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Article
Optimal Placement and Control of Unified Power Flow Control Devices Using Evolutionary Computing and Sequential Quadratic Programming
Proceedings of the 2006 IEEE Power Engineering Society Conference & Exposition (2006, Atlanta, GA)
  • Radha P. Kalyani
  • Mariesa Crow, Missouri University of Science and Technology
  • Daniel R. Tauritz, Missouri University of Science and Technology
Abstract
A crucial factor effecting modern power systems today is power flow control. An effective means for controlling and improving power flow is by installing fast reacting devices such as a unified power flow controller (UPFC). For maximum positive impact of this device on the power grid, it should be installed at an optimal location and employ an optimal realtime control algorithm. This paper proposes the combination of an evolutionary algorithm (EA) to find the optimal location and sequential quadratic programming (SQP) to optimize the UPFC control settings. Simulations are conducted using the classic IEEE 118 bus test system. For comparison purposes, results for the combination of a greedy placement heuristic (H) and the SQP control algorithm are provided as well. The EA+SQP combination is shown to outperform the H+SQP approach.
Meeting Name
2006 IEEE Power Engineering Society Conference & Exposition (2006: Oct. 29-Nov. 1, Atlanta, GA)
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
  • Evolutionary Computing,
  • Power Flow Control Devices,
  • Quadratic Programming,
  • Evolutionary Algorithm (EA),
  • Optimal Realtime Control Algorithm
International Standard Book Number (ISBN)
1-4244-0177-1
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2007 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
11-1-2006
Citation Information
Radha P. Kalyani, Mariesa Crow and Daniel R. Tauritz. "Optimal Placement and Control of Unified Power Flow Control Devices Using Evolutionary Computing and Sequential Quadratic Programming" Proceedings of the 2006 IEEE Power Engineering Society Conference & Exposition (2006, Atlanta, GA) (2006) p. 959 - 964
Available at: http://works.bepress.com/daniel-tauritz/53/