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Conference Papers Year : 2020

Investigation of Power Line Sag Uncertainty in Day-Ahead DLR Forecast Models

Abstract

Dynamic line rating method (DLR) is a novel and cost-effective way to extend power overhead lines (OHLs) transfer capacity based on real-time monitoring of the weather parameters in the vicinity of the conductor. Via DLR models not only real-time, but also day-ahead transfer capacity calculation is possible which is more important from the aspect of TSOs. It is important to mention, that these DLR predictions are based on weather forecasts that usually has some uncertainty. The aim of the paper is to identify the potential risk of forecasted power line ampacity due to uncertain weather forecast. To investigate this rarely studied topic, several simulations were carried out applying real power line parameters and forecasted weather data. The results of the simulations showed that under unfavorable weather conditions the uncertainty of the weather prediction could significantly increase the sag of the OHLs if they fully utilized. To monitor the real-time state of the conductor’s sag, a novel risk factor calculation method was also investigated that provides additional safety information for the system operators in real time.
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hal-03741535 , version 1 (01-08-2022)

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Levente Rácz, Dávid Szabó, Gábor Göcsei, Bálint Németh. Investigation of Power Line Sag Uncertainty in Day-Ahead DLR Forecast Models. 11th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Jul 2020, Costa de Caparica, Portugal. pp.328-336, ⟨10.1007/978-3-030-45124-0_31⟩. ⟨hal-03741535⟩
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