配电网停电管理系统

G. Kumar, N. Pindoriya
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引用次数: 15

摘要

停电检测是配电停电管理系统(OMS)的首要环节。非计划停电检测对于提高配电系统的可靠性和可达性具有重要意义。传统上,客户的故障呼叫是中断通知的主要来源。然而,在停电的第一个小时内,客户只报告了三分之一的停电。高级计量基础设施(AMI)可以几乎立即向公用事业公司发送停电通知,也可以在电力恢复时发出恢复通知。由于通信信道噪声,AMI数据可能会损坏,并且由于临时中断,还可能存在不必要的中断通知。本文提出了一种算法来过滤由于数据损坏和持续时间小于1分钟的临时中断引起的电表通知。采用概率和模糊隶属函数对AMI数据过滤器进行建模,以去除损坏的数据。提出了基于模糊隶属函数模型的配电监控与数据采集(SCADA)系统与AMI系统的集成,实现停电定位。在径向分布试验给料机上对所提模型进行了试验,并对试验结果进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Outage management system for power distribution network
Outage detection is the first and foremost step in the electric power distribution outage management system (OMS). Unplanned outage detection is very important for improving the distribution system reliability and accessibility. Traditionally, customers' trouble calls are the primary source of outage notification. However, customers report only one third of outages in the first hour of outages. The advanced metering infrastructure (AMI) could send outage notifications almost instantly to the utility and could also give restoration notification when power is restored. AMI data may be corrupted due to communication channel noise and there may also be unnecessary outage notifications due to the temporary outages. In this paper, an algorithm is proposed to filter out the meter notifications due to corrupted data and temporary outages of duration less than one minute. An AMI data filter is modelled by probabilistic and fuzzy membership functions to remove the corrupted data. Integration of distribution supervisory control and data acquisition (SCADA) system with AMI for outage location finding is also proposed by fuzzy membership function based model. Proposed models have been tested on a radial distribution test feeder and results are analysed.
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