电力调度SCADA系统中历史数据压缩及存储策略

The Research of Historical Data Compression and Storage Strategy in Power Dispatch SCADA System

为降低电力调度SCADA系统历史数据量、提高历史数据存储效率,提出一种基于有效估算的旋转门算法(effective reckon swing door trending,ERSDT),并针对压缩的历史数据给出了一种新的数据多级存储策略。ERSDT通过搜寻最远压缩点以及旋转平衡因子方式进行数据压缩。针对压缩数据给出实时数据库、历史数据库、磁盘文件库三级存储体系,并描述了三级存储体系的运行原理。实验数据验证了ERSDT算法的可行性,与传统的SDT算法相比提高了压缩率、降低了压缩时间。实践证明ERSDT算法以及多级数据存储策略可以降低历史数据量、提高数据存储及查询效率,从而保证SCADA系统安全、稳定的运行。

In order to reduce the amount of historical data of SCADA system and improve storage efficiency, in this paper, effective reckon swing door trending （ERSDT） which is an algorithm improved from swing door trending （SDT） algorithm and a storage policy of three-level architecture are proposed. ERSDT compress data by searching the farthest compression point and rotating balance factor. Three-level architecture which includes real-time database, historical database and disk storage database is presented to store the compressing data. The result of test verifies the feasibility of ERSDT. Comparing with traditional SDT, ERSDT can improve the compression ratio and reduce the compression time. Practice has proved that ERSDT algorithms and three-level data storage strategy can reduce the amount of historical data, and improve the efficiency of data storage and query.