Congestion Prediction in Energy Networks Using Machine Learning

Energy networks are often very complex which results in highly unpredictable congestion patterns in the physical constraints of the network. Most efforts to model congestion in energy networks are made on toy problems. Here, the objective is to model and predict congestion in a real physical energy network using automated machine learning systems, in particular […]

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