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

Arthur Bossavy 1 Andrea Michiorri 1 Robin Girard 1 Georges Kariniotakis 1
1 PERSEE - Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques
Abstract : 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.
Keywords : solar power stations distribution networks load forecasting photovoltaic power systems power supply quality
Type de document :
Communication dans un congrès
Liste complète des métadonnées

Littérature citée [10 références]  Voir  Masquer  Télécharger
https://hal-mines-paristech.archives-ouvertes.fr/hal-00870576
Contributeur : Magalie Prudon <>
Soumis le : jeudi 4 mai 2017 - 14:10:13
Dernière modification le : lundi 12 novembre 2018 - 11:00:35
Archivage à long terme le : samedi 5 août 2017 - 13:28:29

Fichier

CIRED2013_0856.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

ENSMP | PARISTECH | PERSEE | INSTITUT-TELECOM | PSL | ERSEI

Citation

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⟩

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

340

Téléchargements de fichiers

350

Contact

Informations

CCSD