摘要
针对电网GIS数据量大,导致数据调度结果不理想、调度响应时间过长的问题,提出了基于人工智能的海量电网GIS数据动态调度方法。压缩海量电网GIS数据,使用人工智能调度的神经网络方法,构建误差修补函数,修改神经网络权值,生成人工智能调度模型。在R树数据结构下对所有数据进行缓存,改变当前视野范围,并将查询到的压缩数据以格式字符串形式返回给客户端。结合人工智能调度的数据动态渲染方法,实现了基础地理和电网设备符号的实时绘制,缩短了数据动态调度响应时间,由此完成数据动态调度。实验结果表明,所提方法与实际数据存在最大为10 kB的误差,且调度响应时间为100 s,具有较好的调度效果,能够有效缩短调度响应时间。
In view of the large amount of GIS data in power grid,which leads to unsatisfactory data scheduling results and long scheduling response time,a dynamic scheduling method of massive GIS data in power grid based on artificial intelligence is proposed.Compress the massive GIS data of power grid,use the neural network method of artificial intelligence dispatching,build the error repair function,modify the neural network weights,and generate the artificial intelligence dispatching model.Cache all data under the R-tree data structure,change the current field of view,and return the queried compressed data to the client in the form of format string.Combined with the data dynamic rendering method of artificial intelligence scheduling,the real-time rendering of basic geography and power grid equipment symbols is realized,and shortening the response time of data dynamic scheduling,thereby completing data dynamic scheduling.The experimental results show that the maximum error between the proposed method and the actual data is 10 kB,and the scheduling response time is 100 s,which has a good scheduling effect and can effectively shorten the scheduling response time.
作者
买合布拜·肖开提
薛高倩
雪拉提·司马义
吕娜
MAIHEBUBAI Xiaokaiti;XUE Gaoqian;XUELATI Simayi;LV Na(Information and Communication Company,State Grid Xinjiang Electric Power Co.,Ltd.,Urumqi 830002,China)
出处
《电子设计工程》
2024年第5期146-149,155,共5页
Electronic Design Engineering
关键词
人工智能
电网GIS数据
动态调度
神经网络
artificial intelligence
power grid GIS data
dynamic scheduling
neural network
