• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2013, Vol. 34 ›› Issue (11): 125-128.doi: 10.3969/j.issn.1000-7229.2013.11.025

• 运行与管理 • 上一篇    

1 000 MW级火电项目前期风险元传递模型

王素花   

  1. 大唐三门峡电力有限责任公司,河南省三门峡市 472143
  • 出版日期:2013-11-01
  • 作者简介:王素花(1984),女,硕士研究生,主要从事工程造价、投资管理、招投标等工作,E-mai:wangsuhua_04513248@163.cm。

Risk Elements Transmission Model in Early Stage of 1 000 MW Level Thermal Power Projects

WANG Suhua   

  1. Datang Sanmenxia Power Generation Co., Ltd., Sanmenxia 472143, Henan Province, China
  • Online:2013-11-01

摘要:

1 000 MW级火电机组项目的开发前期存在诸多风险,这些风险的防控对投资者至关重要,为此建立了1 000 MW级火电项目前期风险元传递模型,以便为1 000 MW级火电项目前期风险管理者提供决策依据。根据1 000 MW火电项目前期风险元的特点,分析了风险元的分布情况,在此基础上构建了1 000 MW级火电项目前期风险元传递模型,运用蒙特卡洛模拟法确定了火电项目前期风险元发生的概率,探讨了火电项目前期风险元传递的结构,建立了1 000 MW级火电项目前期前馈(back propagation,BP)神经网络型风险元传递算法,并进行了算例仿真,构建了学习样本集,在Matlab 7.0平台上使用样本集对网络进行了训练和测试。测试结果表明,所建立的风险元传递模型具有正确性和可行性,该模型能有效控制项目投资风险。

关键词: 1 000 MW级火电项目, 风险元传递, 蒙特卡洛模拟, BP神经网络

Abstract:

There are many risks in the early stage of the construction of 1 000 MW level thermal power projects, and the prevention and control of these risks are critical to investors. Therefore, risk elements transmission model was built, which could provide decision-making basis for risk managers. According to the characteristics of risk elements in the early stage of 1 000 MW level thermal power project, the distribution of risk elements were analyzed. On this basis, the risk elements transmission model in the early stage of 1 000 MW level thermal power project was built to determine the occurrence probability of risk elements in the early stage by using Monte Carlo simulation method, and to discuss the risk elements transmission structure in the early stage of thermal power projects. Then the risk elements transmission algorithm with BP neural network was established in the early stage of thermal power projects, the example simulation was implemented to build a learning sample set, with which the network was trained and tested on Matlab 7.0 platform. The test results have shown that the model is correct and feasible, which can effectively control the project investment risk.

Key words: 1 000 MW level thermal power project, risk elements transmission, Monte Carlo simulation, BP neural network