摘要
现有电压暂降严重程度评估方法未充分考虑多元线路特征因素对输电线路故障概率的影响,评估结果存在较大误差。由此,文中提出了基于多元线路特征因素融合的电压暂降严重程度评估方法。首先,基于线路历史故障数据,采用关联规则量化多元线路特征因素对线路故障的影响程度进行研究。然后,通过改进D-S证据理论融合多元线路特征因素建立准确的线路年故障概率模型,并采用基于最大熵模型的故障点法评估节点的电压暂降量。最后,提出了一种同时考虑系统侧电压暂降严重程度和用户敏感设备耐受特性的综合电压暂降严重程度指标,用于评估节点电压暂降严重程度。基于实际电能质量监测数据进行验证,并与未充分考虑线路特征因素的评估案例进行比较,结果表明所提方法能有效提升电压暂降严重程度评估的准确性。
The existing methods for evaluating voltage sag severity do not sufficiently consider the effect of the multiple line characteristic factors on the line failure probability,which leads to a large error in the evaluation results.Therefore,an evaluation method for voltage sag severity based on multiple line characteristic factors fusion is proposed.Firstly,based on line historical fault data,the influence degree of multiple line characteristic factors on line fault which employ association rules to quantify is researched.Secondly,by improving the D-S evidence theory to fuse multiple line characteristic factors,an accurate line annual failure probability model is established,and the voltage sag severity of nodes by introducing maximum entropy into the method of fault positions are obtained.Finally,a comprehensive voltage sag severity index considering both voltage sag severity of power grid side and tolerance characteristics of sensitive equipment on the user side is proposed to evaluate node voltage sag severity.Based on the actual power quality monitoring data for validation and comparison with the evaluation cases that do not fully consider the line characteristic factors,the results show that the proposed method can effectively improve the accuracy of voltage sag severity evaluation.
作者
徐方维
贺东
郭凯
龙晨瑞
XU Fangwei;HE Dong;GUO Kai;LONG Chenrui(College of Electrical Engineering,Sichuan University,Chengdu 610065,China)
出处
《电力工程技术》
北大核心
2024年第2期94-104,共11页
Electric Power Engineering Technology
基金
国家自然科学基金资助项目(52277113)。
关键词
电压暂降
暂降严重程度
线路特征因素
关联规则
改进D-S证据理论
线路年故障概率
敏感设备
voltage sag
voltage sag severity
line characteristic factors
association rules
improving the D-S evidence theory
line annual failure probability
sensitive equipment
