An Adaptive Data Management Model for Smart Grid

Abstract

Application of big data techniques in power system will contribute to the sustainable development of power industry companies and the establishment of strong smart grid. There are significant challenges for big data analytics because of heterogeneous data and scalability, system complexity, reliability, and real time requirements for smart grid. In this paper, a data management model is proposed based on knowledge cube, which is an intelligent and adaptive database. The knowledge cube is established based on Topical, Association, Spatial and Temporal. The proposed data management model could handle data that is only relevant to its semantics. And the cube could be combined adaptively with the necessary information about other relevant knowledge cubes by the association component. The proposed knowledge cubes can support the capture and tracking of dynamic data. The proposed model provides a powerful and extensible framework that is particularly well suited to analyzing big variety data in smart grid.