Results 11 to 20 of about 3,143,268 (283)
Kernel Distributionally Robust Optimization [PDF]
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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Regularization for Wasserstein distributionally robust optimization
ESAIM: Control, Optimisation and Calculus of Variations, 2023 Optimal transport has recently proved to be a useful tool in various machine learning applications needing comparisons of probability measures. Among these, applications of distributionally robust optimization naturally involve Wasserstein distances in their models of uncertainty, capturing data shifts or worst-case scenarios.
Azizian, Waïss +2 more
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Shortfall-Based Wasserstein Distributionally Robust Optimization
Mathematics, 2023 In this paper, we study a distributionally robust optimization (DRO) problem with affine decision rules. In particular, we construct an ambiguity set based on a new family of Wasserstein metrics, shortfall–Wasserstein metrics, which apply normalized ...
Ruoxuan Li, Wenhua Lv, Tiantian Mao
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Probabilistic Optimization Techniques in Smart Power System
Energies, 2022 Uncertainties are the most significant challenges in the smart power system, necessitating the use of precise techniques to deal with them properly. Such problems could be effectively solved using a probabilistic optimization strategy.
Muhammad Riaz +4 more
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Journal of Modern Power Systems and Clean Energy, 2022 Transmission network expansion can significantly improve the penetration level of renewable generation. However, existing studies have not explicitly revealed and quantified the trade-off between the investment cost and penetration level of renewable ...
Jingwei Hu +3 more
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IET Renewable Power Generation, 2023 Integrated generation, transmission, and storage expansion planning (IGT&SP) is the cornerstone to realize low‐carbon transition considering security constraints in the long run.
Lu Qiu, Yangqing Dan, Xukun Li, Ye Cao
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Journal of Modern Power Systems and Clean Energy, 2023 Quick-start generation units are critical devices and flexible resources to ensure a high penetration level of renewable energy in power systems. By considering the wind uncertainty and both binary and continuous decisions of quick-start generation units
Xiaodong Zheng +6 more
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Consensus Distributionally Robust Optimization With Phi-Divergence
IEEE Access, 2021 We study an efficient algorithm to solve the distributionally robust optimization (DRO) problem, which has recently attracted attention as a new paradigm for decision making in uncertain situations.
Shunichi Ohmori
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Energy Reports, 2021 The microgrid (MG) is an effective way to alleviate the impact of the large-scale penetration of distributed generations. Due to the seasonal characteristics of rural areas, the load curve of the rural MG is different from the urban MG.
Changming Chen +9 more
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Multi-Energy Microgrid Data-Driven Distributionally Robust Optimization Dispatch Considering Uncertainty Correlation [PDF]
Dianli jianshe[Objective] Multi-energy microgrids（MEMGs）can integrate multiple energy carriers to improve energy efficiency，thereby contributing to the achievement of "dual carbon" goals. [Methods] This study proposes a data-driven distributionally robust optimization
LI Jiawei, SUN Qinghe, WANG Qiong, YE Yujian, HU Heng, ZHANG Xi
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