Paper Title:
Risk Evaluation of the Wind Power Project Investment Based on BP Neural Network
  Abstract

With the rapid development of the society, more and more countries have been increasingly optimistic about wind power projects because of its advantages, such as non-polluting, renewable, energy-saving and emission reduction. While facing the temptation of high profit, it is necessary to assess the risks of wind power project investment scientifically. Therefore, this article combines with the risk characteristics of wind power project under the current social environment to build a evaluation index system of wind power project to evaluate the risk of wind power project based on BP neural network.

  Info
Periodical
Advanced Materials Research (Volumes 108-111)
Edited by
Yanwen Wu
Pages
256-261
DOI
10.4028/www.scientific.net/AMR.108-111.256
Citation
W. Li, S. C. Li, D. Wang, "Risk Evaluation of the Wind Power Project Investment Based on BP Neural Network", Advanced Materials Research, Vols. 108-111, pp. 256-261, 2010
Online since
May 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Xiao Yu Dong, Hai Bao, Lin Zhao, Lei Liu, Yong Hua Li
Chapter 3: Development and Utilization of Wind Energy
Abstract:With the intermittent and randomness of wind power,the power system needs to arrange certain spinning reserve capacity in response to wind...
2273
Authors: Shu Liang Liu, Yun Xia Song
Chapter 5: Urban Planning and Design
Abstract:Electric power industry is the basic industries. The power plant will face many risk factors in the investment of time. We need to make these...
981
Authors: Yan Ren, Yuan Zheng, Chong Li, Bing Zhou, Zhi Hao Mao
Chapter 3: Development and Utilization of Wind Energy
Abstract:The hybrid wind/PV/pumped-storage power system was the hybrid system which combined hybrid wind/PV system and pumped-storage power station....
719
Authors: Chuang Li, Min You Chen, Yong Wei Zhen, Ang Fu, Jun Jie Li
Chapter 9: Electrical Engineering Principles and Applications
Abstract:The traditional methods to adjust voltage in distribution network reactive power optimization is discretization,and it is difficult to...
1372
Authors: Yi Hui Zhang, He Wang, Zhi Jian Hu, Meng Lin Zhang, Xiao Lu Gong, Cheng Xue Zhang
Chapter 3: Development and Utilization of Wind Energy
Abstract:Extreme learning machine (ELM) is a new and effective single-hidden layer feed forward neural network learning algorithm. Extreme learning...
564