摘要
随着经济社会的发展和用电需求的快速增长,电网规模不断扩大,随之带来了运行特性多变、易出风险等问题,尤其对依赖运行经验较大的电网停电计划编排工作产生了较大影响,使缺乏经验的新人在面对各电压等级不同设备的多种停电方案时措手不及。基于上述问题,采用关联规则挖掘算法及离散段间隙加权法进行停电计划编制专家库中同停规则及窗口期规则的自学习,并将学习结果作为专家库的补充规则。经过某省电力公司的实际系统运行测试,证明该自学习专家库具有实用效应,提高了设备停电检修计划制定的合理性和检修计划制定人员的工作效率,使停电计划编排系统更加智能可靠,为电网安全稳定运行提供了有效的保障。
With the development of economy society and the rapid growth of electricity demand,the power grid is expanding.Then it brings many problems such as variable operation characteristics and risks,eapecially having a great influence on the power cut scheme scheduling of power grids which largely rely on operational experience,so inexperienced new staff are unprepared in the face of various power cut schemes of devices with different voltage levels.Based on the above problems,this paper adopts the association rule mining algorithm and the discrete gap weighting method to conduct the self-learning of the same stop rule and window period rule in the expert database of power cut scheme scheduling,and takes the learning result as the supplementary rule of the expert database.After the actual system operation test in a provincial electric power company,it has proved that the self learning expert database has practical effect to enhance the rationality of the equipment power outage maintenance planning and the work efficiency of maintenance planners,make the power cut scheme scheduling system more intelligent and reliable,and provide an effective guarantee for the safe and stable operation of the power grid.
作者
杨帆
高强
林烨
YANG Fan;GAO Qiang;LIN Ye(State Grid Taizhou Power Supply Company,Taizhou 318000,China)
出处
《电工技术》
2019年第1期45-48,52,共5页
Electric Engineering
关键词
停电计划
自学习
专家库
关联规则挖掘
power cut scheme
self-learning
expert database
association rule mining
