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