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作 者:段雄英[1] 肖臣臣 赵洋洋 刘洪正 井雨刚 李宽 DUAN Xiongying;XIAO Chenchen;ZHAO Yangyang;LIU Hongzheng;JING Yugang;LI Kuan(College of Electrical Engineering,Dalian University of Technology,Liaoning Dalian 116024,China;State Grid Shandong Electric Power Research Institute,Jinan 250000,China)
机构地区:[1]大连理工大学电气工程学院,辽宁大连116024 [2]国网山东省电力公司电力科学研究院,济南250000
出 处:《高压电器》2020年第7期56-62,共7页High Voltage Apparatus
基 金:国家电网公司总部科技项目(SGTYHT/17-JS-201)。
摘 要:特高压断路器的操动时间具有较大的分散性,影响因素众多不利于断路器选相的实现,大数据技术在数据处理上具有高效性。文中对碟簧液压操动机构原理进行分析,收集大量的1100 kV小型GIS断路器实验数据,采用Hadoop软件,设计并搭建了含有数据采集、数据分析和数据处理3大功能的离线分布式处理平台,在平台上通过eclipse进行编程实现了多元线性分析,获得了通过控制电压和油压等影响因素预测断路器动作时间的数学模型。进一步对模型进行优化,结果表明:平台具有高效性、高可靠性,可以通过初始影响因素有效预测断路器的动作时间。从预测结果分析来看,优化后的模型与优化前误差率明显降低,优化后对应的误差范围在±0.8 ms以内,验证了模型的有效性。该研究为电网大数据分析和输变电设备稳定运行提供一定的参考价值。The actuation time of UHV circuit breakers has a great dispersion,many influencing factors are not conducive to the realization of circuit breaker phase selection and big data technology has high efficiency in data processing.The principle of the disc spring hydraulic operating mechanisms is analyzed and a lot of experimental data about the 1100 kV miniature GIS circuit breaker are collected.The offline distributed processing platform containing three major functions of data acquisition,data analysis and data processing is designed and built by Hadoop software.By using eclipse to program on the platform,the multivariate linear analysis method is realized and the forecasting actuation time of breaker mathematical model based on control voltage and oil pressure is obtained and the model is further optimized.It is shown that the action time of breaker can be effectively predicted by initial influencing factors under the condition of high efficiency and high reliability of the platform.From the analysis of the prediction results,the error rate in the optimized model is significantly reduced than the previous one and the corresponding error range within±0.8 ms,which verifies the effectiveness of the model.This paper provides some reference value for the grid big data analysis and the stable operation of power transmission and transformation equipment.
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