Two-stage Stochastic Optimization Clearing Model of Day-ahead Energy Market Considering Renewable Energy

The day-ahead energy market has enabled full competition in the electricity market and efficient optimization of power resources, revealing the price signals from both the supply and demand sides. The uncertainty of renewable power output, coupled with its large-scale grid integration, poses challenges to the operation of the day-ahead market and the reliable consumption of renewable energy. Designing a reasonable dayahead market mechanism to promote the consumption of renewable energy has become an urgent issue. Based on the twostage stochastic optimization method, this paper establishes a dayahead energy market clearing model that accounts for the uncertainty of renewable energy. In the first stage, the securityconstrained unit commitment (SCUC) model is constructed to determine the unit start-up and shut-down status. In the second stage, the stochastic multi-scenario method is utilized to describe the uncertainty of renewable power, followed by the securityconstrained economic dispatch (SCED) model and locational marginal price (LMP) model, which are formulated to clear the generation output schedules and market price. The case studies based on the modified IEEE-RTS79 have verified the effectiveness of the proposed model and method.