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Title: | IEEE-69 Distribution Network Performance Improvement by Simultaneously Optimal Distributed Generation Sizing and Location Using PSO Algorithm |
Other Titles: | تحسين أداء شبكة التوزيع IEEE-69 عن طريق تحديد الحل الامثل لحجم وموقع مولد التوزيع باستخدام خوارزمية حركة الجزيئات |
Authors: | Badran, Ola |
Keywords: | Distribution Network;Distributed Generation location and sizing;Optimal Solution;Voltage Profile;Power Loss |
Issue Date: | 30-Mar-2023 |
Publisher: | Palestine Technical University -Kadoorie |
Citation: | Badran, O. (2023). IEEE-69 Distribution Network Performance Improvement by Simultaneously Optimal Distributed Generation Sizing and Location Using PSO Algorithm. Palestine Technical University Research Journal, 11(1), 01–15. https://doi.org/10.53671/pturj.v11i1.313 |
Series/Report no.: | 11(1);01–15 |
Abstract: | Integrated distributed generation (DG) to the network is the most popular technique to improve the network performance since DG sizing and location could reduce the power loss. However, using a non-optimal DG sizing and location could cause voltage fluctuation and power loss increase. Therefore, it is very important to develop asuitable optimization method that determines the optimal DG sizing and location. This research proposes a new strategy that leads to finding the simultaneous optimal solution involving both the optimal DG sizing and location. The proposed method aims to reduce the overall fitness function that taking into account both the voltage profile index and the power loss reduction. The particle swarm optimization (PSO) technique is the method that is used in this work. MATLAB simulations carried out on IEEE 69-bus radial distribution networks were used to prove the ability of the suggested method. The results obtained demonstrate the effectiveness of the presented method to determine the simultaneously optimal sizing and location of the DG units that minimize the overall power loss and improve the overall voltage profile. |
URI: | https://scholar.ptuk.edu.ps/handle/123456789/1047 |
ISSN: | https://doi.org/10.53671/pturj.v11i1.313 |
Appears in Collections: | 2023 |
Files in This Item:
File | Description | Size | Format | |
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1.-pturj-313.pdf | 832.87 kB | Adobe PDF | View/Open |
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