基于变权灰关联的智能配电网用电可靠性提升对象优选
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(华南理工大学电力学院,广东 广州 510000)

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莫一夫(1991—),男,通信作者,硕士研究生,研究方向为智能配电网规划与评估;E-mail:moyifu@126.com
张勇军(1973—),男,博士,教授,研究方向为电力系统运行分析与控制。

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国家自然科学基金重点资助项目(51777077)


Optimal object selection of power utilization reliability promotion for smart distribution grid based on weighted grey correlation
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(School of Electric Power, South China University of Technology, Guangzhou 510000, China)

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    摘要:

    用电可靠性提升工程是电网企业新时代提升服务质量的重要手段。基于智能配电网的“用电可靠性”新概念构建了用电可靠性提升需求评估指标体系。由此建立了智能配电网用电可靠性提升对象优选模型,并在模型中利用一种结合层次分析法和改进熵权法的综合赋权方法对各指标进行变权处理,使得赋权更加合理。同时引入绝对理想点理论和灰色关联度对传统逼近理想法进行改进,有效地避免了逆排序问题带来的评估误差,准确地优选出急需进行用电可靠性改造的配电网,实现可靠性提升工程的效益最大化。最后通过实例分析,验证了该模型的有效性和实用性。

    Abstract:

    Power utilization reliability advancement engineering for smart distribution grid is an important means for power grid enterprises to improve their management and service quality. Considering the new concept of power utilization reliability for smart distribution grid, this paper establishes an index system to evaluate demands of power utilization reliability promotion. Hence an optimal object selection model of power utilization reliability promotion is set up, and a comprehensive weight method combined with analytic hierarchy process and improved entropy method is used to vary the index weight. Meanwhile, the traditional technique for order preference by similarity to ideal solution is improved based on absolute ideal solution theory and grey correlation degree, which can avoid the error caused by the reverse order problem. According to the result, the smart distribution grids needed to be improved most are selected out, which is better to maximize social and economic benefits. Finally, the effectiveness of index system and model is verified with an example. This work is supported by Key Project of National Natural Science Foundation of China (No. 51777077).

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莫一夫,张勇军.基于变权灰关联的智能配电网用电可靠性提升对象优选[J].电力系统保护与控制,2019,47(5):26-34.[MO Yifu, ZHANG Yongjun. Optimal object selection of power utilization reliability promotion for smart distribution grid based on weighted grey correlation[J]. Power System Protection and Control,2019,V47(5):26-34]

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  • 收稿日期:2018-04-03
  • 最后修改日期:2018-07-20
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  • 在线发布日期: 2019-03-06
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