%0 Journal Article
%T Reconfiguration and Optimal Positioning of Multiple-Point Capacitors in a High-Voltage Distribution Network Using the NSGAII
%A Arouna Oloulade
%A Richard Gilles Agbokpanzo
%A Maurel Richy Aza-Gnandji
%A Hassane Ousseyni Ibrahim
%A Moussa Gonda
%A Em&#233
%A ric Tokoudagba
%A Juliano S&#233
%A tondji
%A Fran&#231
%A ois-Xavier Fifatin
%A Adolphe Moukengue Imano
%J Open Journal of Applied Sciences
%P 501-516
%@ 2165-3925
%D 2025
%I Scientific Research Publishing
%R 10.4236/ojapps.2025.152032
%X The distribution networks sometimes suffer from excessive losses and voltage violations in densely populated areas. The aim of the present study is to improve the performance of a distribution network by successively applying mono-capacitor positioning, multiple positioning and reconfiguration processes using GA-based algorithms implemented in a Matlab environment. From the diagnostic study of this network, it was observed that a minimum voltage of 0.90 pu induces a voltage deviation of 5.26%, followed by active and reactive losses of 425.08 kW and 435.09 kVAR, respectively. Single placement with the NSGAII resulted in the placement of a 3000 kVAR capacitor at node 128, which proved to be the invariably neuralgic point. Multiple placements resulted in a 21.55% reduction in losses and a 0.74% regression in voltage profile performance. After topology optimization, the loss profile improved by 65.08% and the voltage profile improved by 1.05%. Genetic algorithms are efficient and effective tools for improving the performance of distribution networks, whose degradation is often dynamic due to the natural variability of loads.
%K Reconfiguration
%K Capacitor Bank
%K NSGA II
%K Dynamic Network Degradation
%K Distribution Network Reliability
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=140848