Results 31 to 40 of about 9,334 (269)
Distributionally Robust Distributed Generation Hosting Capacity Assessment in Distribution Systems
Energies, 2018 Uncertainties associated with the loads and the output power of distributed generations create challenges in quantifying the integration limits of distributed generations in distribution networks, i.e., hosting capacity.
Mohammad Seydali Seyf Abad +3 more
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Research on power system flexibility considering uncertainties
Frontiers in Energy Research, 2022 In order to help achieve the goal of carbon peak and carbon neutrality, the large-scale development and application of clean renewable energy, like wind generation and solar power, will become an important power source in the future.
Ce Yang +3 more
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Distributionally Robust Recourse Action
CoRR, 2023 A recourse action aims to explain a particular algorithmic decision by showing one specific way in which the instance could be modified to receive an alternate outcome. Existing recourse generation methods often assume that the machine learning model does not change over time.
Duy Nguyen, Ngoc Bui, Viet Anh Nguyen
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Kernel Distributionally Robust Optimization
CoRR, 2020 We propose kernel distributionally robust optimization (Kernel DRO) using insights from the robust optimization theory and functional analysis. Our method uses reproducing kernel Hilbert spaces (RKHS) to construct a wide range of convex ambiguity sets, which can be generalized to sets based on integral probability metrics and finite-order moment bounds.
Zhu, Jia-Jie +3 more
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Distributionally Robust Max Flows [PDF]
, 2020 We study a distributionally robust max flow problem under the marginal distribution model, where the vector of arc capacities is random, with the marginals to the joint multivariate distribution being known, but the correlation being unknown. The goal is to compute the expected value of the max flow under the worst-case joint distribution of arc ...
Chen, Louis L. +3 more
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Stochastic Optimal Power Flow Based on Data-Driven Distributionally Robust Optimization
, 2018 We propose a data-driven method to solve a stochastic optimal power flow (OPF) problem based on limited information about forecast error distributions. The objective is to determine power schedules for controllable devices in a power network to balance ...
camacho +8 more
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Distributionally robust optimization
Acta NumericaDistributionally robust optimization (DRO) studies decision problems under uncertainty where the probability distribution governing the uncertain problem parameters is itself uncertain. A key component of any DRO model is its ambiguity set, that is, a family of probability distributions consistent with any available structural or statistical ...
Daniel Kuhn 0001 +2 more
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Diance yu yibiaoIn order to adapt to the uncertainty of new energy, increase new energy consumption and reduce carbon emissions, an optimal scheduling model of integrated energy distribution network system is proposed based on vine Copula considering three uncertainties
YANG Mingjie +5 more
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, 2017 We consider stochastic programs where the distribution of the uncertain parameters is only observable through a finite training dataset. Using the Wasserstein metric, we construct a ball in the space of (multivariate and non-discrete) probability ...
Esfahani, Peyman Mohajerin, Kuhn, Daniel
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Distributionally Robust Games with Risk-averse Players
, 2016 We present a new model of incomplete information games without private information in which the players use a distributionally robust optimization approach to cope with the payoff uncertainty.
Loizou, Nicolas
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