The mismatch risk and operational cost of off-line stability control strategy and setting values will increase dramatically with high proportion new energy generation which impose uncertainty on power system operation. Given that the fast adaptive online configuration of control strategy cannot replace the off-line strategy formulation procedure in practice for the moment, reforming the off-line stability control strategy configuration by a normative and automatic procedure is inevitable. A normative setting approach of power system off-line stability control strategy based on stochastic-robust mixed integer programming is proposed. The uncertain parameters are divided into two categories according to whether their probability distribution can be credibly provided, and incorporated by stochastic and robust programming respectively; the setting problem is normalized as a dual-branch bi-level stochastic-robust optimization. The proposed approach is demonstrated on a real stability control strategy of China Southern Power Grid, and its efficiency to support daily update is verified. This proposed approach provides a general normalization and automation technical framework for the security-sensitive and simulation-based off-line decision problems in an uncertain operational environment.