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为了保证配电网台区能够健康运行,设计基于数字孪生的配电网台区的健康检测系统。数字孪生的可视化技术需要从几何、物理、行为、规则等多个维度对物理平台进行全方位的建模,利用理论解析模型或拟合解析模型对模型的参数进行修正,基于JavaScript的Three.js和Echarts实现现场数据可视化。实验结果表明,健康检测系统能够检测到台区用电数据和潮流分布式数据中异常数据个数均高于200个,统计到的台区用电数据合格率最高可达到100%。
Abstract:In order to ensure the healthy operation of distribution network station area, a health detection system of distribution network station area is established based on digital twin. Visualization technology of digital twin requires comprehensive modeling of physical platform from multiple dimensions such as geometry, physics, behavior and rules, and uses theoretical analytical model or fitting analytical model to correct model parameters. Three.js and Echarts based on JavaScript realize field data visualization. The experimental results show that the health detection system can detect more than 200 abnormal data in the power consumption data of the station area and the power flow distribution data, and the qualified rate of the power consumption data of the station area can reach 100%.
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基本信息:
中图分类号:TM73
引用信息:
[1]陈若飞,周建.数字孪生助力台区健康循环复诊的研究与应用[J].微型电脑应用,2023,39(04):48-51.
基金信息:
国网吉林省电力有限公司科技项目资助(SGJLCC00KJJS2001830)
2023-04-20
2023-04-20