Proceedings of the 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016)

Short Term Load Forecasting Research Based on Electricity Big Data

Authors
Wei Hu, Qian Ma, Chao Fang, Zheng Xiong, Cong Ji, Chunlin Zhong
Corresponding Author
Wei Hu
Available Online September 2016.
DOI
https://doi.org/10.2991/amitp-16.2016.13How to use a DOI?
Keywords
Electricity Information Acquisition System; Electricity Big Data; Short-term Load Forecasting
Abstract
With global information technology development, the era of big data is in the offing. Power industry is closely related with people's livelihood and it is necessary to introduce big data technology to improve its economy and reliability. The completion of Jiangsu Electricity Information Acquisition System and the accumulation of historical information both laid a rich foundation for the study of the electricity big data. Jiangsu Electricity Power Company has an advantage and it is necessary to take full advantage of electricity big data to carry out related researches. Based on electricity big data, research works on short-term load forecasting were carried out in this paper, which had achieved some results and made a certain contribution for the promotion of big data technology in Jiangsu Electricity Power Company.
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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
978-94-6252-245-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/amitp-16.2016.13How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wei Hu
AU  - Qian Ma
AU  - Chao Fang
AU  - Zheng Xiong
AU  - Cong Ji
AU  - Chunlin Zhong
PY  - 2016/09
DA  - 2016/09
TI  - Short Term Load Forecasting Research Based on Electricity Big Data
PB  - Atlantis Press
SP  - 68
EP  - 71
SN  - 2352-538X
UR  - https://doi.org/10.2991/amitp-16.2016.13
DO  - https://doi.org/10.2991/amitp-16.2016.13
ID  - Hu2016/09
ER  -