The great proliferation of wind power generation has brought about great challenges to\npower system operations. To mitigate the ramifications of wind power uncertainty on operational\nreliability, predictive scheduling of generation and transmission resources is required in the day-ahead\nand real-time markets. In this regard, this paper presents a risk-averse stochastic unit commitment\nmodel that incorporates transmission reserves to flexibly manage uncertainty-induced congestion.\nIn this two-settlement market framework, the key statistical features of line flows are extracted\nusing a high-dimensional probabilistic collocation method in the real-time dispatch, for which\nthe spatial correlation between wind farms is also considered. These features are then used to\nquantify transmission reserve requirements in the transmission constraints at the day-ahead stage.\nComparative studies on the IEEE 57-bus system demonstrate that the proposed method outperforms\nthe conventional unit commitment (UC) to enhance the system reliability with wind power integration\nwhile leading to more cost-effective operations.
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