Critical Line based Optimal Allocation of UPFC to improve Voltage Stability of the system
K. Manoz Kumar Reddy1, A. Kailasa Rao2, R. Srinivasa Rao3

1K.Manoz Kumar Reddy*, Department of Electrical and Electronics Engineering, Aditya College of Engineering,, ADB Road, Surampalem, India.
2A.Kailasa Rao, Department of Electrical and Electronics Engineering,, Pragati Engineering College, Surampalem, India.
3R. Srinivasa Rao, Department of Electrical and Electronics Engineering, University College of Engineering Kakinada, JNTUK, Kakinada, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1253-1259 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7617038620/2020©BEIESP | DOI: 10.35940/ijrte.F7617.038620

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper proposes critical line based optimal allocation of Unified Power Flow Controller (UPFC) in network to improve voltage stability through which finest power flow (PF) control can be obtained with proposed approach. A Genetic Algorithm based Upgraded Differential Evolutionary (UDE) approach is programmed with optimal allocation of UPFC at critical lines to enhance voltage stability. Critical lines can be obtained with severity of buses connected. Ranking Index(RI) is proposed to obtain critical lines in priority manner. UPFC device can be allocated at most priority line flow obtained from the proposed Ranking Index (RI).The constraints are modeled and programmed to make better voltage profiles of various bus networks. IEEE-5bus, 14bus, 30bus system are tested under MATLAB programming environment. The proposed strategy is compared with and without UPFC placement to show its effectiveness.
Keywords: Critical buses, Critical lines Differential Evolution, Voltage Limits, Unified Power Flow Controller.
Scope of the Article: Evolutionary Computing and Intelligent Systems.