Neural Network in the Anticipation of Electricity Use: An Investigation from Micro and Macro Perspectives

DOI

10.2991/aebmr.k.191217.059How to use a DOI?

Keywords

Wavelet analysis, BP neural network, Seasonal adjustment model

Abstract

In our contemporary fiscal lives continuously expanded by technological innovations, electricity is playing an increasingly momentous role. That said, ameliorating electricity consumption anticipation has become a most imminent and pressing issue. Considering the large quantity and high frequency of electric load data (96*197 groups), this paper, from a micro perspective, combines wavelet decomposition with BP neural network to forecast the electric load data of users. The results show that the prediction results are better than that of purely using BP neural network. In addition, from a macro perspective, this paper analyzes the essential factors of electricity consumption in China. Through establishing seasonal adjustment model, our research predicts China’s electricity consumption in the next 10 years. The result indicates that the electricity consumption reaches its peak of 2008.541 billion kWh in the third quarter of 2024, and the power supply should be planned well in advance.

Copyright

© 2019, 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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TY  - CONF
AU  - Mingyuan Zhou
AU  - Yufeng Xiao
AU  - Yanqing Ma
PY  - 2019
DA  - 2019/12/20
TI  - Neural Network in the Anticipation of Electricity Use: An Investigation from Micro and Macro Perspectives
BT  - Proceedings of the 2019 International Conference on Economic Management and Cultural Industry (ICEMCI 2019)
PB  - Atlantis Press
SP  - 335
EP  - 348
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.191217.059
DO  - 10.2991/aebmr.k.191217.059
ID  - Zhou2019
ER  -