引用本文:罗 昆,高 伟,洪 翠.考虑群体决策差异冲突解决机制的配电站房健康状态评估方法[J].电力系统保护与控制,2024,52(10):167-178.
LUO Kun1,GAO Wei,HONG Cui.Health condition assessment method of a distribution station using a groupdecision-making difference conflict resolution mechanism[J].Power System Protection and Control,2024,52(10):167-178
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考虑群体决策差异冲突解决机制的配电站房健康状态评估方法
罗 昆1,高 伟1,2,洪 翠1
1.福州大学电气工程与自动化学院,福建 福州 350108;2.智能配电网装备 福建省高校工程研究中心,福建 福州 350108
摘要:
针对配电站房缺乏健康评估机制、运维周期设置不合理的问题,提出了一种考虑群体决策差异冲突解决机制的配电站房健康状态综合评估方法。首先,建立配电站房指标体系和专家评价框架,设计了一种新型的二元冲突测量函数来量化全局冲突。然后,使用专家评价结果的虚假度、可信度、可用度等测度指标构造专家修正因子,以改进D-S证据理论,通过聚合不同专家的评价意见来量化评价指标的权重。接着,建立改进灰色关联度-逼近理想解法(grey relation analysis-technique for order preference by similarity to an ideal solution, GRA-TOPSIS)评估模型,引入灰色关联接近度,与距离接近度融合得到综合接近度,改善TOPSIS评价判据片面性的缺陷。最后,计算每个配电站房的评价值与理想解之间的综合接近度,反映配电站房的健康状态。实验分析表明该方法能兼容专家评价之间的冲突性、差异性、不确定性,与现有方法相比评估结果更具准确性和合理性,对运维人员制定合理的检修决策具有一定的指导价值。
关键词:  配电站房  专家评价框架  改进D-S证据理论  专家修正因子  改进GRA-TOPSIS评估方法
DOI:10.19783/j.cnki.pspc.240039
分类号:
基金项目:福建省自然科学基金项目资助(2021J01633)
Health condition assessment method of a distribution station using a groupdecision-making difference conflict resolution mechanism
LUO Kun1, GAO Wei1, 2, HONG Cui1
1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; 2. Fujian Province University Engineering Research Center of Smart Distribution Grid Equipment, Fuzhou 350108, China
Abstract:
To tackle the absence of health assessment mechanisms and the irrational maintenance cycles at distribution stations, a comprehensive evaluation method is introduced, integrating a conflict resolution mechanism for group decision-making differences. First, the method sets up an indicator system and an expert evaluation framework, featuring a novel binary conflict measurement function to quantify overarching conflicts. Subsequently, expert correction factors are devised using metrics like falseness, credibility, and usability of expert evaluations to enhance the D-S evidence theory. This adjustment facilitates the weighting of evaluation indicators through the aggregation of various expert opinions. Also, an improved GRA-TOPSIS model is established, integrating grey relational and distance closeness to yield a comprehensive closeness, improving TOPSIS’s one-sided criteria. Finally, this approach calculates the overall closeness between each station’s evaluation value and the ideal solution, accurately reflecting its health status. Experimental analysis reveals that this method effectively reconciles conflicts, differences, and uncertainties in expert evaluations, offering more precise and sensible assessment outcomes, thus providing valuable guidance for maintenance decision-making.
Key words:  distribution station  expert evaluation framework  improved D-S evidence theory  expert correction factor  improved GRA-TOPSIS evaluation method
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