Short Term Load Forecasting Research Based on Electricity Big Data
Wei Hu, Qian Ma, Chao Fang, Zheng Xiong, Cong Ji, Chunlin Zhong
Available Online September 2016.
- https://doi.org/10.2991/amitp-16.2016.13How to use a DOI?
- Electricity Information Acquisition System; Electricity Big Data; Short-term Load Forecasting
- 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.
- 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 BT - Proceedings of the 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016) 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 -