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Locating distribution power system fault employing Bayes theorem with subjective logic

机译:利用贝叶斯定理和主观逻辑定位配电系统故障

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Prompt and effective power system restoration is essential for the minimization of downtime and cost which can get substantial rapidly after a system blackout. Most grids do not have the sensors to diagnose faults for algorithms that employ these measurements. Instead, assessment depends on customer calls that have lost power while the input of the field technician is not reflected into assessment in a formal way. This paper investigates fault location detection for service restoration based on a Distribution Automation System (DAS) with a centralized intelligence Bayesian probabilistic approach that takes into account field technician subjective opinion. The approach employs probabilistic logic and subjective logic based on evidence theory. A simplified model of distribution power system is employed to introduce new concepts that employ evidence theory with subjective and probabilistic logic to address the insufficient information.
机译:及时有效的电源系统恢复对于最大程度地减少停机时间和成本至关重要,而停机时间和成本可以在系统停电后迅速得到大幅提高。大多数网格都没有传感器来诊断使用这些测量值的算法的故障。相反,评估取决于失去电源的客户呼叫,而现场技术人员的输入未以正式方式反映在评估中。本文研究了一种基于配电自动化系统(DAS)的故障定位检测,以进行服务恢复,该系统采用集中智能贝叶斯概率方法,并考虑了现场技术人员的主观意见。该方法采用基于证据理论的概率逻辑和主观逻辑。采用简化的配电系统模型来引入新概念,这些新概念采用具有主观和概率逻辑的证据理论来解决信息不足的问题。

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