Smart grid data analysis and prediction modeling

Hang Yang, Ping Li, Anum Masood, Yuning Xiao, Bin Sheng, Qichen Yu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

With the rapiddevelopment of power grid, prediction ofelectric quantity changes has become increasingly important. High-performance power grid systems can improve economic effectiveness and operational efficiency through accurate prediction. This paper proposes a prediction model based on temperature, humidity, time, and the number of people. On account of the standards of support vector machine (SVM) and the HBase platform, we have implemented a forecasting model and designed simulative experiments. The experimental results show that time and variation in the number of people has a remarkable influence on prediction, while temperature and humidityhardly have any effects.

Original languageEnglish
Title of host publicationPIC 2016 - Proceedings of the 2016 IEEE International Conference on Progress in Informatics and Computing
EditorsYinglin Wang, Yaoru Sun
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages541-544
Number of pages4
ISBN (Electronic)9781509034833
DOIs
Publication statusPublished - 15 Jun 2017
Externally publishedYes
Event4th IEEE International Conference on Progress in Informatics and Computing, PIC 2016 - Shanghai, China
Duration: 23 Dec 201625 Dec 2016

Publication series

NamePIC 2016 - Proceedings of the 2016 IEEE International Conference on Progress in Informatics and Computing

Conference

Conference4th IEEE International Conference on Progress in Informatics and Computing, PIC 2016
CountryChina
CityShanghai
Period23/12/1625/12/16

Keywords

  • Data mining
  • HBase data storage
  • Machine learning
  • Power prediction
  • SVM

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Health Informatics

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