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基于大数据应用和人工智能决策的电网辅助控制体系探讨 被引量:2

Discussion on Power Grid Auxiliary Control System Based on Big Data Application and Artificial Intelligence Decision
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摘要 针对电网实时调度业务引入人工智能技术,基于大数据应用和人工智能思维决策,以安全防误为准则,打通横纵向业务系统,构建辅助调控人员开展日常业务工作的一体化、自动化、智能化的体系。该体系实现了降低调控人员负载率及提高电网操作安全性、便捷性的目标,具备安全防误、基于专家库的主动电网异常辅助决策等能力,实现了辅助驾驶与自动驾驶,具备“高参、指挥”能力,利用机器学习扩充知识库,主动感知分析电网运行事件进行辅助决策或自主处置,提升了调度业务水平和电网安全性。 Based on big data applications and artificial intelligence thinking decisions,the power grid real-time dispatch business introduces artificial intelligence technology.Taking safety and error prevention as the criterion,the horizontal and vertical business system is opened up,and an integrated,automated and intelligent system that assists regulators in their daily business work is built.The system achieves the goal of reducing the load rate of control personnel and improving the safety and convenience of power grid operation.It has the ability of safety and error prevention,active power grid abnormal auxiliary decision-making based on expert database.Assistant driving and automatic driving are realized,and it has the ability of"high participation and command".Machine learning is used to expand the knowledge base,and active perception and analysis of power grid operation events are used to assist decision-making or autonomous disposal,so as to improve the level of dispatching service and power grid security.
作者 蔡新雷 齐颖 CAI Xinlei;QI Ying(Electric Power Dispatching and Control Center of Guangdong Power Grid,Guangzhou 510600,China;Guangdong Huaxing Bank,Guangzhou 510600,China)
出处 《电工技术》 2021年第6期40-42,共3页 Electric Engineering
关键词 调度业务 人工智能 大数据驱动 辅助控制 dispatching business artificial intelligence big datadriven auxiliary control
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  • 1曹一家,陈晓刚,孙可.基于复杂网络理论的大型电力系统脆弱线路辨识[J].电力自动化设备,2006,26(12):1-5. 被引量:218
  • 2李国杰.大数据研究的科学价值[J].中国计算机学会通讯,2012,8(9):8-15.
  • 3赵国栋,易欢欢,糜万军,鄂维南.大数据时代的历史机遇[M].北京:清华大学出版社,2013:前言.
  • 4Gantz J, Reinsel D. Extracting value from chaos [J]. Proceedings oflDCiView, 2011: 1-12.
  • 5GTM Research. The soft grid 2013-2020. Big data & utility analytics for smart grid-research excerpt [R/OL]. GTM, 2013. http-//www.giiresearch.com/reportJ gm257044-soft-grid-big-data-utility-analytics-smart-grid.h tml.
  • 6EPRI. Big data challenges for the grid: EPRI survey results and analysis Data analytics and applications demonstration newsletter[R/OL]. 2013. http://www. smartgridnews.com/artmardpublish/Business_Analytics/Bi g-Data-challenges-for-the-grid-EPRI-survey-results-and-a nalvsis.
  • 7EPRI. The whys, whats, and hows of managing data as an asset[R]. USA: EPRI, 2014.
  • 8IBM. Managing big data for smart grids and smart meters[R/OL]. IBM Software White Paper. http://www. smartgridnews.com/artman/publish/Business_Strategy/ Managing-big-data-for-smart-grids-and-smart-meters-524 8.html.
  • 9Oracle Utilities. Utilities and big data: A seismic shift is beginning[R]. An Oracle Utilities White Paper.
  • 10科技部.国家高技术研究发展计划(863计划)2015年度项目申报指南[EB/OL].http://program.most.gov.cn/htmledit/639A0448.5482.4F63.42C4.95368125A2F8.html.

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