A Novel Smart Grid State Estimation Method Based on Neural Networks

Mohamed Abdel-Nasser*, Karar Mahmoud, Heba Kashef

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The rapid development in smart grids needs efficient state estimation methods. This paper presents a novel method for smart grid state estimation (e.g., voltages, active and reactive power loss) using artificial neural networks (ANNs). The proposed method which is called SE-NN (state estimation using neural network) can evaluate the state at any point of smart grid systems considering fluctuated loads. To demonstrate the effectiveness of the proposed method, it has been applied on IEEE 33-bus distribution system with different data resolutions. The accuracy of the proposed method is validated by comparing the results with an exact power flow method. The proposed SE-NN method is a very fast tool to estimate voltages and re/active power loss with a high accuracy compared to the traditional methods.

Original languageEnglish
Pages (from-to)92-100
Number of pages9
JournalINTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE
Volume5
Issue number1
DOIs
Publication statusPublished - Jun 2018
MoE publication typeA1 Journal article-refereed

Keywords

  • Neural Network
  • Smart Grid
  • Renewable Energy
  • Power Loss
  • Voltage Profile
  • POWER-FLOW
  • PENETRATION
  • PV

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