Optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm
TK1006.M83 2017
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2024
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my.uniten.dspace-330002024-08-04T02:01:02Z Optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm Muhammad Aniq-Aiman Kamalluddin Distributed generation of electric power Renewable energy sources TK1006.M83 2017 Nowadays, electrical power demands increase rapidly and become unpredictable causing the company of electrical power supply facing problems such as power system losses with voltage instability and affecting reliability, power quality indices and cost. Therefore, the Distributed Generation (DG) has then become the most suitable and preferable solution especially renewable energy type due to its advantages. In order to install this DG at distribution line, the location and sizing of the DG is crucial to avoid other power system issues like overvoltage and instability. This thesis reports a development to find the most optimum placement and sizing of DG to minimize power losses and improve voltage stability. To determine the placement of the DG, Fast Voltage Stability Index (FVSI) becomes crucial to identify the condition and state of the bus system. Furthermore, to decide the sizing of the DG, artificial intelligence comes as a perfect method as it best in their capability for real time control, simpler and faster calculations and flexibility to various operating circumstances to obtain the most optimized value. Hence, in this research paper, genetic algorithm (GA) will be used to find the proper sizing of the DG. Power flow analysis then becomes the next-key analysis to evaluate the voltage magnitude and the line losses of the bus before and after the DG installation. Observations and research are done on IEEE 33 radial bus system using Matlab environment. 2024-07-30T07:41:41Z 2024-07-30T07:41:41Z 2017 Resource Types::text::Final Year Project https://irepository.uniten.edu.my/handle/123456789/33000 en application/pdf |
| institution |
Universiti Tenaga Nasional |
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UNITEN Library |
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Asia |
| country |
Malaysia |
| content_provider |
Universiti Tenaga Nasional |
| content_source |
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| url_provider |
http://dspace.uniten.edu.my/ |
| language |
English |
| topic |
Distributed generation of electric power Renewable energy sources |
| spellingShingle |
Distributed generation of electric power Renewable energy sources Muhammad Aniq-Aiman Kamalluddin Optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm |
| description |
TK1006.M83 2017 |
| format |
Resource Types::text::Final Year Project |
| author |
Muhammad Aniq-Aiman Kamalluddin |
| author_facet |
Muhammad Aniq-Aiman Kamalluddin |
| author_sort |
Muhammad Aniq-Aiman Kamalluddin |
| title |
Optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm |
| title_short |
Optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm |
| title_full |
Optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm |
| title_fullStr |
Optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm |
| title_full_unstemmed |
Optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm |
| title_sort |
optimal sizing and placement of renewable energy system for minimum power loss and voltage improvement in power system using genetic algorithm |
| publishDate |
2024 |
| _version_ |
1806517981564370944 |
| score |
13.222552 |