Research Article
Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control
@ARTICLE{10.4108/ew.3815, author={Guipeng Weng}, title={Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control}, journal={EAI Endorsed Transactions on Energy Web}, volume={10}, number={1}, publisher={EAI}, journal_a={EW}, year={2023}, month={11}, keywords={fireworks algorithm, fuzzy control, PI control, adaptive, intelligent control of streetlights}, doi={10.4108/ew.3815} }
- Guipeng Weng
Year: 2023
Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control
EW
EAI
DOI: 10.4108/ew.3815
Abstract
As road traffic develops, energy-saving and efficient street lights have become a key research field for relevant professionals. To reduce street lights energy consumption, a fireworks algorithm is used to optimize the membership function parameters of fuzzy control and the initial parameters of PI control. A fireworks algorithm improved adaptive fuzzy PI solar LED street light control system is designed. The results showed that in the calculation of Root-mean-square deviation and Mean absolute error, the Root-mean-square deviation of the adaptive fuzzy PI control system improved by the fireworks algorithm was 0.213, 0.258, 0.243, 0.220, and the Mean absolute error was 0.143, 0.152, 0.154, 0.139, respectively, which proved that the prediction accuracy was high and the stability was good. In the calculation of the 1-day power consumption of the solar LED intelligent control system, the average power consumption of the designed solar LED intelligent control system was about 2000W, which was 25.9%, 47.4%, and 42.9% lower than the other three control methods, respectively. This proves that its energy consumption is low, and its heat generation is low, and the battery service life is long. The research and design of an adaptive fuzzy PI control solar LED street light intelligent control system has good performance, which can effectively achieve intelligent management and energy conservation and emission reduction in smart cities.
Copyright © 2023 G. Peng et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.