Abstract: To address the insufficient flexibility in peak regulation and ramping of power systems under high renewable energy penetration, a novel energy storage optimization configuration method based on probabilistic flexibility assessment is proposed. First, an effective peak regulation and ramping capacity probability distribution model considering forced outages of conventional units is constructed, combined with kernel density estimation, Frank-Copula function, and seasonal autoregressive moving average models to generate source-load uncertainty scenarios. Second, flexibility shortage probability and expectation metrics are introduced, establishing a bi-level energy storage siting and sizing optimization model incorporating state-of-charge constraints. IEEE 39-bus system case studies demonstrate that after energy storage integration, the mean probability of insufficient system flexibility drops from 0.303 to 0.126 (a 58.4% reduction), while the mean expected shortage decreases from 424 MW to 230 MW (a 45.8% reduction). The proposed method effectively identifies system flexibility weak links and enhances the matching capability between flexibility supply and demand.