Indian Journal of Science and Technology

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Online Voltage Estimation for Distribution Networks in Presence of Distributed Generation


Affiliations
1 Electrical Engineering Department, Aeronautical University of Science and Technology, Tehran, Iran, Islamic Republic of
2 Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran, Islamic Republic of
 

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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  • Online Voltage Estimation for Distribution Networks in Presence of Distributed Generation

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Authors

Roozbeh Kamali
Electrical Engineering Department, Aeronautical University of Science and Technology, Tehran, Iran, Islamic Republic of
Reza Sharifi
Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran, Islamic Republic of
Hamid Radmanesh
Electrical Engineering Department, Aeronautical University of Science and Technology, Tehran, Iran, Islamic Republic of
S. H. Fathi
Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran, Islamic Republic of

Abstract


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.



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i18%2F132951