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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS)
Yahiaoui Merzoug
Dr. Moulay Taher University of SAIDA
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Distribution network reconfiguration for loss reduction using PSO method Yahiaoui Merzoug; Bouanane Abdelkrim; Boumediene Larbi
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (234.588 KB) | DOI: 10.11591/ijece.v10i5.pp5009-5015

Abstract

In recent years, the reconfiguration of the distribution network has been proclaimed as a method for realizing power savings, with virtually zero cost. The current trend is to design distribution networks with a mesh network structure, but to operate them radially. This is achieved by the establishment of an appropriate number of switchable branches which allow the realization of a radial configuration capable of supplying all of the normal defects in the box of permanent defect. The purpose of this article is to find an optimal reconfiguration using a Meta heuristic method, namely the particle swarm optimization method (PSO), to reduce active losses and voltage deviations by taking into account certain technical constraints. The validity of this method is tested on a 33-IEEE test network and the results obtained are compared with the results of basic load flow.
Optimal placement of wind turbine in a radial distribution network using PSO method Yahiaoui Merzoug; Bouanane Abdelkrim; Boumediene Larbi
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (595.739 KB) | DOI: 10.11591/ijpeds.v11.i2.pp1074-1081

Abstract

The aim of this article is to apply the Particle Swarm Optimization (PSO) method to find the best location for the wind turbine in the radial distribution network. The optimal location is found using the loss sensitivity factor. By respecting the constraints of the active power transmitted in the branches and the limits of the voltages modules for all the nodes. The validity of this method is tested on a 33-IEEE test network and the results obtained are compared with the results of basic load flow.
Universal phase shifter regulator system modeling with robust GPC using neural networks for compensation power in transmission line Bouanane Abdelkrim; Nerziou Madani; Yahiaoui Merzoug; Raouti Driss
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i3.pp1448-1458

Abstract

Electricity consumption is increasing gradually and this trend will continue in the future. In addition, rapid network control systems using the resources offered by power electronics and control microelectronics have been recently studied and developed, and are currently in normal application for some, for others, in pilot applications or as prototypes. This paper attempts to show that these systems are referred to by the general acronym flexible alternative current transmission systems (FACTS) similarly dethroned the traditional systems while offering better solutions and solving the energy quality problem such as the hybrid system (unified power flow controller (UPFC), or universal phase shifter regulator (UPSR)) which opens up new perspectives for more efficient operation of networks by continuous and rapid action on the various parameters of the network (voltage, phase shift, and impedance); thus, the power transits will be better controlled and the voltages better held, which will make it possible to increase the stability margins or tend towards the thermal limits of the lines. In this work, we used a classic control (PI-decoupled) and others while offering more flexibility of control thanks to the development of strategies identification/control based on generalized predictive control (GPC) with neural network to ensure robust control with advanced algorithms.
Co-Authors Bouanane Abdelkrim Bouanane Abdelkrim Boumediene Larbi Nerziou Madani Raouti Driss