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

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....

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Main Author:	Napis, Nur Faziera
Format:	Thesis
Language:	English English
Published:	2017
Subjects:	Q Science (General) QC Physics
Online Access:	http://eprints.utem.edu.my/id/eprint/20718/1/Network%20Reconfiguration%20And%20Distributed%20Generation%20Sizing%20In%20Radial%20Distribution%20System%20Using%20Improved%20Evolutionary%20Particle%20Swarm%20Optimization%20-%20Nur%20Faziera%20Napis%20-%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/20718/2/Network%20Reconfiguration%20And%20Distributed%20Generation%20Sizing%20In%20Radial%20Distribution%20System%20Using%20Improved%20Evolutionary%20Particle%20Swarm%20Optimization.pdf
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institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
topic	Q Science (General) QC Physics
spellingShingle	Q Science (General) QC Physics Napis, Nur Faziera Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization
description	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.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Napis, Nur Faziera
author_facet	Napis, Nur Faziera
author_sort	Napis, Nur Faziera
title	Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization
title_short	Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization
title_full	Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization
title_fullStr	Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization
title_full_unstemmed	Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization
title_sort	network reconfiguration and distributed generation sizing in radial distribution system using improved evolutionary particle swarm optimization
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Electrical Engineering
publishDate	2017
url	http://eprints.utem.edu.my/id/eprint/20718/1/Network%20Reconfiguration%20And%20Distributed%20Generation%20Sizing%20In%20Radial%20Distribution%20System%20Using%20Improved%20Evolutionary%20Particle%20Swarm%20Optimization%20-%20Nur%20Faziera%20Napis%20-%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/20718/2/Network%20Reconfiguration%20And%20Distributed%20Generation%20Sizing%20In%20Radial%20Distribution%20System%20Using%20Improved%20Evolutionary%20Particle%20Swarm%20Optimization.pdf
_version_	1747833993168945152
spelling	my-utem-ep.207182022-03-15T08:17:12Z Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization 2017 Napis, Nur Faziera Q Science (General) QC Physics 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. 2017 Thesis http://eprints.utem.edu.my/id/eprint/20718/ http://eprints.utem.edu.my/id/eprint/20718/1/Network%20Reconfiguration%20And%20Distributed%20Generation%20Sizing%20In%20Radial%20Distribution%20System%20Using%20Improved%20Evolutionary%20Particle%20Swarm%20Optimization%20-%20Nur%20Faziera%20Napis%20-%2024%20Pages.pdf text en public http://eprints.utem.edu.my/id/eprint/20718/2/Network%20Reconfiguration%20And%20Distributed%20Generation%20Sizing%20In%20Radial%20Distribution%20System%20Using%20Improved%20Evolutionary%20Particle%20Swarm%20Optimization.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106154 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Electrical Engineering 1. Abri, R. 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Network Reconfiguration And Distributed Generation Sizing In Radial Distribution System Using Improved Evolutionary Particle Swarm Optimization

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