| Issue |
E3S Web Conf.
Volume 423, 2023
2023 7th International Workshop on Renewable Energy and Development (IWRED 2023)
|
|
|---|---|---|
| Article Number | 01008 | |
| Number of page(s) | 4 | |
| Section | Biomass Energy Conversion and Power Generation System Application | |
| DOI | https://doi.org/10.1051/e3sconf/202342301008 | |
| Published online | 08 September 2023 | |
Design of Edge Computing System for Photovoltaic Panel Hot Spot Detection Based on Machine Learning
State Grid Zhejiang Electric Power Co., Ltd. Research Institute
* Corresponding author. Tel.: + 86 - 0571 - 51211778. E-mail address: caijie_2023@163.com Address: 1 Huadian Rd., Hangzhou, Zhejiang, 310012, China
The hot spot effect of photovoltaic panel refers to the local heating phenomenon caused by the photovoltaic panel being covered, which not only seriously affects the power generation efficiency of photovoltaic panel, but also is one of the most important factors threatening the service life of photovoltaic panel. In this paper, an edge computing system was designed to detect hot spot effect based on real-time sensing data such as current, voltage and illuminance. The system consists of three parts: data acquisition side, data processing side and data display side. The hot spot detection algorithm model based on machine learning is deployed on the edge side, which can detect the degree of hot spot effect and locate the hot spot according to the sensor data of each photovoltaic panel in real time. Additionally, this system could push the data to the cloud management platform and each user terminal to realize remote operation and maintenance.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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