引用本文:高磊,闫培丽,阮思烨,许志勇,李鹏,顾俊捷.基于相似度计算的学习型模板库在虚回路设计和校验中的应用[J].电力自动化设备,2017,37(7):
GAO Lei,YAN Peili,RUAN Siye,XU Zhiyong,LI Peng,GU Junjie.Application of similarity-calculation-based learning template library in design and check of virtual circuit[J].Electric Power Automation Equipment,2017,37(7):
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基于相似度计算的学习型模板库在虚回路设计和校验中的应用
高磊1, 闫培丽2, 阮思烨3, 许志勇4, 李鹏5, 顾俊捷5
1.国网江苏省电力公司电力科学研究院,江苏 南京 210036;2.国网北京经济技术研究院,北京 102209;3.华北电力设计院有限公司,北京 100120;4.国网江苏省电力公司,江苏 南京 210024;5.南京五采智电电力科技有限公司,江苏 南京 211106
摘要:
智能变电站二次回路设计基本相通,由于虚端子描述尚不统一,使得新建站虚端子连接无法复用,仍采用人工点对点连接,导致效率不高。提出自动创建虚回路模板库,通过关键字匹配实现虚回路的自动设计和完整性及正确性校验,其核心在于学习型模板库海量学习已有配置描述(SCD)文件,采用中文分词技术进行关键字提取,引入经典的RKR-GST算法完成虚端子描述的相似度计算,从而进行关键字的匹配整合,从而创建、整理和完善虚回路模板库。试验证明,通过该方法对新建智能变电站的虚端子连接效率和准确性都有较大提升。
关键词:  智能变电站  配置描述文件  相似度  学习型模板库  虚回路  设计  校验
DOI:10.16081/j.issn.1006-6047.2017.07.031
分类号:TM761
基金项目:国家电网公司科技项目(新一代智能变电站二次系统虚回路自动连接与扩建回路自动重构技术研究)
Application of similarity-calculation-based learning template library in design and check of virtual circuit
GAO Lei1, YAN Peili2, RUAN Siye3, XU Zhiyong4, LI Peng5, GU Junjie5
1.State Grid Jiangsu Electric Power Company Research Institute, Nanjing 210036, China;2.State Grid State Power Economic Research Institue, Beijing 102209, China;3.North China Electric Design Institute Limited Company, Beijing 100120, China;4.State Grid Jiangsu Electric Power Company, Nanjing 210024, China;5.Nanjing Five-C Smart Power Grid Technology Co. Ltd.,Nanjing 211106, China
Abstract:
Though the design principle of smart substation secondary circuits is basically same, because the virtual terminal description has not been unified, the virtual terminal connection of new substation is still manually implemented with low efficiency. A method is proposed to automatically create the virtual circuit template library for realizing the automatic design and the integrity and correctness check of virtual circuits based on the keyword matching. Massive SCDs(Substation Configuration Descriptions) stored in the learning template library are explored, the Chinese word segmentation technology is applied to extract the keywords and the classic RKR-GST algorithm is introduced to calculate the similarity of virtual terminal descriptions for the matching and integration of keywords as well as the creation, organization and improvement of the virtual circuit template library. Experiments show that, with the proposed method, the efficiency and accuracy of virtual terminal connection for new smart substation are greatly improved.
Key words:  smart substation  substation configuration description  similarity  learning template library  virtual circuit  design  check

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