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1000 MW级火电项目前期风险元传递模型
引用本文:王素花.1000 MW级火电项目前期风险元传递模型[J].电力建设,2013(11):125-128.
作者姓名:王素花
作者单位:大唐三门峡电力有限责任公司
摘    要:1000MW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1000 MW级火电项目前期风险元传递模型,以便为1000 MW级火电项目前期风险管理者提供决策依据.根据1000 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1000 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1000MW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:1000  MW级火电项目  风险元传递  蒙特卡洛模拟  BP神经网络

Risk Elements Transmission Model in Early Stage of 1000 MW Level Thermal Power Projects
WANG Suhua.Risk Elements Transmission Model in Early Stage of 1000 MW Level Thermal Power Projects[J].Electric Power Construction,2013(11):125-128.
Authors:WANG Suhua
Affiliation:WANG Suhua;Datang Sanmenxia Power Generation Co. ,Ltd.;
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.
Keywords:1 000 MW level thermal power project  risk elements transmission  Monte Carlo simulation  BPneural network
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