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沿海区域输配电线路抵御强台风预警技术研究进展 被引量:17

Review on Research Progress in Early Warning Methods for Typhoon Disaster of Transmission and Distribution Lines
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摘要 台风灾害是导致沿海区域输配电线路故障的主要原因之一,灾前预警是抗台减灾的重要环节。目前,国内外采用的输配电线路抵御强台风预警方法一般仅考虑了台风路径和风圈范围,缺乏对台风灾害链的系统性描述,导致预警的针对性和有效性明显不足。为此,有必要深入开展沿海区域输配电线路抵御强台风预警技术的研究。首先基于输配电线路台风灾害链构建了预警体系;然后从因果、统计和混合预警3个方向综述了输配电线路抵御强台风预警方法的研究进展,并评述了各种方法的优缺点;最后提出了一种基于网格化、大数据和人工智能的输配电线路抵御强台风预警方法,并详细论述了方法的实现原理和关键技术,有望为电网台风灾害预警提供一种新的思路。 Typhoon disaster is one of the main reasons for the failure of coastal transmission and distribution lines, early warning of disasters is an important link of typhoon resistance and disaster reduction for the transmission and distribution lines. At present, the adopted early warning methods of resisting severe typhoon at home and abroad, generally only considered the path and wind range of typhoon. Because of the lack of a systematic description of the typhoon disaster chain for the transmission and distribution lines, the pertinence and effectiveness of early warning are obviously insufficient. Therefore, it is necessary to carry out in-depth studies on the early warning technology of resisting severe typhoon for coastal transmission and distribution lines. Firstly, early warning system of the typhoon disaster for transmission and distribution lines based on the disaster chain is constructed. Then, the research progresses early warning methods of resisting severe typhoon for transmission and distribution lines are summarizes from three aspects, including causality, statistics and mixed early warning, and the advantages and disadvantages of various methods are reviewed. Finally, an early warning method of resisting severe typhoon for transmission and distribution lines based on grid, big data and artificial intelligence is proposed, also the implementation principles and key technologies of this method are discussed in detail. It is expected to provide a new idea for early warning of typhoon disaster in power grid.
作者 陈彬 舒胜文 黄海鲲 张明龙 钱健 郭晓君 CHEN Bin;SHU Shengwen;HUANG Haikun;ZHANG Minglong;QIAN Jian;GUO Xiaojun(Electric Power Research Institute of State Grid Fujian Electric Power Co., Ltd., Fuzhou 350007, China;State Grid Cuhivating Laboratory of Wind Resistance and Disaster Mitigation Under Severe Typhoon Environment, Fuzhou 350007, China)
出处 《高压电器》 CAS CSCD 北大核心 2018年第7期64-72,共9页 High Voltage Apparatus
基金 国网公司科技项目(13KJ5401A093120170000) 福建省政府引导性项目(2017Y0063)~~
关键词 输配电线路 台风 灾害链 预警 大数据 人工智能 transmission and distribution lines typhoon disaster chain early warning big data artificial intelligence
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