配网馈线自动化仿真培训测试系统的环境搭建设计思路

Design Idea of Environment Construction for Simulation Training and Testing System of Distribution Network Feeder Automation

随着我国智能配电网的快速发展,新型设备及先进技术不断在配电网应用,配电网设备、配电自动化系统也在加速更新换代,未来智能配电网技术体系和运营方式将发生重大变革,对配电网生产人员的专业技能提出更高的要求。目前,配电网生产人员的专业技能水平远远无法满足未来配电网发展的需求,因此,需要面向配电网生产人员开展高效、实用的培训。需要开发建设高效、专业的配电网生产仿真培训系统,满足相关人员的学习、培训、训练、考核、鉴定等需求,提高配电自动化运行和维护水平,从而切实提高配电自动化的实用程度。结合项目经验,重点介绍了配网馈线自动化仿真培训测试系统搭建的整体系统框架、典型网架结构设计、测试场景监管监控这3个方面的设计思路,以期对配网馈线自动化的仿真培训以及试验验证提供环境支持。

With the rapid development of China's smart distribution grid,new equipment and advanced technologies are constantly being applied in the distribution grid,and the equipment and distribution automation system of the distribution grid are also accelerating their upgrading.In the future,the technical system and operation mode of the smart distribution grid will undergo major changes,and higher professional skills are required for the production personnel of the distribution grid.At present the professional skill level of the production personnel of the distribution grid is far from meeting the needs of the future development of the distribution grid,therefore,efficient and practical training for the production personnel of the distribution grid is needed.It is necessary to develop and construct an efficient and professional simulation training system for the production of the distribution grid,to meet the needs of relevant personnel for learning,training,training,assessment and identification,and to improve the level of operation and maintenance of distribution automation,so as to effectively improve the practicality of distribution automation.Combined with the project experience,this paper focuses on the overall system framework of the distribution network feeder automation simulation training and testing system,the design of the typical network structure design and test scenarios supervision and monitoring of the three aspects of the design ideas,in order to provide environmental support for the simulation training of the distribution network feeder automation as well as the experimental validation.