Panoramic risk assessment and self-healing control of big data on smart distribution grid
In this paper,the big data of the DG is divided into initial cluster and the association rules are established based on running states of the DG,and the association rules can achieve extensive clustering division.Based on the current data and according to the extensive clustering division,the running states could be predicted.The panoramic risk assessment and self-healing control strategy of the DG could be achieved with the initial cluster and extensive cluster.It has been pointed out that big data technology shows broad application in the fields of on-line security stability analysis and smart alarming of the DG,the challenges of big data technology in the future for the DG are concluded.
smart distribution gridself-healing controlbig datapanoramic risk assessment
NETL
NSTL
万方数据
维普
