DOI: 10.9790/1676-1104013343 www.iosrjournals.org 33 | Page Optimal Location of IPFC for Improving Power System Performance Using Cuckoo Search Algorithm Dr. Arul S 1 , Chellaswamy C 2 1 Department of Electronics and Communication Engineering, Jeppiaar Institute of Technology, Chennai, India. 2 Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Tamil Nadu, India, Abstract: This paper presents a new scheme based on cuckoo search algorithm (CSA) for enhancing the performance of interline power flow controller (IPFC) under multiline transmission for reducing the transmission line congestion to a great extent. Optimal placement of IPFC is done by subtracting line utilization factor (SLUF) and CSA-based optimal tuning. The multi objective function consists of active power loss, security margin, bus voltage limit violation and capacity of installed IPFC. The multi objective function is tuned by CSA and the optimal location for minimizing the congestion in transmission lines is obtained. The simulation is performed using MATLAB for the case study using an IEEE 30-bus test system. The performance of CSA has been studied under different loading conditions and compared with two other optimization techniques such as particle swarm optimization (PSO) and differential evolution algorithm (DEA). The result shows that the proposed CSA outperforms the other two methods and it best suits the power system security. Keywords : congestion management; cuckoo search algorithm; Interline power flow controller (IPFC); optimal location; power system; subtracting line utilization factor I. Introduction There is an enormous increase in power transaction due to power system renovation and different factors such as environmental, right-of-way and high cost, which forms the hurdle for the expansion of power transmission network. With the advancement in flexible Ac transmission system (FACTS), several innovative concepts turn the system into more flexible and have control over power flow without altering the generation schedule. Optimal location identification and allocation of FACT devices improve various parameters of the system [1], [2]. FACT is based on power electronics and other stationary tools which control one or more parameters of AC transmission system thereby increasing the power transfer capability and controllability [3]. Various FACT tools has been used for this purpose such as static Var compensator (SVC), static synchronous compensator (STATCOM), static synchronous series compensator (SSSC), thyristor controller series capacitor (TCSC), unified power flow controller (UPFC) and interline power flow controller (IPFC) [4]. IPFC combines two or more FACT controllers in series and can control power flows of a group of lines and sub-networks. On the other hand the UPFC can control power flow of single transmission line only. The IPFC also has the capability to directly transfer real power between compensated lines and transfer power demand from over loaded to under loaded lines [5], [6]. To solve power system state estimation problem Taguchi differential evolution algorithm is used. For improving the accuracy and reliability of state estimation problem the positive properties of Taguchi method is combined with the differential evolution [7]. Application of differential evolution algorithm for transient stability with different constrains to get optimal power flow has been introduced by Cai et al [8]. A modified differential evolution algorithm with fitness sharing for increasing the stability, reduce overload and voltage violations of power system [9]. A particle swarm optimization (PSO)- based algorithm is used to estimate exact location and sizing of unified power flow controller to perform congestion management. The impact of load variations, system reliability and congestion cost of the system has been studied [10]. Automatic human motion tracking in video sequences using PSO technique is proposed by Sanjay et al [11]. Computer vision and pattern recognition is used to identify the motion of human and high search space is used for high variability in human appearance. CS algorithm is the nature inspired algorithm for optimization heuristics to solve difficult optimization problems. The obligatory brood parasitism with levy flight is a unique behavior of CS algorithm [12]. Comparison of several FACT devices using CS algorithm for three unequal areas of thermal systems has been studied in [13]. Distributed network reconfiguration for power loss minimization, load frequency control, voltage profile improvement for nonlinear interconnected power system using CS algorithm has been studied [14], [15]. Multi-objective short-term scheduling and non-convex economic dispatch considering system characteristics including valve-point effects, multiple fuels, prohibited zones and power loss using CS method has been studied [16], [17]. Line utilization factor (LUF) is used to determine the percentage of loading by