In power systems with a high proportion of renewable energy, to achieve coordinated optimal scheduling of source and load considering multiple uncertainties is an important issue in power system operation. Therefore, a probabilistic spinning reserve optimization model based on multiple scenarios is constructed. Multiple uncertain factors are considered in the model, such as wind power and solar power forecast errors, load forecast error and unscheduled generator outage. Renewable energy curtailment and load shedding are used as special reserve resources in the day-ahead security-constrained unit commitment (SCUC) to improve the economic operation efficiency. The calculations of reliability indexes, expected energy not served and expected energy curtailment, are simplified, and the inequality constraints related to these two indexes are reduced, which improves the computational performance of the model. The model optimizes the total expected cost considering multiple uncertainties. Case studies based on the IEEE-RTS demonstrate the effectiveness of the proposed model. The numerical results show that the improved calculation method of reliability indexes can effectively reduce the solution time of the SCUC model. The reserve optimization model can realize the dynamic allocation of the spinning reserve capacity of the system and improve economic operation of the system.