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基于全息风险评估和组合赋权的电网建设项目投资决策方法 被引量:11

Investment Decision Method for Power Grid Construction Projects Based on Holographic Risk Assessment and Combination Weighting
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摘要 为了提高我国电网建设项目投资建设的精准性,本文提出了一种多个电网建设项目的投资决策方法。首先,通过深入分析我国电网建设项目特点和发展需求,根据电网建设项目投资建设时序,进行多维度、多视角识别风险来源,构建了全息风险评估指标体系;其次,根据风险影响后果对指标进行分类分析,构建电网建设项目投资决策风险评估模型;接下来,对指标进行赋权,构建基于风险影响后果的综合风险模型,考虑到当前赋权方法的不足和企业投资意愿,提出了一种新的组合赋权方法;最后,建立了考虑综合风险的电网建设项目投资决策模型;算例分析结果表明了本文所提投资决策方法的有效性和适用性。 In order to improve the accuracy of investment and construction of power grid construction projects,this paper proposes an investment decision-making optimization method for multiple power grid construction projects.This paper firstly analyzes the characteristics and development requirements of China’s power grid projects deeply.A holographic risk assessment index system is established for construction projects based on the multi-dimensional,multiperspective risk sources identification by using these projects’ time sequence.Secondly,the risk assessment model of construction projects investment decision is built up on the indexes classification according to the risk consequences.Then,the index is weighted to build a comprehensive risk model based on risk consequences. Meanwhile,a new weighting combination optimization method is proposed with the consideration of the investment willingness of enterprises,and designed to make an improvement of current weighting evaluation methods.Finally,the investment decision model of power grid construction projects considering comprehensive risks is established.The validity and applicability of the proposed evaluation method are verified by the case study.
作者 刘明华 刘文霞 刘晨苗 常源 刘宗歧 LIU Minghua;LIU Wenxia;LIU Chenmiao;CHANG Yuan;LIU Zongqi(School of Electrical and Electronic Engineering,North China Electric Power University,Beijing 102206,China)
出处 《现代电力》 北大核心 2019年第5期87-94,共8页 Modern Electric Power
基金 国家电网公司科技项目(SGTYHT/16-JS-198)
关键词 电网建设项目 指标体系 综合风险 组合赋权 投资决策模型 power grid construction project index system comprehensive risk combination weighting investment decision model
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