电网灾害损失信息融合分析与预测技术

Min Xu, Jian Yang, Jian Yang, Lin Peng, Shiyang Tang, Ning Li, Zhansheng Hou, Zhimin He, Gang Wang, He Wang, Xingchuan Bao, Hai Yu, Liang Zhu, Zehao Zhang, Jing Li, Tianxiong Gu, Yang Yang, Dai Ye
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引用次数: 0

摘要

在自然灾害袭击电网后,大量的报警信息会流入控制中心,特别是当电网出现复杂故障或自动装置出现异常时。由于保护、断路器误动、拒动、通道原因等存在一些不确定因素,因此一种能够实现不确定信息的灾害评估方法具有重要意义。传统的基于粗糙集的评价算法虽然可以处理不确定信息,但只能有效地处理离散数据。在实际应用中,数据是连续的,大部分是模糊的,概念之间的界限不是很清楚。模糊集可以克服这一缺点。创造性地提出了一种基于直觉模糊粗糙集的电网灾害及时准确评估方法。在评估中,采用属性过滤和数据清洗来降低灾难属性的冗余度;通过值过滤提取评价规则,通过匹配确定灾害等级,并随着形势的发展进行调整和更新,为应急决策提供科学依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Power Grid Disaster Loss Information Fusion Analysis and Prediction Technology
After the natural disaster attacks the power grid, a large number of alarm information will flow into the control center, especially when the power grid has complex faults or the automatic device acts abnormally. Because there are some uncertain factors in protection, circuit breaker misoperation, rejection and channel reasons, a kind of disaster assessment method that can realize uncertain information is of great significance. Although the traditional evaluation algorithm based on rough set can deal with uncertain information, it can only deal with discrete data effectively. In practice, there are continuous data and most of them are fuzzy, and the boundary between concepts is not very clear. Fuzzy set can overcome this disadvantage. This paper creatively proposes a method based on intuitionistic fuzzy rough set to evaluate power grid disasters timely and accurately. In the evaluation, attribute filtering and data cleaning are used to reduce the redundancy of disaster attributes; Through value filtering, the evaluation rules are extracted, the disaster level is determined through matching, and adjusted and updated with the development of the situation, so as to provide a scientific basis for emergency decision-making.
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