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Identifying Representative Load Time Series for Load Flow Calculations.

, , , and . DARE@PKDD/ECML, volume 10691 of Lecture Notes in Computer Science, page 83-93. Springer, (2017)

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Representation Learning in Power Time Series Forecasting, , and . Deep Learning: Algorithms and Applications, Springer, (2020)Continuous Learning of Deep Neural Networks to Improve Forecasts for Regional Energy Markets, , and . International Federation of Automatic Control (IFAC) World Congress, page 12175--12182. Elsevier, (2020)Probabilistic upscaling and aggregation of wind power forecasts, , , , and . Energy, Sustainability and Society, 10 (1): 15 (2020)Forecasting Power Grid States for Regional Energy Markets with Deep Neural Networks., , and . IJCNN, page 1-8. IEEE, (2020)Using grid supporting flexibility in electricity distribution networks., , , , , and . GI-Jahrestagung, volume P-294 of LNI, page 531-544. GI, (2019)