ANN Based SVC FACTS Controller to Enhance Voltage Stability of Multi-Machine Power System
M. Suman1, M. Venu Gopala Rao2, P.V. Ramana Rao3

1M.Suman, Department of Eee , Vlits, Vadlamudi, Guntur, India.
2M.Venu Gopala Rao, Department of Eee, Pvpsit, Vijayawada, India.
3P.V.Ramana Rao, Department of Eee, Anucet, Guntur, India.

Manuscript received on 04 July 2019 | Revised Manuscript received on 08 July 2019 | Manuscript published on 30 August 2019 | PP: 381-387 | Volume-8 Issue-10, August 2019 | Retrieval Number: I8401078919/2019©BEIESP | DOI: 10.35940/ijitee.I8401.0881019
Open Access | Ethics and  Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Voltage stability is the most vital phenomena in power systems which may be disturbed by the mismatch between the reactive power supply and demand. The occurrence of internal faults in the equipment and short circuit faults also there may be voltage collapse at the buses. Voltage stability can be improved using Static VAR Compensator (SVC) which is a shunt device. It can generate or absorb reactive power in a controlled manner such that it can enhance voltage stability of the system. LIndex method is used to determine voltage sensitivity at each bus and the bus having highest L- index value can be considered as a weak bus which is the optimal location of FACTS controller. The investigation is made to observe how susceptance in susceptance model and firing angle in firing angle model of the SVC is predicted to enhance the voltage at each bus by the artificial neural network under chaotic load. Standard IEEE 5 bus and 30 bus systems are considered as test systems and simulations are performed in MATLAB software.
Keywords: Voltage Stability, Reactive Power control, L-Index method, Static VAR Compensator, Artificial Neural Network.
Scope of the Article: Application Artificial Intelligence and machine learning in the Field of Network and Database