Proceedings of the 2018 5th International Conference on Management Science and Management Innovation (MSMI 2018)

Electric Power Demand Forecasting of Jilin Province Based on Secondary Exponential Smoothing Model

Authors
Xiao-Dan GUO, Peng LI
Corresponding Author
Xiao-Dan GUO
Available Online April 2018.
DOI
10.2991/msmi-18.2018.13How to use a DOI?
Keywords
Electric power system, Demand forecast, Secondary exponential smoothing method.
Abstract

Under the background of rapid economic growth, the issue of electric power development has drawn increasing attention. Based on the economic development, energy structure, environment and other factors, this paper analyzes the influence factors of electric power demand. Then this paper develops a prediction model of electric power demand based on the secondary exponential smoothing model. At last, this model is used to predict the electric power demand of Jilin Province. This model is proven to be sufficient accurate with the posterior difference test.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 5th International Conference on Management Science and Management Innovation (MSMI 2018)
Series
Advances in Economics, Business and Management Research
Publication Date
April 2018
ISBN
978-94-6252-527-6
ISSN
2352-5428
DOI
10.2991/msmi-18.2018.13How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xiao-Dan GUO
AU  - Peng LI
PY  - 2018/04
DA  - 2018/04
TI  - Electric Power Demand Forecasting of Jilin Province Based on Secondary Exponential Smoothing Model
BT  - Proceedings of the 2018 5th International Conference on Management Science and Management Innovation (MSMI 2018)
PB  - Atlantis Press
SP  - 69
EP  - 74
SN  - 2352-5428
UR  - https://doi.org/10.2991/msmi-18.2018.13
DO  - 10.2991/msmi-18.2018.13
ID  - GUO2018/04
ER  -