@inproceedings{cb1630f67d51417380dffb347d3fee0c,
title = "A Novel Single-Axis Solar Tracker Based on Reinforcement Learning",
abstract = "Solar panels with fixed angles can hardly consistently achieve maximum power output because the sun's rays are not always perpendicular to the panel. To address this problem, a single-axis solar tracker based on reinforcement learning (RL) is designed in this paper. The proposed RLbased solar tracker has a simple structure that no additional sensors or positioning devices are required. Therefore, the maintenance of the proposed tracker is easy to perform. Simulations have been conducted to validate the effectiveness of the proposed solar tracker. The results demonstrate that the mean absolute error (MAE) between the tracking tilt angle and the theoretical value is within a one-eighth degree.",
keywords = "reinforcement learning (RL), simulation, single-axis tracker, solar panel, solar tracker",
author = "Ming Huang and Ziqiang Bi and Jieming Ma and Xiaohui Zhu and Jie Zhang and Man, {Ka Lok}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 3rd International Conference on Industrial IoT, Big Data and Supply Chain, IIoTBDSC 2022 ; Conference date: 23-09-2022 Through 25-09-2022",
year = "2022",
doi = "10.1109/IIoTBDSC57192.2022.00067",
language = "English",
series = "Proceedings - 2022 International Conference on Industrial IoT, Big Data and Supply Chain, IIoTBDSC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "329--333",
booktitle = "Proceedings - 2022 International Conference on Industrial IoT, Big Data and Supply Chain, IIoTBDSC 2022",
}