计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 52-56.doi: 10.11896/jsjkx.191100210
石赫1, 杨群1, 刘绍翰1, 李伟2,3,4
SHI He1, YANG Qun1, LIU Shao-han1, LI Wei2,3,4
摘要: 为对电网调度部门保存的应急预案进行处理,以方便调度人员面临突发事件时能快速检索和匹配预案中的类似事故并借鉴以往经验处理突发事故,需要进行预案的信息抽取,提取其关键信息。传统的电网故障应急预案处理方法的通用性和可扩展性不强,无法有效实现电网故障应急预案的数字化。采用深度学习方法,对调度紧急预案的内容进行句法分析,得到分析树,在此基础上抽取出故障时系统的状态信息和对故障的处置要点,进而将非结构化的预案信息转化成结构化数据存储和管理。采用上述方法可以有效管理电网预案,辅助调度人员完成故障的判定并按预案给出的操作方法进行电网运行管理,从而提高故障处理效率。同时,该方法具有通用性好、扩展性强的优势,可以实现模型的持续改进。
中图分类号:
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