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This vine copula performs better than the the Gaussian copula since the latter has been proven to have 0 tail dependence and, therefore, is less precise when describing the complicated dependence structures existing in renewable generation
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Vine-copula technique, which is capable of modeling the high-dimensional, dependent multivariate with a variety of bivariate copulae such as Frank and Gumbel copulae to better represent tail dependence in the correlated samples. This emulator allow us to evaluate the time-consuming CPF solver at the sampled values with a negligible computational cost.įurthermore, to simulate the high-dimensional dependent samples that represent the uncertainties from the loads and renewables, we propose to adopt a novel Known as a Bayesian-learning-based method for a nonlinear regression problem in statistics, the GPE can serve as a nonparametric, reduced-order model representation for the nonlinear CPF model. To overcome the abovementioned shortcomings, this paper proposes, for the first time, to utilize a method based on a Gaussian process emulator (GPE) to solve the probabilistic CPF problem. System, to which correlated renewable generation are attached, reveal theĮxcellent performance of the proposed method. The simulations conducted on the IEEE 57-bus The time-consuming continuation power-flow solver at the sampled values with a Gaussian-process-emulator-based reduced-order model to replace the originalĬomplicated continuation power-flow model. The traditional Monte-Carlo method, we propose to use a nonparametric, Furthermore, to reduce the prohibitive computational time required in Its capability in simulating complex multivariate highly dependent model We propose to generate system uncertain inputs via a novel vine copula due to Quantify the impact of uncertain power injections on the load margins. Facing theseĬhallenges, this paper proposes a cost-effective, nonparametric method to
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Threatening the security of power system planning and operation. The loads bring large uncertainties in the power system states that are The increasing penetration of renewable energy along with the variations of