TITLE

A Prediction Model for Wind Farm Power Generation based on Genetic-neural Network

AUTHOR(S)
Rui-lin Xu; Xin Xu; Xing-zhe Hou; Bo Zhu; Min-you Chen
PUB. DATE
August 2012
SOURCE
Journal of Convergence Information Technology;Aug2012, Vol. 7 Issue 14, p11
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
As a renewable energy source, wind turbine generators are considered to be important generation alternatives in electric power systems because of their non-exhaustible nature in the times of energy crisis. As wind power penetration increases, power forecasting is crucially important for integrating wind power into a conventional power grid. A short-term wind farm power output prediction model is presented using a neural network optimized by a genetic algorithm (GA). Using wind data from a wind farm in Inner Mongolia of China, a power forecasting map is illustrated, and a comparative study between a Back-Propagation (BP) neural network model and a GA-BP neural network model is undertaken.
ACCESSION #
100032943

 

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