Intelligent solar module: Application of AI to improve failure rate due to Climate change
- Authors
- Park, Junhyun; Yoon, Guwon; Cho, Keonhee; Lee, Tacklim; Choi, Myeong-In; Park, Sehyun
- Issue Date
- Oct-2022
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Artificial Intelligence; Photovoltaic Generation Forecasting; Solar Energy
- Citation
- 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022
- Journal Title
- 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/67109
- DOI
- 10.1109/ICCE-Asia57006.2022.9954638
- ISSN
- 0000-0000
- Abstract
- This paper proposes a method to apply artific ial intelligence to prevent the failure of photovol taic modules and the degradation of energy effic iency. Intelligent solar modules can maintain m aximum energy efficiency while responding app ropriately to climate changes that can cause sol ar modules to fail such as heat waves, heavy sno w, and strong winds. Consumers can efficiently manage with monitoring applications and stably supply solar energy through these systems.
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Collections - College of ICT Engineering > School of Electrical and Electronics Engineering > 1. Journal Articles
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