陈勇杰, 贾雍, 柴彬, 沈澄泓, 周长星. 基于多数据融合的电力物资供应风险指数研究——以浙江某中型城市为例[J]. 电力大数据, 2022, 25(2): 46-54. DOI: 10.19317/j.cnki.1008-083x.2022.02.007
引用本文: 陈勇杰, 贾雍, 柴彬, 沈澄泓, 周长星. 基于多数据融合的电力物资供应风险指数研究——以浙江某中型城市为例[J]. 电力大数据, 2022, 25(2): 46-54. DOI: 10.19317/j.cnki.1008-083x.2022.02.007
CHEN Yong-jie, JIA Yong, CHAI Bin, SHEN Cheng-hong, ZHOU Zhang-xing. Risk Index of Power Material Supply Based on Multi Data Fusion:A Case Study of a Certain City in Zhejiang Province[J]. Power Systems and Big Data, 2022, 25(2): 46-54. DOI: 10.19317/j.cnki.1008-083x.2022.02.007
Citation: CHEN Yong-jie, JIA Yong, CHAI Bin, SHEN Cheng-hong, ZHOU Zhang-xing. Risk Index of Power Material Supply Based on Multi Data Fusion:A Case Study of a Certain City in Zhejiang Province[J]. Power Systems and Big Data, 2022, 25(2): 46-54. DOI: 10.19317/j.cnki.1008-083x.2022.02.007

基于多数据融合的电力物资供应风险指数研究——以浙江某中型城市为例

Risk Index of Power Material Supply Based on Multi Data Fusion:A Case Study of a Certain City in Zhejiang Province

  • 摘要: 为了保障配电网建设工作中的物资供应,降低物资供应风险,本文从供应链视角出发,将风险识别从需求侧向供应商前端和外部环境延伸和拓展,运用AHP层次分析法构建了一套配网物资供应风险评估模型。模型融合电力系统海量数据和气象、交通、征信等一系列数据,选择物资需求量、供应商产能情况、物资可调性、运输能力这四个因素为一级指标,其中供应商情况包含供应商复产情况、质量抽检/延期交货、信用评价三个二级指标,实现对配网工程物资供应风险的量化和分级。这个模型在实践应用中,提升了物资供应链条信息透明度,通过对高风险物资的统筹调配,有效防范了供应商风险或自然灾害等突发事件对工程建设带来的负面影响。本文最后对电力物资供应风险指数模型提出了进一步改进的方案。

     

    Abstract: In order to ensure the supply of materials in the construction of distribution network and reduce the risk of material supply, in this paper, from the view of supply chain, the risk identification is extended and expanded from the demand side to the front end of suppliers and the external environment, and a risk assessment model of distribution network material supply is constructed by using analytic hierarchy process method.The model integrates the massive data of power system and external information such as transportation, meteorology and credit investigation, and selects four factors: material demand, supplier situation, material adjustability and transportation capacity as the first-class indicators.The supplier situation includes three second-level indicators: supplier resumption, quality sampling/delayed delivery and credit evaluation.The model realizes the quantitative evaluation and classification of material supply risk of state grid projects.In practice, this model improves the information transparency of the material supply chain by coordinating the allocation of high-risk materials, effectively prevent the supplier risk or natural disasters and other emergencies on the construction of the negative impact.At last, this paper puts forward a further improvement scheme for the risk index model of power material supply.

     

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