CAJ | 학술논문

电能质量监测具有采集数据量大、采集频率高等特点，长期监测将形成电能质量大数据，而常规数据存储、处理方式很难有效利用大数据，发掘大数据的价值。设计并实现电能质量大数据存储分析原型系统，系统基于开源大数据处理技术Hadoop和HBase构建为支持高效存储和分析海量数据的云平台。系统依据电能质量监测数据特点，将数据按监测点集中存储和列簇组合存储，提高数据检索效率。系统设计基于 MapReduce 并行框架的电能质量数据统计和评估算法，实现对电能质量的分析评估。通过原型系统的应用，证明该云平台可存储和分析电能质量大数据。
전능질량감측구유채집수거량대、채집빈솔고등특점，장기감측장형성전능질량대수거，이상규수거존저、처리방식흔난유효이용대수거，발굴대수거적개치。설계병실현전능질량대수거존저분석원형계통，계통기우개원대수거처리기술Hadoop화HBase구건위지지고효존저화분석해량수거적운평태。계통의거전능질량감측수거특점，장수거안감측점집중존저화렬족조합존저，제고수거검색효솔。계통설계기우 MapReduce 병행광가적전능질량수거통계화평고산법，실현대전능질량적분석평고。통과원형계통적응용，증명해운평태가존저화분석전능질량대수거。
Power quality monitoring has the features of large amount of data gathering and high frequency of data collection. Long-term monitoring will form power quality big data, and conventional data storage and processing method is difficult to effectively use big data to discover the value of power quality data. In this paper, a prototype system of power quality big data storage and analysis is designed and implemented. Based on open source Hadoop and HBase big data processing technology, the system builds one cloud platform for supporting efficient storage and massive data analysis. Based on the characteristics of the power quality monitoring data, centralized storage and column family combination storage of data are conducted according to monitoring points to improve the efficiency of data retrieval. MapReduce based parallel processing algorithms for analysis and evaluation of power quality big data are designed. Through the application of the prototype system, it is proved that the cloud platform can store and analyze power quality big data effectively.