一种考虑气象因素的配电网设备故障关联挖掘模型
摘要：电网结构日益复杂，故障监测与防范的成本随之增大，而强对流天气的频繁出现使得设备故障与外界条件关联更加紧密，因此挖掘故障设备与故障因素间的关联关系，并对具有较高关联度的设备进行重点监测与防范，对电力系统的安全稳定运行具有重要意义。基于模糊频繁项挖掘算法，提出了1种考虑气象因素的配电网设备故障关联挖掘模型。该模型首先从多元信息库中提取故障特征数据，采用Relief-F算法排除相关程度较小的冗余特征，通过数据预处理与数据整合，构建包含气象因素的故障关联特征库。其次，以故障关联特征库为基础，引入模糊集理论，提出基于模糊频繁项集挖掘算法的故障因素与故障设备关联模型构建方法。最后，基于故障关联模型进行了算例分析，结果验证了所提方法的正确与有效性。
Abstract:The structure of the power grid is becoming more and more complex, and the cost of fault monitoring and prevention will increase. The frequent occurrence of strong convective weather makes equipment failures more closely related to external conditions. Therefore, it is of great significance for the safe and stable operation of the power system to excavate the correlation between the fault equipment and the fault factors, and to focus on the monitoring and prevention of the equipment with high correlation degree. Based on the fuzzy frequent item mining algorithm, a distribution network equipment fault association mining model that considers meteorological factors was proposed. The model first extracts fault characteristic data from a multivariate information database, uses the Relief-F algorithm to eliminate redundant features that are less relevant, and builds a fault associated characteristic database containing meteorological factors through data preprocessing and data integration. Secondly, based on the fault correlation feature database, the fuzzy set theory was introduced, and the method of fault factor and fault equipment association model construction was proposed based on the fuzzy frequent item set mining algorithm. Finally, an example was analyzed based on the fault correlation model, and the results verify the correctness and effectiveness of the proposed method.
标题：一种考虑气象因素的配电网设备故障关联挖掘模型
英文标题：A Model for Mining Association of Equipment Faults in Distribution Network Considering Meteorological Factors
作者：李丰君, 王子欣, 孙芊, 彭磊, 苗世洪,
关键词：关联规则, 气象因素, 模糊频繁项挖掘, 配电网, Relief-F算法,
发表日期：2023-08-10
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