Results 21 to 30 of about 9,044 (253)
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
The Distributionally Robust Optimization Reformulation for Stochastic Complementarity Problems
We investigate the stochastic linear complementarity problem affinely affected by the uncertain parameters. Assuming that we have only limited information about the uncertain parameters, such as the first two moments or the first two moments as well as ...
Liyan Xu, Bo Yu, Wei Liu
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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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Probabilistic Optimization Techniques in Smart Power System
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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Robustness to dependency in portfolio optimization using overlapping marginals [PDF]
In this paper, we develop a distributionally robust portfolio optimization model where the robustness is across different dependency structures among the random losses.
Doan, Xuan Vinh +2 more
core +1 more source
Research on power system flexibility considering uncertainties
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 Distributed Generation Hosting Capacity Assessment in Distribution Systems
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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Distributionally Robust Submodular Maximization
Submodular functions have applications throughout machine learning, but in many settings, we do not have direct access to the underlying function $f$. We focus on stochastic functions that are given as an expectation of functions over a distribution $P$. In practice, we often have only a limited set of samples $f_i$ from $P$.
Staib, Matthew +2 more
openaire +3 more sources
Distributionally Robust Convex Optimization [PDF]
Distributionally robust optimization is a paradigm for decision making under uncertainty where the uncertain problem data are governed by a probability distribution that is itself subject to uncertainty. The distribution is then assumed to belong to an ambiguity set comprising all distributions that are compatible with the decision maker’s prior ...
Wolfram Wiesemann +2 more
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Distributionally Robust Low-Carbon Scheduling Model for Virtual Power Plants Considering Emerging Distributed Resources and Electricity Carbon Trading [PDF]
[Objective] To improve the low-carbon economic performance of scheduling strategies for virtual power plants, this study proposes a distributionally robust low-carbon scheduling model that incorporates emerging distributed resources and electricity ...
WANG Jiayi, HE Shuaijia
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