Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
PV power forecast using a nonparametric PV model
Year:2015
Research Areas
  • Electronic technology and of the communications
Information
Abstract
Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%. ? 2015 Elsevier Ltd. All rights reserved.
International
Si
JCR
Si
Title
Solar Energy
ISBN
0038-092X
Impact factor JCR
3,541
Impact info
Datos JCR del año 2013
Volume
115
10.1016/j.solener.2015.03.006
Journal number
From page
354
To page
368
Month
MARZO
Ranking
Participants
  • Autor: Marcelo Pinho Almeida (Universidad de Sao Paulo)
  • Autor: Oscar Perpiñan Lamigueiro (UPM)
  • Autor: Luis Narvarte Fernandez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Centro o Instituto I+D+i: Instituto de Energía Solar
  • Departamento: Ingeniería Eléctrica, Electrónica Automática y Física Aplicada
  • Departamento: Teoría de la Señal y Comunicaciones (Provisional)
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)