The fluctuation and intermittency of the wind and solar power outputs results in the regulation pressure of thermal units in power systems. The adjustable energy-intensive loads (such as the Electrolytic aluminium and Steel plants) have great potentialities to participate in demand response (DR) programs. This paper proposes an optimal scheduling method of the unit commitment (UC) with the consideration of the energy-intensive loads participating in wind and solar power consumption. It adopts the nonparametric kernel density estimation method to model the wind and solar power outputs. And then it uses Frank-Copula function to describe the correlation between the scenarios of wind and solar power outputs. A stochastic unit commitment (SUC) model introduces chance constrained theory of the reserve coefficient to describe time-variant scenarios, on the basis of the deviation between the typical and simulative scenarios. The simulation results based on IEEE 118-bus system shows that the energy-intensive load in the SUC model can flexibly adjust and respond to the change of wind and solar power output, reduce the impact of wind and solar power output’s uncertainty and promote the consumption of wind and solar power.