| 引用本文: | 杨靛青,叶锟锋.混合信息下智能变电站建设项目综合效益评价[J].电力系统保护与控制,2023,51(23):45-58. |
| YANG Dianqing,YE Kunfeng.Comprehensive benefit evaluation of smart substation construction projects from hybrid information[J].Power System Protection and Control,2023,51(23):45-58 |
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| 摘要: |
| 从智能效益、经济效益、绿色效益和安全效益4个维度构建了智能变电站建设项目综合效益评价指标体系。其中评价指标的属性值为包含语言变量、精确数和正态分布区间数的混合信息。在此基础上，基于直觉模糊集和组合赋权法，构建了一种面向混合信息的混合多准则决策模型。该模型首先用不同的转换规则将混合信息一致化为直觉模糊数的形式。然后采用基于合作博弈模型的群组决策特征根法-直觉模糊熵(group eigenvalue method intuitionistic fuzzy entropy, GEM-IFE)组合赋权法来确定指标的综合权重，并基于直觉模糊集建立了改进的逼近理想解排序方法(technique for order preference by similarity to ideal solution, TOPSIS)评价模型。最后，以10个智能变电站建设项目作为案例进行分析，并将该模型与传统的TOPSIS方法和单一赋权法进行比较。结果证明该混合多准则决策模型具有良好的鲁棒性。 |
| 关键词: 正态分布区间数 混合信息 混合多准则决策 直觉模糊 组合赋权法 TOPSIS方法 |
| DOI：10.19783/j.cnki.pspc.230496 |
| 分类号: |
| 基金项目:国家自然科学基金项目资助(71572040，72001126)；福建省自然科学基金面上项目资助(2021J1573) |
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| Comprehensive benefit evaluation of smart substation construction projects from hybrid information |
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YANG Dianqing, YE Kunfeng
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School of Economics and Management, Fuzhou University, Fuzhou 350108, China
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| Abstract: |
| A comprehensive benefit evaluation index system of a smart substation construction project is constructed from four dimensions of intelligent, economic, green and safety benefits. The attribute values of the evaluation indicators are the hybrid information containing linguistic variables, exact numbers and normal distribution interval numbers. A hybrid multi-criteria decision making model for hybrid information is constructed based on intuitionistic fuzzy sets and a combined weighting method. First, different transformation rules are used to uniformly convert the hybrid information into the form of intuitionistic fuzzy numbers. Then the GEM-IFE combination weighting method based on a cooperative game model is used to determine the comprehensive weight of indicators, and an improved TOPSIS evaluation model is established based on intuitionistic fuzzy sets. Finally, 10 smart substation construction projects are taken as cases for analysis, and this model is compared with the traditional TOPSIS method and single weighting method. The results show that the hybrid multi-criteria decision-making model has good robustness. |
| Key words: normal distribution interval numbers hybrid information hybrid multi-criteria decision-making intuitionistic fuzzy combination weighting method TOPSIS method |
