Now-casting photovoltaic power with wavelet analysis and extreme learning machines

A. Teneketzoglou, N.G. Paterakis, J.P.S. Catalão

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)

Samenvatting

High penetration of Photovoltaic (PV) systems, a variable resource, poses challenges to the stability and power quality of electrical grids. Forecasting accurately the PV power has been recognized as a way to ease this problem. This work addresses now-casting of PV power with Extreme Learning Machines (ELMs) without exogenous inputs. Wavelet decomposition and multi-resolution analysis is the most effective way to achieve high accuracy for 5 min-ahead forecast up to 70% greater than the persistence model. A neural network evaluation algorithm based on multiple initializations and incremental hidden nodes is applied and ELMs performance and computation efficiency is evaluated versus Time Delay Neural Networks (TDNNs) for time and time-frequency domain forecasting.

Originele taal-2Engels
Titel2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Aantal pagina's6
ISBN van elektronische versie978-1-5090-0191-0
DOI's
StatusGepubliceerd - 11 sep. 2015
Extern gepubliceerdJa
Evenement18th International Conference on Intelligent System Application to Power Systems (ISAP 2015) - Porto, Portugal
Duur: 11 sep. 201517 sep. 2015
Congresnummer: 18

Congres

Congres18th International Conference on Intelligent System Application to Power Systems (ISAP 2015)
Verkorte titelISAP 2015
Land/RegioPortugal
StadPorto
Periode11/09/1517/09/15

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