Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization

Napis, Nur Faziera (2017) Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization. Masters thesis, Universiti Teknikal Malaysia Melaka.

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Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization - Nur Faziera Napis - 24 Pages.pdf - Submitted Version

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Abstract

The present of Distributed Generation (DG) with suitable Distribution Network Reconfiguration (DNR) in the distribution system may lead to several advantages such as voltage support, power losses reduction, deferment of new transmission line and distribution structure and improved system stability. However, installation of the DG unit at non-optimal sizes with non-optimal DNR can incur higher power losses, power quality problem, voltage instability and amplification of operational cost. To overcome the power losses and voltage stability problems, an appropriate planning of DG units and DNR are considered. Thus, the first objective of this research is to develop an optimization technique named Improved Evolutionary Particle Swarm Optimization (IEPSO). The objective function is formulated to minimize the total power losses and to improve the voltage stability index. The load flow algorithm and voltage stability index calculation are integrated in the MATLAB environment to solve the optimization problem. Recently, the power system networks are being operated closer to the stability boundaries due to economic and environmental constraints. The heavier loading in the highly developed networks leads to voltage stability problems. However, the voltage stability problem of the distribution system can be improved if the loads are rescheduled efficiently with optimal DNR and DG sizing. Thus, the second objective of this research is to analyze the voltage stability index with three load demand levels; light load, nominal load, and heavy load with optimal DNR and DG sizing. The third objective of this research is to validate the performance of the proposed technique with other optimization techniques, namely Particle Swarm Optimization (PSO) and Iteration Particle Swarm Optimization (IPSO). Four case studies on 33-bus and 69-bus distribution system have been conducted to validate the effectiveness of the IEPSO. The optimization results show that, the best achievement of IEPSO technique for power losses reduction is up to 79.26%, and 58.41% improvement in the voltage stability index for three load conditions, light load, nominal load and heavy load. The proposed optimal DG sizing and DNR algorithm will provide a solution for independent power producer and power utility in terms of technical issues which beneficial for future electricity especially in integrating DG for the distribution network.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Electric power distribution, Computer networks, Swarm intelligence, Network Reconfiguration, Particle Swarm Optimization
Subjects: Q Science > Q Science (General)
Q Science > QC Physics
Divisions: Faculty of Electrical Engineering
Depositing User: Nor Aini Md. Jali
Date Deposited: 24 Apr 2018 08:37
Last Modified: 17 Jul 2020 14:54
URI: http://eprints.utem.edu.my/id/eprint/20718
Statistic Details: View Download Statistic

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