Author(s)

Libyan Song ¹, Xiaorong Zhang ²

Affiliation(s)

¹ School of Electrical and New Energy, China Three Gorges University, Yichang, Hubei, 443002, China
² State Grid Shanxi Jiexiu Power Supply Company, Jiexiu, Shanxi, 032000, China

Corresponding Author

Libyan Song

ABSTRACT

With the rapid development of artificial intelligence technology on a global scale, it will affect the future development trend of the electrical industry to a large extent. According to the research on the automation control technology of air-conditioning equipment in shopping malls, the research on the automation control technology of low-voltage electrical equipment based on artificial intelligence is proposed. In the design of artificial intelligence low-voltage electrical equipment automation control technology, firstly, a brief overview of low-voltage electrical equipment automation control technology, through analysis of low-voltage electrical equipment automation control technology composition and use process, The air conditioning system based on fuzzy neural network is studied in detail. Using artificial intelligence to showcase the technical examples in the automation control of electrical equipment, study the automation energy-saving optimization countermeasures of air-conditioning equipment in shopping malls, and clarify the important management projects of air-conditioning active energy-saving and energy-saving, and commit to the important management projects of air-conditioning active energy-saving.

KEYWORDS

Artificial intelligence, Low voltage electrical, Automation control, Technology

CITE THIS PAPER

Libyan Song, Xiaorong Zhang, Research on Automatic Control Technology of Low Voltage Electrical Equipment Based on Artificial Intelligence. Adult and Higher Education (2021) 3: 113-116. DOI: http://dx.doi.org/10.23977/aduhe.2021.030323.

REFERENCES

[1] Li Bohu, Chai Xudong, Zhang Lin, et al. Preliminary research on modeling and simulation technology for new artificial intelligence systems [J]. Journal of System Simulation, 2018, 30(2):349-362.
[2] Cheng Lefeng, Yu Tao, Zhang Xiaoshun, et al. Smart energy dispatching robots and their knowledge automation in information-physical-social integration: framework, technology and challenges [J]. Chinese Society for Electrical Engineering, 2018, 38(1):25-40.
[3] Xu Yufeng, Liu Lijun, Huang Qingsong, et al. Research on TF-IDF weight improvement algorithm in intelligent medical guidance system [J]. Computer Engineering and Applications, 2017, 53(4):238-243.

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