Interprovincial electricity spot trading of surplus renewable energy is an important way to overcome the inverse distribution of energy supply and demand in China and promote the consumption of renewable energy. In the existing researches

the surplus power prediction is calculated based on the renewable power prediction

and the prediction results are not very sensitive. Conventional optimization methods are difficult to deal with the high risks of low acuity to spot transactions. This paper applies conditional value-at-risk（CVaR） theory to quantify transaction risk

and proposes an automatic adjustment method of risk coefficients to achieve risk control

so as to find the optimal surplus power interprovincial transaction plan. Then

to get the minimum incremental network loss caused by the transactions

the optimization and decomposition model of the surplus power in the area is established

and the transaction plan is implemented to the power producers in the sending area. Finally

a case was studied by using historical data from a certain area to verify the effectiveness of the method. The results show that the proposed method can be adopted to effectively control the transaction risk and improve the economic benefits while ensuring the security of the power grid.