Distributionally Robust Transmission Expansion Planning: a Multi-scale Uncertainty Approach. (arXiv:1810.05212v1 [math.OC])

In this paper, we present a distributionally robust optimization (DRO) approach for the transmission expansion planning (TEP) problem, considering both long- and short-term uncertainties on the system load and renewable generation. Long-term uncertainty is represented on two interrelated levels. At the first level, as is customary in industry applications, the deep uncertainty faced in economic, political, environmental, and technological development is addressed based on plausible visions of long-term future scenarios (trends), traced by current experts beliefs. Subsequently, uncertainty-related parameters defining the probability distributions of the uncertain factors are partially refined for each long-term scenario, thereby inducing an ambiguity set. Finally, for each long-term scenario and induced ambiguity set, the inherent risk model for the short-term uncertainty is described by means of conditional probability distributions. The mathematical problem is formulated as a distribu 查看全文>>