Research Article STATCOM Estimation Using Back-Propagation, PSO, Shuffled Frog Leap Algorithm, and Genetic Algorithm Based Neural Networks Hamed Atyia Soodi and Ahmet Mete Vural Electrical and Electronics Engineering Department, University of Gaziantep, S ¸ahinbey, 27310 Gaziantep, Turkey Correspondence should be addressed to Hamed Atyia Soodi; hamedelec77@gmail.com Received 18 October 2017; Revised 28 February 2018; Accepted 21 March 2018; Published 26 April 2018 Academic Editor: Carlos A. V. Sakuyama Copyright © 2018 Hamed Atyia Soodi and Ahmet Mete Vural. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Diferent optimization techniques are used for the training and fne-tuning of feed forward neural networks, for the estimation of STATCOM voltages and reactive powers. In the frst part, the paper presents the voltage regulation in IEEE buses using the Static Compensator (STATIC) and discusses efcient ways to solve the power systems featuring STATCOM by load fow equations. Te load fow equations are solved using iterative algorithms such as Newton-Raphson method. In the second part, the paper focuses on the use of estimation techniques based on Artifcial Neural Networks as an alternative to the iterative methods. Diferent training algorithms have been used for training the weights of Artifcial Neural Networks; these methods include Back-Propagation, Particle Swarm Optimization, Shufed Frog Leap Algorithm, and Genetic Algorithm. A performance analysis of each of these methods is done on the IEEE bus data to examine the efciency of each algorithm. Te results show that SFLA outperforms other techniques in training of ANN, seconded by PSO. 1. Introduction Te power systems are the backbone of any country’s eco- nomic and social sectors, without which a country cannot excel in the industrial and social development. But the power systems face the ever-growing load demand as more industrial and housing units are established, which makes the job of power system managing challenging. Recently, the increase of nonlinear loads has badly afected the power quality, due to inherent voltage fuctuations in these types of loads, and has also raised question on the long-term stability of the power systems and their associated instruments [1, 2]. Hence, more research studies have been dedicated to improving the power quality and efciency through variety of diferent techniques. Te total power in the system contains both real and reactive power, which implies that if the reactive power of the system is improved, the overall system can beneft from this improvement. A family of diferent devices which can control the reactive power at designated buses is given the name Flexible AC Transmission Systems (FACTS). Tese devices have the capability to dynamically adjust diferent system parameters to enhance the performance and quality [2]. Te FACTS are actually controllers which can improve the system stability in terms of voltages, reactive power, and phase angles in the steady-state operation. One of the important FACTS devices which we have focused on in this research is called the Static Synchronous Compensator (STATCOM). A STATCOM is used to control the bus voltage or reactive power injec- tion/absorption at the bus and is connected in shunt with the designated bus. Te STATCOM when used as a voltage regulator draws controllable reactive currents from the buses. Since it is an expensive device, the selection of the optimal bus for the installation is of prime importance. When installed at an ideal Hindawi Computational Intelligence and Neuroscience Volume 2018, Article ID 6381610, 17 pages https://doi.org/10.1155/2018/6381610