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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
