Deep decoupling and data collaboration method for power monitoring data

The invention discloses a deep decoupling and data collaboration method for power monitoring data, and belongs to the technical field of power monitoring. According to the invention, a storm architecture and a Python language are used as power monitoring data mining tools, various technical modules with different functions are designed, and all parts of module systems are integrated to construct aset of detailed data monitoring process system, so that deep mining of power monitoring data is completed by data through a series of modules. And finally, deep decoupling and data collaboration of the power monitoring data are realized. According to the invention, the data quality is improved, and the reliability, accuracy, timeliness and effectiveness of the data are ensured, so that the comprehensive quality management of the power supply enterprise data is realized, and the integration and mining application of the data are ensured. 本发明公开了一种电力监测数据的深度解耦与数据协同方法，属于电力监测技术领域。本发明采用storm架构和Python语言作为电力监测数据挖掘工具，设计各类拥有不同作