Paper
10 November 2022 Opto-electronic hybrid energy hydrogen production algorithm based on K-means technology
Xiaoxiao Xu, Ziwang Ye, Mingdan Han
Author Affiliations +
Proceedings Volume 12331, International Conference on Mechanisms and Robotics (ICMAR 2022); 1233151 (2022) https://doi.org/10.1117/12.2652610
Event: International Conference on Mechanisms and Robotics (ICMAR 2022), 2022, Zhuhai, China
Abstract
In recent years, problems such as climate deterioration, energy crisis and rapid population growth have gradually become a hot issue for all mankind. As an optional clean energy in the future, the development and utilization of hydrogen energy has focused the attention of the world. Based on the K-means big data clustering technology, this paper designs an optimal curve algorithm for calculating the photoelectric hybrid energy input ratio in the field of hydrogen manufacturing. This algorithm mainly analyzes the hydrogen output curve of a variety of photoelectric energy ratios within 24 hours, finds the best ratio at each time and introduces the Q function to evaluate the curve, so that the Q function value and the corresponding curve are at the corresponding time. The partial derivative of the curve and the output are inversely correlated, so that the calculated curve with the best ratio will also raise the output to a higher level under the premise that the smoothness is guaranteed. This algorithm improves the original fixed ratio and is equipped with a least squares data cleaning algorithm based on commercial experience, which effectively improves the accuracy of data in the research process.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaoxiao Xu, Ziwang Ye, and Mingdan Han "Opto-electronic hybrid energy hydrogen production algorithm based on K-means technology", Proc. SPIE 12331, International Conference on Mechanisms and Robotics (ICMAR 2022), 1233151 (10 November 2022); https://doi.org/10.1117/12.2652610
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KEYWORDS
Hydrogen production

Solar energy

Hydrogen

Data analysis

Optoelectronics

Data processing

Hydrogen energy

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