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Jan, 2021
面向快速和可扩展的交流潮流最优控制学习的空间网络分解
Spatial Network Decomposition for Fast and Scalable AC-OPF Learning
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Minas Chatzos, Terrence W. K. Mak, Pascal Van Hentenryck
TL;DR
提出了一种新颖的机器学习方法,用于预测AC-OPF解决方案,该方法具有快速可扩展的培训,通过电力网络的空间分解来学习预测区域的机器学习模型,实验结果证明了该方法的潜力和优越性。
Abstract
This paper proposes a novel
machine-learning
approach for predicting
ac-opf
solutions that features a fast and scalable training. It is motivated by the two critical considerations: (1) the fact that topology
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