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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Labed Imen
University of Constantine 1
Control & Systems Engineering Electrical & Electronics Engineering

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Power flow variation based on extreme learning machine algorithm in power system Labed Imen; Labed Djamel
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.583 KB) | DOI: 10.11591/ijpeds.v10.i3.pp1244-1254

Abstract

The main focus of this paper is a study that empowers us to understand how the temperature variation affects the transmission line resistance and as a result the power flow analysis with a specific end goal to assess losses in the electrical network. The paper is composed of two sections; the first part is a power flow study under normal conditions utilizing the neural network approach while the second investigated extreme learning machine algorithm efficiency and exactitude. Extreme learning machine algorithm has been used to settle several complications in power system: load forecasting, fault diagnosis, economic dispatch, security, transient stability; Thus, we proposed to study this technique to figure out this sort of complex issue.The study was conducted for IEEE 30 bus test system. The simulation results are exposed and analyzed in detail at the end of this paper.
Co-Authors Labed Djamel