期刊文献+

基于人工智能的电网调度操作智能防误系统建设及实践 被引量:8

Construction and practice of intelligent error proof system for power grid dispatching operation based on artificial intelligence
下载PDF
导出
摘要 本文将人工智能算法引入电网调度业务,结合调度规程和指令规范,通过语音识别平台实时转化调度电话为文本信息,对于识别的文字通过语义理解、深度学习提取关键词,识别和探测业务场景。利用提取的关键信息在电网操作平台基于电网实时状态校核、调度业务场景规则进行校核和防误。通过语音平台对于不规范和不正确的调度指令进行告警和提示。通过运行操作历史大数据不断学习发现规律,建立完善的调度业务知识图谱,不断提高语音识别的准确率和场景探测的准确度,进而实现调度电话业务24小时安监的功能。本系统实现了操作全过程状态、潮流等全链条智能防误管控,可解决电话下令时由于监护不到位、下令不规范、调度指令理解错误等情况发生时,调度误下令、误操作问题。 In this paper,artificial intelligence algorithms are introduced into the power grid dispatch business.Combined with dispatch procedures and instruction specifications,the dispatch phone is converted into text information through a voice recognition platform in real time.Key words are extracted through semantic understanding and deep learning for the recognized text to identify and detect business scenarios.The extracted key information is used to verify and prevent errors on the grid operation platform based on the grid real-time status verification and scheduling business scenario rules.Alarms and prompts for irregular and incorrect scheduling instructions through the voice platform.Through the operation and operation of historical big data,it constantly learns and discovers laws,establishes a perfect knowledge map of dispatching services,and continuously improves the accuracy of voice recognition and the accuracy of scene detection,thereby realizing the function of 24-hour security supervision of dispatching telephone services.The system realizes full chain intelligent anti-misoperation management and control of the entire process status and current flow,which can solve the problems of dispatching wrong orders and misoperations when the phone is ordered due to inadequate monitoring,irregular orders,and incorrect understanding of scheduling instructions.
作者 蔡新雷 齐颖 CAI Xinlei;QI Ying(Electric Power Dispatching and Control Center of Guangdong Power Grid Co.,Ltd.,Guangzhou 510600 Guangdong,China;Guangdong Rural Credit Union Bank YINXIN Center,Guangzhou 510600 Guangdong,China)
出处 《电力大数据》 2020年第4期16-23,共8页 Power Systems and Big Data
关键词 人工智能 语音识别 大数据 防误 校核 artificial intelligence speech recognition big data error proofing check
  • 相关文献

参考文献14

二级参考文献214

共引文献2392

同被引文献74

引证文献8

二级引证文献26

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部