Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 319-326 |
Journal / Publication | Applied Energy |
Volume | 93 |
Online published | 4 Jan 2012 |
Publication status | Published - May 2012 |
Externally published | Yes |
Link(s)
Abstract
This paper develops new real time prediction models for output power and energy efficiency of solar photovoltaic (PV) systems. These models were validated using measured data of a grid-connected solar PV system in Macau. Both time frames based on yearly average and monthly average are considered. It is shown that the prediction model for the yearly/monthly average of the minutely output power fits the measured data very well with high value of R2. The online prediction model for system efficiency is based on the ratio of the predicted output power to the predicted solar irradiance. This ratio model is shown to be able to fit the intermediate phase (9am to 4pm) very well but not accurate for the growth and decay phases where the system efficiency is near zero. However, it can still serve as a useful purpose for practitioners as most PV systems work in the most efficient manner over this period. It is shown that the maximum monthly average minutely efficiency varies over a small range of 10.81% to 12.63% in different months with slightly higher efficiency in winter months. © 2011 Elsevier Ltd.
Research Area(s)
- Efficiency, Grid connection, Photovoltaic system, Solar irradiance
Citation Format(s)
Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems. / Su, Yan; Chan, Lai-Cheong; Shu, Lianjie et al.
In: Applied Energy, Vol. 93, 05.2012, p. 319-326.
In: Applied Energy, Vol. 93, 05.2012, p. 319-326.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review