DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-1,Issue-1 ( Mar, 2013 ) | |||||||||
Paper Title |
Increasing Online State of Wind Power Generation By Prediction of Wind Speed Using Optimised Probablistic Neural Network | |||||||||
Author Name |
S. Vinoth Kumar, K. Tamilarasi, P. S. Balamurugan | |||||||||
Affilition |
Department of CSE Karpagam University, Department of CSE Karpagam University, Department of CSE Karpgam Univeristy | |||||||||
Pages |
13-18 | |||||||||
Abstract |
A windmill offline stage which causes an effect in the production of power. In a season time due to heavy wind speed the generator exceeds the limit of RPM. It causes damage in the valuable part of the windmill. In this paper we proposed system to avoid an offline state and make the continuous production by using the optimized probabilistic neural network (OOPNN) [3]. The supervised learning algorithm using as a learning stage to store the dataset pattern. Optimized prediction error algorithm (OPEA) used for a more optimized error reducing in learning and make effective production. The predicted value is sent to the controller unit (CU). The CU maintains the speed of an the generator RPM by rotating the angle of the blade depends on the wind speed and also make increase load in gear to maintain the same level of RPM in the generator [7] [10]. | |||||||||
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