Results 21 to 30 of about 8,860,352 (207)
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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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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Distributionally Robust and Generalizable Inference
Statistical Science, 2023 We discuss recently developed methods that quantify the stability and generalizability of statistical findings under distributional changes. In many practical problems, the data is not drawn i.i.d. from the target population. For example, unobserved sampling bias, batch effects, or unknown associations might inflate the variance compared to i.i.d ...
Rothenhäusler, Dominik +1 more
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Frequency-Constrained Resilient Scheduling of Microgrid: A Distributionally Robust Approach [PDF]
IEEE Transactions on Smart Grid, 2021 In order to prevent the potential frequency instability due to the high Power Electronics (PE) penetration under an unintentional islanding event, this paper presents a novel microgrid scheduling approach which includes the system frequency dynamics as ...
Zhongda Chu, Ning Zhang, Fei Teng
semanticscholar +1 more source
IEEE Transactions on Smart Grid, 2022 This paper focuses on the distributionally robust dispatch for integrated transmission-distribution (ITD) systems via distributed optimization. Existing distributed algorithms usually require synchronization of all subproblems, which could be hard to ...
J. Zhai +4 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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IEEE Transactions on Power Systems, 2022 As the penetration of intermittent renewable energy increases in bulk power systems, flexible generation resources, such as quick-start gas units, become important tools for system operators to address the power imbalance problem. To better capture their
Siyuan Wang +3 more
semanticscholar +1 more source
Distributionally-robust Recommendations for Improving Worst-case User Experience
The Web Conference, 2022 Modern recommender systems have evolved rapidly along with deep learning models that are well-optimized for overall performance, especially those trained under Empirical Risk Minimization (ERM).
Hongyi Wen +5 more
semanticscholar +1 more source
Data-Driven Chance Constrained Optimization under Wasserstein Ambiguity Sets [PDF]
, 2018 We present a data-driven approach for distributionally robust chance constrained optimization problems (DRCCPs). We consider the case where the decision maker has access to a finite number of samples or realizations of the uncertainty.
Cherukuri, Ashish +2 more
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Distributionally Robust Graph-based Recommendation System [PDF]
The Web ConferenceWith the capacity to capture high-order collaborative signals, Graph Neural Networks (GNNs) have emerged as powerful methods in Recommender Systems (RS). However, their efficacy often hinges on the assumption that training and testing data share the same
Bohao Wang +8 more
semanticscholar +1 more source