A Data-Driven Method for Risk Assessment of Loop Closing Operation with Uncertain Load

In order to ensure the reliability of power consumption, the loop closing operation is usually used for load transfer without power cut. It is necessary to accurately predict the loop closing current. However, there exists uncertainties as the load date of distribution network cannot be obtained instantaneously. Stochastic power flow method can make a risk assessment of the power grid with uncertainties, but systematic analysis of the current's cumulative probability distribution in stochastic power flow is rarely reported. In this paper, a new method of stochastic power flow calculation based on correlation sampling is proposed. The load data samples are built by sampling on relevant days method. At the same time, the calculation process of stochastic power flow with branch currents as random variables is derived in detail. Finally, the application of the algorithm is introduced and the validity of the algorithm is verified by a real closing loop operation.