Abstract: Accurate price forecasting is helpful to the implementation of macro-control. However,the transformation of energy structure leads to large-scale renewable energy integration,causing the reduction and fluctuation of electricity price,reducing the sequence correlation of time series forecasting,and increasing the difficulty of real-time electricity price forecasting. To solve this problem,this paper uses autocorrelation function and the maximum number of information to calculate the electricity price itself and the correlation between the electricity price and electricity quantity,and provides basis for model input. On this basis,deep echo state network with deep reserve pool characteristics is used for the real-time electricity price forecasting. The results show that: there is a strong correlation between the electricity price and the electricity quantity and electricity price itself,which should be taken into account;The deep echo state network can significantly improve the accuracy of forecasting model and has strong robustness.