Validated real-time energy models for small-scale grid-connected PV-systems

L.M. Ayompe, A. Duffy, S.J. McCormack and M. Conlon

Energy, 2010, vol. 35, issue 10, 4086-4091

Abstract: This paper presents validated real-time energy models for small-scale grid-connected PV-systems suitable for domestic application. The models were used to predict real-time AC power output from a PV-system in Dublin, Ireland using 30-min intervals of measured performance data between April 2009 and March 2010. Statistical analysis of the predicted results and measured data highlight possible sources of errors and the limitations and/or adequacy of existing models, to describe the temperature and efficiency of PV-cells and consequently, the accuracy of power prediction models. PV-system AC output power predictions using empirical models for PV-cell temperature and efficiency prediction showed lower percentage mean absolute errors (PMAEs) of 7.9–11.7% while non-empirical models had errors of 10.0–12.4%. Cumulative errors for PV-system AC output power predictions were 1.3% for empirical models and 3.3% for non-empirical models. The proposed models are suitable for predicting PV-system AC output power at time intervals suitable for smart metering.

Keywords: Real-time; Grid-connected PV-system; Empirical models; Power; Microgeneration (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544210003440
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:35:y:2010:i:10:p:4086-4091

DOI: 10.1016/j.energy.2010.06.021

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().