Optimal location of interline power flow controller for controlling multi transmission line: A new integrated technique

Abstract

In this paper, an interline power flow controller (IPFC) is used for controlling multi transmission lines. However, the optimal placement of IPFC in the transmission line is a major problem. Thus, we use a combination of tabu search (TS) algorithm and artificial neural network (ANN) in the proposed method to find out the best placement locations for IPFC in a given multi transmission line system. TS algorithm is an optimization algorithm and we use it in the proposed method to determine the optimum bus combination using line data. Then, using the optimum bus combination, the neural network is trained to find out the best placement locations for IPFC. Finally, IPFC is connected at the best locations indicated by the neural network. Furthermore, using Newton-Raphson load flow algorithm, the transmission line loss of the IPFC connected bus is analyzed. The proposed methodology is implemented in MATLAB working platform and tested on the IEEE-14 bus system. The output is compared with the genetic algorithm (GA) and general load flow analysis. The results are validated with Levenberg-Marquardt back propagation and gradient descent with momentum network training algorithm.

Keywords

IEEE-14 bus system / interline power flow controller (IPFC) / tabu search (TS) algorithm / artificial neural network (ANN) / training algorithm / load flow

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg