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Enhancing Congestion Forecast for TSOs: a Probabilistic Approach

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This paper addresses the challenges of large uncertainties in day-ahead congestion management due to increased renewable energy integration, complex network interactions, and short-term market trading. These uncertainties lead to increased congestion risks and costly redispatch actions. The paper introduces a novel probabilistic congestion forecasting

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