Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i18/71484
Year: 2016, Volume: 9, Issue: 18, Pages: 1-5
Original Article
Roozbeh Kamali1 , Reza Sharifi2 , Hamid Radmanesh3*and S. H. Fathi2
1Electrical Engineering Department, Aeronautical University of Science and Technology, Tehran, Iran; [email protected] 3Faculty of Engineering, Islamic Azad University Central Tehran Branch, Tehran, Iran; [email protected] 2Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran; [email protected], [email protected]
*Author for correspondence
Hamid Radmanesh
Faculty of Engineering, Islamic Azad University Central Tehran Branch, Tehran, Iran; [email protected]
This paper present an Artificial Neural Network (ANN) model for online profile voltage estimation to aim distribution network voltage regulation with consider Distributed Generation (DG). Arrival of DG to the distribution network affect the feeder voltages. Commonly, the On-Load Tap Changer (OLTC) transformer with a line drop compensation (LDC) that monitors the voltage along the feeder is used to regulate the voltage within allowable limits. But with presence DG because of multi-directional power flow, there are complications for the operation of the LDC to detect the correct amount of voltage profile along the feeder. The proposed estimation method employs Artificial Neural Network (ANN) concept and eliminates utilization of power flow calculations, resulting in low computational burden and online operation especially in case of systems with high order of complexity. Proposed technique is tested on a 13 bus distribution network and simulation outcomes validate effectiveness and efficiency of the suggested scheme.
Keywords: Artificial Neural Network (ANN), Distributed Generation, On-Load Tap Changer
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