The Short Term Load Forecasting of RBF Neural Network Power System Based on Fuzzy Control
Jiangnan Ni, Guo Jin
Available Online September 2016.
- 10.2991/icence-16.2016.28How to use a DOI?
- Power system, Load forecasting, RBF neural network, Fuzzy control.
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.
- © 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/).
Cite this article
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 -