Load identification method of household smart meter based on decision tree algorithm
Shaoqing Shi,
Zhuo Xu and
Yong Xiao
International Journal of Global Energy Issues, 2022, vol. 44, issue 5/6, 440-453
Abstract:
In order to ensure the safe and economic operation of power grid, a load identification method of household smart meters based on decision tree algorithm is proposed. This paper pre-processes the missing data, noise data and inconsistent data in the load data of household smart meter, and uses the decision tree algorithm to predict the load data after pre-processing. According to the prediction results, combined with mathematical tools, from the PQ characteristics, current characteristics, V-I characteristics The load characteristics of household smart meters are extracted from the characteristics, harmonic characteristics and instantaneous characteristics and the objective function of load identification is constructed based on the combination of characteristics, so as to realise the load identification of household smart meters based on decision tree algorithm. Comparative results show that this method can reduce the error rate of load, to improve the efficiency of identification, identifying the shortest time of only 1.5 s.
Keywords: decision tree; household smart meter; load data; feature combination. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=125409 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:440-453
Access Statistics for this article
More articles in International Journal of Global Energy Issues from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().