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DOI: 10.14569/IJACSA.2022.0130763
PDF

Data Collection Method for Energy Storage Device of Distributed Integrated Energy Station based on Double Decision Tree

Author 1: Hao Chen
Author 2: Guilian Wu
Author 3: Linyao Zhang
Author 4: Jieyun Zheng

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 7, 2022.

  • Abstract and Keywords
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Abstract: The distributed integrated energy station includes an electric energy storage device, heat storage device, cold storage device and other devices. Aiming at the problem of low data acquisition accuracy of energy storage device caused by using a single sensor or acquisition scheme in the existing methods, a new data acquisition method of energy storage device of distributed integrated energy station is designed based on double decision tree algorithm. The data acquisition process of double decision tree algorithm is constructed. On the basis of the process, the mathematical models of electric energy storage device, heat storage device, cold storage device and hybrid energy storage device are established. Then the double decision tree algorithm is used to solve the constructed model, and the acquisition pseudo code is given. So far, the data acquisition of distributed integrated energy station energy storage device based on double decision tree has been completed. The results of case analysis show that the accuracy of this method is higher than 98%, and the collection time is less than 30 ms.

Keywords: Double decision tree; distributed; integrated; energy station; energy storage device; data collection

Hao Chen, Guilian Wu, Linyao Zhang and Jieyun Zheng, “Data Collection Method for Energy Storage Device of Distributed Integrated Energy Station based on Double Decision Tree” International Journal of Advanced Computer Science and Applications(IJACSA), 13(7), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130763

@article{Chen2022,
title = {Data Collection Method for Energy Storage Device of Distributed Integrated Energy Station based on Double Decision Tree},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130763},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130763},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {7},
author = {Hao Chen and Guilian Wu and Linyao Zhang and Jieyun Zheng}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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