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- W2150829038 abstract "The increasing penetration of renewable generation in power systems necessitates the modeling of this stochastic system infeed in operation and planning studies. The system analysis leads to multivariate uncertainty analysis problems, involving non-Normal correlated random variables. In this context, the modeling of stochastic dependence is paramount for obtaining accurate results; it corresponds to the concurrent behavior of the random variables, having a major impact to the aggregate uncertainty (in problems where the random variables correspond to spatially spread stochastic infeeds) or their evolution in time (in problems where the random variables correspond to infeeds over specific time-periods)." @default.
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- W2150829038 date "2009-07-01" @default.
- W2150829038 modified "2023-09-30" @default.
- W2150829038 title "Using copulas for modeling stochastic dependence in power system uncertainty analysis" @default.
- W2150829038 doi "https://doi.org/10.1109/pes.2009.5275265" @default.
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