A risk assessment method based on multi-stage overloading in smart distribution network

The risk assessment for power system is becoming an important and mandatory task in planning and operation. The traditional risk assessment determines whether the system is secure or not in the present state and lack of identifying the risk level. This paper presents a multi-stage overloading identification method for risk assessment in smart distribution network with historical, real-time and forecasting load data, the risk level is classified according to the overload risk identification rules based on the overload severity. The method is applied to a real-site circuit and the simulation result shows that the proposed method is able to effectively identify location of the risk and the risk level of alert region, which will be used to achieve the risk assessment of active defense in the self-healing process in smart distribution network.