为确定配电中压地下电缆报警系统,进行了可行性分析

R. Bonanno, M. Lacavalla
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引用次数: 4

摘要

本文对城市地下配电电缆故障预警系统的可行性进行了研究。近年来,能源分配公用事业公司观察到地下电缆中断的频率显著增加,主要集中在城市地区。对于这种类型的停电,警报系统的定义要求配电公司提供故障/停电。我们考虑了米兰市的第一个案例研究,其中2012-2015年期间的电力故障事件可供我们使用。气象数据的可用性也至关重要,无论是在大气方面还是在诸如土壤温度和土壤湿度等变量方面,以便突出与停电的相关性。所有这些变量都可以在RSE目前使用的预报和气象再分析模式的输出中找到。通过分析TERNA公布的实际负荷数据,还评估了电力需求对故障的影响,该数据可以被认为是估计米兰市区负荷的代理。最后,还考虑了与故障数据相关的其他变量,例如典型的带循环电流的地下导体的表皮温度或用于识别夏季热浪的其他大气变量(例如2m的气温)。一旦评估了故障与上述变量之间的相关性,最后就米兰市开发了一个统计模型,以提供具有相对相关不确定性的每日故障率的估计。该模型展示了一个相当好的解释方差(约50%),并显示了影响故障预测的变量如何与实际负载、空气温度和深层土壤湿度相关联。这项工作是为实施一个警报系统作准备,该系统用于预测可能导致地下电力线广泛故障的危急情况。然而,为了达到这一目的,与配电公司的强大协同作用是必要的,以获得意大利其他城市地区的其他故障时间序列。
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A feasibility analysis aimed at defining an alert system for Distribution MV Underground Cables
In this work, a feasibility study of an alert system for predicting the failure of underground distribution cables in urban areas was assessed. In recent years, energy distribution utilities have observed a significant increase in the frequency of outages on underground cables, mostly concentrated in urban areas. The definition of an alert system for this type of outages required to have failures/outages provided by distribution power utilities. A first case study for the city of Milan was considered where power fault events were made available to us for the period 2012-2015. The availability of meteorological data was also of crucial importance, both in the atmosphere and on variables such as soil temperature and soil moisture in order to highlight the correlations with the outages. All these variables could be found as outputs of the forecast and meteorological reanalysis models currently in use in RSE. The influence of electricity demand on faults was also assessed by analyzing the Actual Load data published by TERNA, which can be considered a proxy for estimating the load for the urban area of Milan. Finally, other variables that could be correlated with the fault data were also considered, such as the skin temperature of a typical underground conductor with circulating current or other atmospheric variables for the identification of summer heat waves (e.g. the 2m air temperature). Once the correlations between the failures and the variables mentioned above have been assessed, a statistical model was finally developed on the city of Milan, to provide an estimate of the daily rate of failures with relative associated uncertainties. This model demonstrates a fairly good explained variance (about 50%) and shows how the variables that influence most the prediction of failures are associated with the Actual Load, air temperature and deeper soil moisture. This work is preparatory to the implementation of an alert system for predicting critical situations that may lead to widespread failures of underground power lines. To this end, however, a strong synergy with the distribution utilities is necessary to obtain other time series of faults also in other Italian urban areas.
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