Abstract
The solar energy is getting popular due to the awareness of the environmental issues. Multiple module strings are set up in a solar-power plant to increase power production which is sold to electricity company via connected grid. Inevitably, devices can break, leading to loss of power production. To minimize the loss, it is important to be able to detect faulty devices as soon as possible for maintenance. In this paper, an approach relying on careful data pre-processing is proposed and compares with an existing approach.
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Acknowledgement
This work was partially supported by the grants from Ministry of Science and Technology, Reforecast Co., Ltd., and the Intelligent Recognition Industry Service Center.
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Hsu, CC., Li, JL., Chang, A., Chen, YS. (2019). An Enhanced Pre-processing and Nonlinear Regression Based Approach for Failure Detection of PV System. In: Chang, CY., Lin, CC., Lin, HH. (eds) New Trends in Computer Technologies and Applications. ICS 2018. Communications in Computer and Information Science, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-13-9190-3_27
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DOI: https://doi.org/10.1007/978-981-13-9190-3_27
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