海量多元异构智能电网数据未经处理就进行压缩与存储，存在压缩误差大、运行时间长的问题，影响压缩储存效果。因此，提出基于状态估计的海量多元异构智能电网数据压缩存储方法。融合海量多元异构智能电网数据，推导出准确的智能电网数据，通过Tucker分解智能电网大数据压缩方法，压缩海量多元异构智能电网数据。采用可扩展标记语言（XML）技术预处理数据，结合非关系型的数据库技术，实现海量多元异构智能电网数据的快速存储。试验结果表明，该方法的线路电阻、电抗动态参数估计准确性高，数据压缩平均绝对误差、F范数误差低，运行时间短，具有一定的实际应用性能。

Massive multivariate heterogeneous smart grid data are compressed and stored without processing, which has the problems of large compression error and long running time, affecting the compression and storage effect. Therefore, a data compression and storage method of massive multivariate heterogeneous smart grid based on state estimation is proposed. The massive multivariate heterogeneous smart grid data are integrated to deduce the accurate smart grid data. And the massive multivariate heterogeneous smart grid data are compressed through the Tucker decomposition smart grid big data compression method. Extensible markup language (XML) technology is used to preprocess the data, and combined with the nonrelational database technology to realize the rapid storage of massive multivariate heterogeneous smart grid data. The experimental results show that this method has high accuracy in estimating the dynamic parameters of line resistance and reactance, low average absolute error and Fnorm error of data compression, short running time and certain practical application performance.