应用贝叶斯估计个别输电线路的中断率

Kai Zhou, J. Cruise, Chris J. I kill, I. Dobson, L. Wehenkel, Zhaoyu Wang, Amy L. Wilson
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引用次数: 1

摘要

尽管输电线路中断在电力系统可靠性分析中起着重要的作用,但从有限的数据中准确估计单个线路的中断率仍然是一个挑战。最近使用贝叶斯层次模型的工作展示了如何通过利用线路部分共享一些共同特征来将线路中断数据组合在一起,以获得更准确的线路中断率估计。从更少年份的数据中可以获得更低的方差估计。在本文中,我们探索使用实际效用数据使用这种新的贝叶斯分层方法可以实现什么。特别是,我们评估了检测线路中断率随时间增加的能力,量化了恶劣天气对中断率的影响,并讨论了中断率不确定性对简单可用性计算的影响。
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Applying Bayesian estimates of individual transmission line outage rates
Despite the important role transmission line outages play in power system reliability analysis, it remains a challenge to estimate individual line outage rates accurately enough from limited data. Recent work using a Bayesian hierarchical model shows how to combine together line outage data by exploiting how the lines partially share some common features in order to obtain more accurate estimates of line outage rates. Lower variance estimates from fewer years of data can be obtained. In this paper, we explore what can be achieved with this new Bayesian hierarchical approach using real utility data. In particular, we assess the capability to detect increases in line outage rates over time, quantify the influence of bad weather on outage rates, and discuss the effect of outage rate uncertainty on a simple availability calculation.
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