The rapid accumulation of big data in the power grid dispatching and control system provides a sufficient condition for the risk analysis of power grid equipment. Based on the analysis of characteristics of big data in the dispatching and control system

a universal analysis framework of big data in power dispatching and control system is built

and on basis of the application of risk management and control in power grid

a data mining method for high risk equipment based on high risk tree(HRT)is proposed. From the perspective of multiple factor analysis of equipment risk

considering impact of equipment importance and equipment hidden danger on equipment risk

equipment risk influence degree is defined

equipment importance indicators and equipment hidden danger indicators are proposed. The equipment risk value as the target of mining high risk equipment

the construction of HRT retaining the original database of equipment risk value and equipment risk prior knowledge information is for mining high risk equipment set

specifically the high risk equipment risk set meeting the threshold will be obtained according to the HRT path information. Finally

the proposed method is simulated based on massive historical alarm data in dispatching and control system. The simulation results show that HRT can quickly deal with the alarm data to get high risk equipment set meeting the conditions

and it can reflect the potential association between high risk equipment

so it will provide reference for the follow-up of power grid risk management and control.