Results 1 to 10 of about 6,348 (109)

Risk-Aware Distributionally Robust Optimization for Mobile Edge Computation Task Offloading in the Space–Air–Ground Integrated Network [PDF]

Sensors, 2023
As an emerging network paradigm, the space–air–ground integrated network (SAGIN) has garnered attention from academia and industry. That is because SAGIN can implement seamless global coverage and connections among electronic devices in space, air, and ...
Zhiyuan Li, Pinrun Chen
doaj   +2 more sources

Distributionally robust optimization for fire station location under uncertainties [PDF]

Scientific Reports, 2022
Emergency fire service (EFS) systems provide rescue operations for emergencies and accidents. If properly designed, they can decrease property loss and mortality.
Jinke Ming, Jean-Philippe P. Richard, Rongshui Qin, Jiping Zhu   +3 more
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Sinkhorn Distributionally Robust Conditional Quantile Prediction with Fixed Design [PDF]

Entropy
This paper proposes a novel data-driven distributionally robust framework for conditional quantile prediction under the fixed design setting of the covariates, which we refer to as Sinkhorn distributionally robust conditional quantile prediction.
Guohui Jiang, Tiantian Mao
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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
doaj   +1 more source

Distributionally Robust Co-optimization of Transmission Network Expansion Planning and Penetration Level of Renewable Generation

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, Xiaoyuan Xu, Hongyan Ma, Zheng Yan   +3 more
doaj   +1 more source

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, Sadiq Ahmad, Irshad Hussain, Muhammad Naeem, Lucian Mihet-Popa   +4 more
doaj   +1 more source

Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach

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
doaj   +1 more source

Day-ahead Network-constrained Unit Commitment Considering Distributional Robustness and Intraday Discreteness: A Sparse Solution Approach

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, Baorong Zhou, Xiuli Wang, Bo Zeng, Jizhong Zhu, Haoyong Chen, Waisheng Zheng   +6 more
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Wasserstein distance-based distributionally robust optimal scheduling in rural microgrid considering the coordinated interaction among source-grid-load-storage

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, Jianxu Xing, Qinchao Li, Shengyuan Liu, Jien Ma, Jiaqian Chen, Lei Han, Weiqiang Qiu, Zhenzhi Lin, Li Yang   +9 more
doaj   +1 more source

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
doaj   +1 more source