The Short Term Load Forecasting of RBF Neural Network Power System Based on Fuzzy Control

DOI

10.2991/icence-16.2016.28How to use a DOI?

Keywords

Power system, Load forecasting, RBF neural network, Fuzzy control.

Abstract

This paper presents a kind of power system short-term load prediction algorithm based on fuzzy control and RBF neural network, to solve the problems of th traditional RBF neural network in electric power system short-term load forecast errors. Through the example verification, this method can improve the prediction accuracy compared with the traditional RBF load forecasting method, which has a good application prospect.

Copyright

© 2016, 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  - Jiangnan Ni
AU  - Guo Jin
PY  - 2016/09
DA  - 2016/09
TI  - The Short Term Load Forecasting of RBF Neural Network Power System Based on Fuzzy Control
BT  - Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
PB  - Atlantis Press
SP  - 133
EP  - 137
SN  - 2352-538X
UR  - https://doi.org/10.2991/icence-16.2016.28
DO  - 10.2991/icence-16.2016.28
ID  - Ni2016/09
ER  -