The impact of available data history on the performance of photovoltaïc generation forecasting models - Mines Paris Accéder directement au contenu
Communication Dans Un Congrès Année : 2013

The impact of available data history on the performance of photovoltaïc generation forecasting models

Résumé

The continuous growth of solar power capacity raises challenges to distribution system operators regarding power quality and security of supply. Network management systems must be enhanced with short-term forecasting functionalities able to predict the solar plants production in the next hours or days. The provision of individual forecasts for each solar plant on the network is often required. To that purpose, historical measurements are needed for tuning the forecasting models. The situation is challenging for new plants for which long history of measurements is not yet available. In that case, models able to provide accurate production forecasts based on few historical production data, are required. In this paper, we investigate the performance of state-of-the-art short-term PV forecasting models as a function of the historical data available for tuning. We compare the results with those obtained by a reference model whose utilization does not require more than one day of past production data. Our analysis relies on production data from a 200 kWc solar plant located in the south-east of France. It shows that satisfactory performances can be expected from state-of-the-art models, when calibrated with no more than one or two weeks of training data.
Fichier principal
Vignette du fichier
CIRED2013_0856.pdf (200.54 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00870576 , version 1 (04-05-2017)

Identifiants

Citer

Arthur Bossavy, Andrea Michiorri, Robin Girard, Georges Kariniotakis. The impact of available data history on the performance of photovoltaïc generation forecasting models. 22nd International Conference on Electricity Distribution - CIRED 2013, Jun 2013, Stockholm, Sweden. 4 p. - ISBN 978-1-84919-732-8, ⟨10.1049/cp.2013.0971⟩. ⟨hal-00870576⟩
230 Consultations
166 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More