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基于回归预测的母线电量不平衡率异常分析方法
沈天时, 王俊翔, 时宇飞
(国网上海市电力公司市北供电公司)
Abnormality Analysis of Electricity Unbalance Rate of Busbar Based on Regression Forecasting
shentianshi, Junxiang Wang, Yufei Shi
(Shibei Electric Power Supply Company, State Grid Shanghai Power Company)
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投稿时间:2024-11-10    修订日期:2024-12-16
中文摘要: 母线电量不平衡率是衡量供电企业经济技术水平的重要标尺。随着变电站改造升级,当母线不平衡率出现异常时,仅靠现场调试、SCADA数据比对等传统方法进行排查效率低下或易无功而返。为克服这一问题,本文提出集成负荷预测与电能采集系统的在线分析方法,运用回归算法得出电量变化趋势,通过将电量预测值与采样值进行比对,实现数据异常监测,提升消缺快速性和准确性,并据此设计了包含母线-线路拓扑判定、故障定位、故障定型的母线不平衡率异常分析流程。最后算例分析验证了该平台方案的有效性。
Abstract:Electricity unbalance rate of busbar is the vital ruler for measuring economic and technological level of power supply enterprises. With the reforming and upgrading of substations, the abnormality of electricity unbalance rate of busbar can not be judged high efficiently and successfully only by traditional methods such as on-site inspection or SCADA data comparison. In order to overcome this problem, this paper proposes an online analysis method based on load forecasting and energy collection system, obtaining load variation trend through regression algorithm, monitoring data abnormality by comparing load forecasting value and sampling ones, promoting fault elimination efficiency and accuracy, also devising steps of abnormality analysis of electricity unbalance rate of busbar including topology identification, fault location fixing, fault type determination according to the method. the method is also proved to be effective by a calculation example.
文章编号:20241110001     中图分类号:    文献标志码:
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