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Hotspot Detection Method in Large Capacity Photovoltaic (PV) Farm
The obligation to use low carbon emissions power plants encourages the increased utilization of renewable energy generation. Among the whole renewable energy plants, photovoltaic (PV) is a modular plant that is easy to implement, which the utilization reaches 100GW in the year 2017. By the increasin...
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Published in: | IOP conference series. Materials Science and Engineering 2020-12, Vol.982 (1), p.12019 |
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description | The obligation to use low carbon emissions power plants encourages the increased utilization of renewable energy generation. Among the whole renewable energy plants, photovoltaic (PV) is a modular plant that is easy to implement, which the utilization reaches 100GW in the year 2017. By the increasing use of PV globally, the health of PV modules needs to be a concern because, during the operation, PV modules can experience various faults. Almost 50% of the overall fault is the hotspot which is very hard to detect on a wide area PV farm. For example, a 30 MW PV generation with an area of 60 hectares and composed of 126000 modules (consists of millions of cell), the existing hotspot detection methods takes up to 210 days. The long time and not continuous detection lets the hotspot to degrade and burn the modules. To prevent catastrophic failure due to hotspot, a detection method that can detect the fault quickly is needed. The proposed method, thermal imaging using a fish-eye lens could be used in this case as it has a very wide angle of view, which allows monitoring all of the PV modules in one detection period. |
doi_str_mv | 10.1088/1757-899X/982/1/012019 |
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subjects | Catastrophic events Modular equipment Modules Photovoltaic cells Power plants Renewable energy Renewable resources Thermal imaging |
title | Hotspot Detection Method in Large Capacity Photovoltaic (PV) Farm |
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