Earticle

초록

영어

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.

목차

Abstract
 1. Introduction
 2. Artificial Neural Network Model
  2.1. The Algorithm of BPNN
  2.2. The Design of BPNN
 3. Reality of BPNN Models
 4. The Development and Design of Forecasting System
 5. Error Analysis of the Forecasting Results
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Shenghui Wang [ Shenyang Institute of Engineering, Shenyang 110136, China ]
• Xiaonan Liu [ Shenyang Institute of Engineering, Shenyang 110136, China ] Corresponding author
• Yuexin Jin [ Shenyang Institute of Engineering, Shenyang 110136, China ]
• Keding Qu [ NorthEast China Grid Company Limited, Shenyang 110136, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605