Distributed Renewable Energy (DRE) is connected to the power grid on a large scale in the form of a microgrid, and the stable operation of the power grid faces challenges. There is uncertainty on the renewable energy output in the microgrid and excessively large flexible load adjustments in the regulation process may reduce user satisfaction. Thus a day-ahead optimal scheduling model considering the uncertainty of DRE output and user satisfaction is established. First, the theory of Conditional Value at Risk (CVaR) is used to quantify the uncertainty risk of the microgrid and improve the stability of the system, and the uncertainty is converted into risk costs. Secondly, the degree of difference between the new and old load curves before and after optimization is used as an index to judge user satisfaction, while the economic operation of the microgrid is satisfied and the user’s sense of power consumption is also improved. The objective function of the optimal scheduling model is to minimize the overall operating cost and maximize user satisfaction. Finally, the NSGA-II algorithm generated by improved crossover operator coefficients is used, and the optimization results under different confidence levels and three schemes are analyzed through simulation, thereby verifying the effectiveness of the proposed model. This work is supported by the National Natural Science Foundation of China (No. 61672337).