DocumentCode
3583335
Title
Outlier data forecasting of power load based on neural PSO
Author
Pan, Guanyu ; Yan, Hui ; Dou, Quansheng ; Li, Haijun
Author_Institution
Dept. of Inf. Eng., Jilin Bus. & Technol. Coll., Changchun, China
Volume
3
fYear
2010
Firstpage
1140
Lastpage
1142
Abstract
Load forecasting is a traditional research field of power system. This paper proposed a neural particle swarm algorithm which treats neural network as one of the particles in the swarm. The resulting optimized particle from the algorithm was used as the forecast model of the load forecasting. The model has been used in software system of load forecasting of JiLin power grid Co, Ltd. obtained desired results.
Keywords
load forecasting; neural nets; particle swarm optimisation; power grids; JiLin power grid Co, Ltd; forecast model; load forecasting; neural PSO; neural network; neural particle swarm algorithm; optimized particle; outlier data forecasting; power load; power system; software system; Artificial neural networks; Biological system modeling; Forecasting; Load forecasting; Load modeling; Particle swarm optimization; Predictive models; artificial intelligence; load forecasting; neuron network; particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5583678
Filename
5583678
Link To Document