TY - JOUR
T1 - Hotspot Detection Method in Large Capacity Photovoltaic (PV) Farm
AU - Pramana, P. A.A.
AU - Dalimi, R.
N1 - Funding Information:
The authors would like to express special thanks and acknowledgment to the Indonesia Endowment Fund for Education (Lembaga Pengelola Dana Pendidikan Indonesia) which gave the financial support for this research.
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/12/18
Y1 - 2020/12/18
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85098548489&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/982/1/012019
DO - 10.1088/1757-899X/982/1/012019
M3 - Conference article
AN - SCOPUS:85098548489
SN - 1757-8981
VL - 982
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 1
M1 - 012019
T2 - 2nd International Conference in Engineering, Technology and Innovative Researches, ICETIR 2020
Y2 - 2 September 2020 through 3 September 2020
ER -