Statistical analysis of the performance and simulation of a two-axis tracking PV system

Perpiñan Lamigueiro, Oscar ORCID: https://orcid.org/0000-0002-4134-7196 (2009). Statistical analysis of the performance and simulation of a two-axis tracking PV system. "Solar Energy", v. 83 (n. 11); pp. 2074-2085. https://doi.org/10.1016/j.solener.2009.08.008.

Descripción

Título: Statistical analysis of the performance and simulation of a two-axis tracking PV system
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: Solar Energy
Fecha: Noviembre 2009
Volumen: 83
Número: 11
Materias:
ODS:
Palabras Clave Informales: two-axis tracking, solar radiation, performance calculation, statistical analysis
Escuela: E.U.I.T. Industrial (UPM) [antigua denominación]
Departamento: Ingeniería Eléctrica [hasta 2014]
Licencias Creative Commons: Reconocimiento - No comercial - Compartir igual

Texto completo

[thumbnail of PERPINAN_ART2009_01.pdf]
Vista Previa
PDF (Portable Document Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (469kB) | Vista Previa

Resumen

The energy produced by a photovoltaic system over a given period can be estimated from the incident radiation at the site where the Grid Connected PV System (GCPVS) is located, assuming knowledge of certain basic features of the system under study. Due to the inherently stochastic nature of solar radiation, the question “How much energy will a GCPVS produce at this location over the next few years?” involves an exercise of prediction inevitably subjected to a degree of uncertainty. Moreover, during the life cycle of the GCPVS, another question arises: “Is the system working correctly?”. This paper proposes and examines several methods to cope with these questions. The daily performance of a PV system is simulated. This simulation and the interannual variability of both radiation and productivity are statistically analyzed. From the results several regression adjustments are obtained. This analysis is shown to be useful both for productivity prediction and performance checking exercises. Finally, a statistical analysis of the performance of a GCPVS is carried out as a detection method of malfunctioning parts of the system.

Más información

ID de Registro: 1843
Identificador DC: https://oa.upm.es/1843/
Identificador OAI: oai:oa.upm.es:1843
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/5484291
Identificador DOI: 10.1016/j.solener.2009.08.008
URL Oficial: http://www.sciencedirect.com/science/article/pii/S...
Depositado por: Oscar Perpiñán Lamigueiro
Depositado el: 06 Oct 2009 06:35
Ultima Modificación: 12 Nov 2025 00:00