Electricity Consumption Forecast of Hunan Province Using Combined Model Based on Multivariate Linear Regression and BP Neural Network

DOI

10.2991/mcei-17.2017.138How to use a DOI?

Keywords

Multivariate linear regression; BP neural network; Combined model; Electricity consumption forecast of hunan province

Abstract

In recent years, the low energy consumption level and shortage of energy resources have become key factors restricting energy development and structural adjustment of Hunan Province. Therefore, load forecasting does play a significant role in making reasonable grid plan for Hunan Province. In this paper, by collecting and analyzing data of Hunan Power Grid, we identified the factors affecting electricity consumption, then used multiple linear regression method and BP neural network to predict the electricity consumption in the next nine years. The results showed that, the growth rate of electricity consumption of Hunan Province in next nine years is lower than that of the past ten years.

Copyright

© 2017, 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  - Yan Li
AU  - Shuyu Dai
AU  - Dongxiao Niu
PY  - 2017/12
DA  - 2017/12
TI  - Electricity Consumption Forecast of Hunan Province Using Combined Model Based on Multivariate Linear Regression and BP Neural Network
BT  - Proceedings of the 2017 7th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2017)
PB  - Atlantis Press
SP  - 651
EP  - 655
SN  - 2352-538X
UR  - https://doi.org/10.2991/mcei-17.2017.138
DO  - 10.2991/mcei-17.2017.138
ID  - Li2017/12
ER  -