Proceedings of the 2016 International Conference on Education, Management Science and Economics

Prediction of City Saturated Load Based on Combined Logistic Model

Authors
Jing-min Wang, Jie Zhang
Corresponding Author
Jing-min Wang
Available Online December 2016.
DOI
https://doi.org/10.2991/icemse-16.2016.2How to use a DOI?
Keywords
City Saturated Load, logistic model, grey theory, combination forecast
Abstract
Accurate load forecasting is the prerequisite for efficient resources distribution among the power supply, power grid and the users. Based on traditional logistic model, data accumulated generating method and grade differential format are used to design the logistic of grade difference format. In the meanwhile, another two factors affecting power load, GDP and population, are introduced into the traditional logistic model, and next the rate of diffusion is turned into function to form the logistic expand model .Finally, combined logistic model is constructed by the combination of the weights from the error criteria of the two models. Compared to traditional logistic model, subjective parameters and constant environment can be avoided in the model. Thus, it can better reflect the dynamic growth trend of future urban electric load. With the application of the model, urban electricity saturation consumption and the arrival time in Beijing have been predicted. The result shows that Beijing would enter the stage of power saturation in 2023 and the saturation electricity consumption would be 121.5 billion kWh.
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Proceedings
2016 International Conference on Education, Management Science and Economics
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
December 2016
ISBN
978-94-6252-275-6
ISSN
2352-5398
DOI
https://doi.org/10.2991/icemse-16.2016.2How 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  - Jing-min Wang
AU  - Jie Zhang
PY  - 2016/12
DA  - 2016/12
TI  - Prediction of City Saturated Load Based on Combined Logistic Model
BT  - 2016 International Conference on Education, Management Science and Economics
PB  - Atlantis Press
SP  - 6
EP  - 9
SN  - 2352-5398
UR  - https://doi.org/10.2991/icemse-16.2016.2
DO  - https://doi.org/10.2991/icemse-16.2016.2
ID  - Wang2016/12
ER  -