A Short Term Forecasting Method for Wind Power Generation System based on BP Neural Networks
Shenghui Wang, Xiaonan Liu, Yuexin Jin, Keding Qu · Advanced science and technology letters · 2015
This paper analyze and summarize the current situation as well as methods of forecasting wind power from home and aboard based on wind power development of China. Due to the BP neural network can approximate any nonlinear mapping with any arbitrary precision and its generalization ability is strong. This paper used BP neural network for power prediction, set up a model with numerical weather prediction data and wind power of a wind farm in Inner Mongolia Autonomous Region. Then used MATLAB to simulate and verify the feasibility of this prediction model The precision meet the requirements. In the last of this paper, the author development and design a simple system of wind power forecasting by using visual basic. The system has made the forecasting process to be simple and convenient. And also made easy to operation for the dispatcher.