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Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming

TK1006.S52 2017

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Main Author: Sharifah Munirah Mahmor
Format: text::Final Year Project
Language:English
Published: 2024
Subjects:
Distributed generation of electric power
Electric power system stability
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spelling my.uniten.dspace-330042024-08-04T02:03:46Z Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming Sharifah Munirah Mahmor Distributed generation of electric power Electric power system stability TK1006.S52 2017 Distributed generation (DG) in a power system is real power generation near the point of consumption. DG units can be fossil fuel generators like coal power plant or renewable sources like solar photovoltaic, wind turbine, etc. Normally, DG units generate small amount of electric power compared to the conventional generating units like coal power plants, large hydro stations, etc. This is why they are located near to consumers. In future ahead, the quantity of DG units connected to power systems grid has increased dramatically due to the deregulation by the governments. Many countries have started to reduce their dependency on fossil fuel generating units as they want to reduce the carbon emission produced from the electric power generation. It is important to ensure the optimal location and suitable size for DG units to be installed at power system grids. Otherwise, the connection may disturb the power system stability and security. The power injected to a system must be balanced with the power absorbed by the system. In order to find the appropriate placing and sizing of DG units in a power system, a project proposed to implement a hybrid optimization technique termed as immune evolutionary programming (IEP) in DG installation. Three DG units with different sizes have been installed in the IEEE 26- bus test system. And three cases have been introduced to study the performance of IEP algorithm. The difference between these three cases is at their load level. Case I has no load increment, Case II has 50 % load increment and Case III has 100% load increment. Voltage steadiness is also included in order to find a solution to DG installation issues. It is ensured that the voltage at all buses in the 26-bus system is within the allowable range (0.95 p.u. to 1.05 p.u.) after the DG units are installed. Furthermore, the power factor also maintained to be 0.85 p.u. It is found that the IEP algorithm effectively solved the DG installation problem for the all three cases. Keywords: Distributed Generation (DG), Evolutionary Programming (EP), Artificial Immune System (AIS), total loss minimization, voltage stability control. 2024-07-30T07:49:48Z 2024-07-30T07:49:48Z 2017 Resource Types::text::Final Year Project https://irepository.uniten.edu.my/handle/123456789/33004 en application/pdf
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
topic Distributed generation of electric power
Electric power system stability
spellingShingle Distributed generation of electric power
Electric power system stability
Sharifah Munirah Mahmor
Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming
description TK1006.S52 2017
format Resource Types::text::Final Year Project
author Sharifah Munirah Mahmor
author_facet Sharifah Munirah Mahmor
author_sort Sharifah Munirah Mahmor
title Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming
title_short Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming
title_full Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming
title_fullStr Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming
title_full_unstemmed Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming
title_sort optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming
publishDate 2024
_version_ 1806517982138990592
score 13.188404

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