Mid-Term Load Forecasting Based on Grey Neural Network Corrector Model

DOI

10.2991/icismme-15.2015.300How to use a DOI?

Keywords

load forecasting; related factors; grey model; BP neural network

Abstract

A novel grey neural network corrector model is presented in this paper, because mid-term load forecasting is affected by many factors and has large research space. This method combines BP neural network with 3 kinds of grey models, and selects influential factors by grey related analysis method, and then adds the equal dimension and new information technology. The validity of the novel model can be tested by utilizing actual data of a certain area. Comparing with 3 kinds of grey models, the novel model can improve the accuracy of load forecasting results. Experimental results prove that this method is feasible and effective to mid-term load forecasting.

Copyright

© 2015, 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  - Chao Yang
AU  - Yunliang Wang
PY  - 2015/07
DA  - 2015/07
TI  - Mid-Term Load Forecasting Based on Grey Neural Network Corrector Model
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 1405
EP  - 1409
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.300
DO  - 10.2991/icismme-15.2015.300
ID  - Yang2015/07
ER  -