Probabilistic assessment improves transmission reliability margin, indicating enhanced renewable generation integration for electricity trading.
With the rapid transition toward a low-carbon power system, the temporal intermittency and spatial unevenness of renewable generation have imposed emerging challenges to the supply–demand balance of electricity. To enhance the secure utilization of inter-regional transmission capacity under uncertainties, this paper proposes a correlation-aware Gaussian mixture model (GMM) for probabilistic assessment of the transmission reliability margin (TRM) of interconnectors. The proposed method explicitly captures multi-source uncertainties, including renewable generation, load, and power contract execution deviation. The internal correlations among uncertain factors are embedded in the GMM to avoid the misestimation associated with independent-distribution assumptions. Simulation results on a four-region system demonstrate that the proposed method outperforms existing methods in higher accuracy and computational efficiency, which enables reliable and economic cross-regional power trading under uncertainty.
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Lu et al. (2025) studied this question.
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