基于大数据与聚类算法的电网信息化数据整合研究  

Research on Power Grid Informatization Data Integration Based on Big Data and Clustering Algorithms

作　　者：宋超 刘剑磊 王志乾 张志鑫 SONG Chao;LIU Jianlei;WANG Zhiqian;ZHANG Zhixin(Gansu Tongxing Intelligent Technology Development Co.,Ltd.,Lanzhou Gansu 730050,China)

机构地区：[1]甘肃同兴智能科技发展有限责任公司,甘肃兰州730050

出　　处：《信息与电脑》2024年第20期181-184,共4页Information & Computer

摘　　要：传统的数据处理和分析方法已难以满足海量、复杂且实时的电力数据处理需求,亟需引入更为先进的技术手段,因此提出了基于大数据与聚类算法的电网信息化数据整合方案。首先,通过大数据与聚类算法检测并修正异常值,提高数据质量和聚类准确性;接着,引入数据挖掘技术,设计适应度函数,以优化数据匹配;最后,对电网信息化数据进行有序排列,实现智能整合。实验结果表明,该方法使电网总出力测试结果与设定目标趋于一致,比其他方法误差更小。Traditional data processing and analysis methods are no longer sufficient to meet the demands of massive,complex,and real-time power data processing,and there is an urgent need to introduce more advanced technological means.Therefore,a power grid information data integration based on big data and clustering algorithms is proposed.Firstly,detect and correct outliers through big data and clustering algorithms to improve data quality and clustering accuracy.Next,data mining techniques are introduced to design a fitness function to optimize data matching.Finally,arrange the information data of the power grid in an orderly manner to achieve intelligent integration.The experimental results show that this method makes the total output test results of the power grid consistent with the set target,and has smaller errors compared to other methods.

关 键 词：大数据 聚类算法 电网 数据整合 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]