System operators usually simplify the dynamic stability constraints into tractable but over-conservative static power transfer limits

curtailing renewable energy export and consumption. To address this

an unsupervised condition mapping rule generation and multi-banding switching method for multiple inter-corridors' coupling power transfer limits is proposed. Firstly

the K-means++ is employed to identify various operating patterns of renewable energy. The proof of sample size required for stable clustering is also completed. For each operating pattern

correlation coefficients are used to identify coupled inter-corridor pairs. A grid partitioning algorithm is proposed to build power transfer limits of coupled inter-corridors

thus generating a conditional mapping from operating patterns to coupling transfer limits. A model to match operating patterns and coupling transfer limits is then constructed via distance criteria and the Big-M method. Upon this

penalty functions and Lagrange multipliers are proposed for limit switching to maximize renewable energy export. Case studies on the IEEE 39-bus system and a realistic system show that

compared to traditional methods

the proposed method increases average consumption of renewable energy while reduces operational costs

under the premise of strictly satisfying the pre-fault stability verfications.