Industrial power demand forecasting based on big data technology orienting to energy internet: A case study of Hunan Province

2018 International Conference on New Energy and Future Energy System

Chen, J.^1,2 ; Chen, H.Y.^1,2 ; Wen, M.^1,2 ; Sun, S.^1,2

State Grid Hunan Electric Power Company Economic Research Institute, No. 398 New Shaodong Road, Changsha, Hunan

410000, China^1

Power Economic Research Room, Beijing Economy World Research Institute, No. 17 South Jianhua Road, Beijing

100022, China^2

关键词: Big data technologies;    Electric energies;    Electricity-consumption;    Energy internet;    Energy transmission efficiencies;    Goodness of fit;    Industrial power;    Olap technologies;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/188/1/012031/pdf
DOI  :  10.1088/1755-1315/188/1/012031

来源: IOP

【 摘 要 】

Making energy carry information is the major research direction of achieving Energy Internet. Besides, electric energy has incomparable advantages in energy transmission efficiency. Therefore, the future of Energy Internet is the Power Internet. Then, accurately predicting the consumption of power becomes the foundation of Energy Internet. Depending on the extraction, transformation, loading (ETL), Hadoop, Oracle and OLAP technologies. This paper establishes energy, electricity, economy forecasting and warning system. By considering the data of energy, electricity and economy together, a new economic power transmission model is established. The traditional econometric methods, such as OLS, AR, MA, ARMA and X11, are all employed during the estimated process. The estimating results demonstrate that the goodness of fits of the new models are all approximately equal to 0.998. The electricity consumption of industry is 1935224.28∗104 kWh in the 3rd quarter and 2,846,897.0 ∗104 kWh in the 4th in 2017, respectively.