Parameter extraction of PV modules using particle swarm optimization
Global warming and atmospheric pollution campaign has cause a global demand of clean energy for power generation, therefore needs for electrical energy increase daily, this need has led researcher to continue working on optimizing renewable energy for power generation such of photovoltaic energy....
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Format: | Thesis |
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Language: | English |
Subjects: | |
Online Access: | http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72316/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/72316/2/Full%20text.pdf |
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Summary: | Global warming and atmospheric pollution campaign has cause a global demand of clean
energy for power generation, therefore needs for electrical energy increase daily, this need
has led researcher to continue working on optimizing renewable energy for power
generation such of photovoltaic energy. However, lots of renewable energy research
approach recently is mostly on photovoltaic optimization techniques, For reliable and fast
design of photoelectric system development, an efficient and precise simulate is essential,
simulator tools is practically design for many purposes such as maximum power point
region prediction, to estimate the system efficiency and to understand the relationship
between Photovoltaic system and power converters. Maximum power point region tracking
and efficiency estimation is very crucial in PV module design as it is useful to determine
the type of converter requires and how this converter have to design in order for the system
to transfer optimum power to load. However, understand the relationship between
photovoltaic system and converters helps to determine overall energy yield prediction.PV
simulator comprises of different element, among all, the most important element is the PV
cell model itself. Therefore, it becomes compulsory to have high precision model that can
simulate and emulate the properties and behavior of PV cells such as fits the measured I-V
curve and to estimate data under different conditions. |
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