Dynamic line rating day-ahead forecasts - cost benefit based selection of the optimal quantile

Romain Dupin (1) , Andrea Michiorri (1) , Georges Kariniotakis (1)

1 PERSEE - Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques

Dynamic Line Rating (DLR) is a promising field of research aiming to help network operators face challenges, such as increased penetration of renewable energies and peak electricity demand. Research on real-time overhead line ampacity estimation is currently advanced and, in the last few years, research has started to address medium-term DLR forecasting. The focus is on probabilistic forecasts, in order to select ratings associated with very low probability of occurrence. For this reason, 1%-quantiles are usually selected. In this paper, the authors propose a methodology for selecting the most appropriate quantiles based on a cost-benefit analysis, considering both the economic benefits of an increased line ampacity and the costs associated with a DLR forecast that is higher than its observed value. The proposed methodology is evaluated using realistic weather data on a virtual line connecting Belgium and France.

Mots clés: Dynamic Line Rating; Renewable energies; Forecast

Domaines: Energétique

Romain Dupin, Andrea Michiorri, Georges Kariniotakis. Dynamic line rating day-ahead forecasts - cost benefit based selection of the optimal quantile. CIRED 2016 workshop - Electrical networks for society and people , CIREC - Centre International de Recherche sur l’Environnement et le Développement, Jun 2016, Helsinki, Finland. ⟨hal-01398440⟩