Abstract: With the improvement of intermittent renewable energy penetration and the development of advanced information technology, research begins to focus on how to manage responsive loads to optimize resources and assets. Demand response can change the consumer consumption mode and balance the supply and demand of the power grid. On the premise that microgrid operators can meet users' power demand through local generators and demand response, this paper proposes a new two-stage stochastic programming model considering a risk management strategy. Business risk aversion is modeled by the conditional value at risk method. Microgrid operators sell electricity to users according to real-time price schemes, and users respond to electricity prices by adjusting loads to reduce costs. Considering risk aversion and system frequency security, the proposed scheduling model maximizes the expected profits of operators. The effectiveness of the proposed model is demonstrated by the results of case studies.