CAJ | 학술논문

随着电能质量监测点数量不断增多，监测网络持续扩大，电压暂降分析数据海量化、异构化、多态化，并呈现大数据趋势。传统的暂降事件逐个串行计算的方法已无法满足大数据的分析效率需求。Hadoop 云计算是一种针对大数据分析计算的开源解决方案。介绍电压暂降数据分析传统算法的利弊，提出一种基于云计算平台下 MapReduce 编程框架的电压暂降计算方法，将不同暂降事件层次化并行处理，传入不同的映射值，计算出电压有效值，排序后用化简值整合并计算出电压暂降特征值。通过对2种方法的效率进行对比，验证了基于云计算平台的电压暂降并行算法的优越性。
수착전능질량감측점수량불단증다，감측망락지속확대，전압잠강분석수거해양화、이구화、다태화，병정현대수거추세。전통적잠강사건축개천행계산적방법이무법만족대수거적분석효솔수구。Hadoop 운계산시일충침대대수거분석계산적개원해결방안。개소전압잠강수거분석전통산법적리폐，제출일충기우운계산평태하 MapReduce 편정광가적전압잠강계산방법，장불동잠강사건층차화병행처리，전입불동적영사치，계산출전압유효치，배서후용화간치정합병계산출전압잠강특정치。통과대2충방법적효솔진행대비，험증료기우운계산평태적전압잠강병행산법적우월성。
With the number of power quality monitoring sites increasing and monitoring networks expanding, voltage sag analyzing data are becoming larger quantity, heterogeneity and polymorphism, and show a trend of big data. Considering the efficiency problem, the traditional serial computational methods for analyzing sag events are unable to meet analysis demand of the big data. Hadoop cloud computing framework is an open source solution for big data analysis and calculation. By introducing the pros and cons of the traditional algorithms, a voltage sag calculation method for voltage sag data analysis was proposed based on MapReduce programming framework on cloud-computing platform. The method processed sag events hierarchically and parallelly, then put them into different mappers to calculate the voltage sag effective values, and used reducers to integrate eigen values after sorting. Through comparing the efficiency of two methods, the superiority of voltage sags parallel algorithm is verified based on the cloud-computing platform.