摘要
针对智能电网控制系统内部通信协议杂糅导致的处理速度慢、处理数据时无法很好地检测出错误数据等问题,提出一种基于动态贝叶斯网络的监控与数据采集系统故障监测及诊断方法。该方法使用云平台处理和保存即时的数据,减轻各个站点因处理数据而产生的不必要开销,并使用贝叶斯网络模型来更快速更高效地进行错误数据的监测。在层与层之间使用通信协议快速高效地传输数据,以提高广域控制能力。试验结果显示,监控与数据采集系统相对于其他检测错误数据的系统灵敏度有了10%~20%的提高,故障识别准确率可达95%,提高了智能电网测试平台检测和识别能力。
A fault monitoring and diagnosis method for monitoring and data acquisition systems based on dynamic Bayesian networks was proposed to address the issues of slow processing speed and inability to detect erroneous data during data processing caused by the hybridization of internal communication protocols in smart grid control systems.The method used a cloud platform to process and save real-time data,reducing unnecessary costs incurred by various sites due to data processing,and utilized Bayesian network models to monitor erroneous data more quickly and efficiently.The communication protocols between layers were employed to quickly and efficiently transmit data to improve wide area control capabilities.The experimental results show that the monitoring and data acquisition system has improved its sensitivity by 10%to 20%compared to other systems that detect erroneous data,and the fault recognition accuracy can reach 95%,thus improving the detection and recognition capabilities of the smart grid testing platform.
作者
孙玉玲
纪林
史名册
韩博
鲍心竹
Sun Yuling;Ji Lin;Shi Mingce;Han Bo;Bao Xinzhu(Marketing Service Center,State Grid Liaoning Electric Power Co.,Ltd.,Shenyang Liaoning 110000,China)
出处
《电气自动化》
2024年第3期87-89,共3页
Electrical Automation
关键词
监控与数据采集系统
通信协议技术
贝叶斯网络
故障检测
远程终端控制
智能电网测试平台
monitoring and data acquisition system
communication protocol technology
Bayesian network
fault detection
remote terminal control
smart grid test platform
