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Intelligent Power Source Selection for Solar Energy Optimization

delete2024-08-01
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PRE
AI
M
Mathew Habyarimana *
G
Gulshan Sharma
P
Pitshou N. Bokoro
K
Kingsley A. Ogudo
DOI:10.1109/ICABCD62167.2024.10645223delete
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摘要

摘要

En 中文
The automatic power source selection methods used in the different hybrid systems to select the required power supply according to the pre-selected requirements have encountered different challenges including the optimal use. The need for power source selection technology originates from the need of combining different source of energy such as electricity produced from biomass feedstocks; this energy makes the environment highly polluted due to greenhouse gas emissions and is inappropriate for densely populated areas, plus the availability of its resources, it needs to be combined with the renewable energy. In this research, solar energy is optimally used as an alternative energy by means of the power source selection technology. Without optimal use; the solar batteries end up either being overused shortening their lifetimes or underused, which is the main challenge in solar battery use. This research is an extension of the previous work, incorporating the design of the system that optimizes solar energy systems. The built prototype managed to increase the lifetime of the Winston battery from 2200 cycles at 80% DOD to 5000 cycles setting it to 50% DOD.
Keyword:
Optimization
selection
cycles
microcontroller
renewable

期刊

I
International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems
IF:
0
论文数:
4
被引数:
0

机构

U
University of Johannesburg
学者数:
6.8K
论文数: 6.8K
被引数: 1.2W
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