Designing of a TEF-based neuro-fuzzy controller for IPFC to improve the transient stability

Abstract

SUMMARY In recent years, because of structure renewal, development, and progressive distribution, many of the economical and technical characteristics of power systems in the various parts of production, transmission, distribution, and consumption have been changing. Especially, the transmission systems have been affected to a great degree because of the increase in demand and limitation in the new lines formation. One of the shortcomings of this affair is the risk of losing stability after turbulence occurrence. The controllability and stability of power systems can be increased by FACTS devices. One of the FACTS devices is Interline Power‐Flow Controller (IPFC) by which the voltage stability, dynamic stability, and transient stability of power systems can be improved. In the present paper, the convenient operation and control of IPFC for transient stability improvement are considered. Considering that, the system's Lyapunov energy function is a relevant tool to study the stability affair. IPFC energy function optimization has been used in order to access the maximum of transient stability margin. In order to control IPFC, ANFIS which is a neuro‐fuzzy controller has been used. The designing results have been studied by the simulation of a single‐machine system with infinite bus and another standard 9‐buses system (Anderson and Fouad, 1977). Moreover, with simulating of other FACTS devices, such as unified power flow controller (UPFC), static synchronous series compensator (SSSC), and static synchronous compensator (STATCOM) and comparing the results, the superiority of IPFC is proved. Copyright © 2012 John Wiley & Sons, Ltd.

Optimal robust stabilizer design based on UPFC for interconnected power systems considering time delay

“…1 [4]. By controlling the magnitude and the phase of the series injected voltage (U ser ), the real and reactive power flow in the transmission line can be managed.…”

“…The shunt inverter provides the required active power for the series branch and the UPFC losses. Also, the reactive compensation to maintain the shunt bus voltage at the defined set point is performed by the shunt inverter [3][4][5]. …”

“…Removing such drawback, application of FACTS devices has been shown to be an effective and practical strategy for stability enhancement [3]. The UPFC from the FACTS family has been also introduced as a device with the ability of controlling both the active and reactive power independently and simultaneously [4].…”

Estimation of recovery cost with the incorporation of an IPFC in a SCUC problem

“…Incorporating FACTS devices into a power system network reduce the burden of generators which are committed to meet the sudden load demand thus making the generation more economical. Interline Power Flow Controller, which is the latest evolved FACTS device for transmission network, is used to compensate a number of transmission lines in a given network [3,4]. During the outage of lines in power system network, there is a chance for violation of constraints, since the actual load has to be met by the existing transmission lines and certain lines will get overloaded.…”

An improved adaptive RBF neuro‐sliding mode control strategy: Application to a static synchronous series compensator controlled system

“…Adaptive approximation based control that overcomes this assumption encompasses a variety of methods, which appear in the literature such as intelligent control, neural control, adaptive fuzzy control, memory-based control, knowledge-based control, adaptive nonlinear control, and adaptive linear control. [8][9][10][11][12][13] Research in these fields have diverse backgrounds such as mathematics, engineering, and computer sciences, and therefore, the perspective of the various papers in these areas are also varied. However, the objective of the various practitioners is typically similar, which is to design a controller that can guarantee stability and achieve a high level of control performance for systems that contain poorly modeled nonlinear effects, or the dynamics of the system changes during operation.…”