Three PV plants performance analysis using the principal component analysis method
Mustapha Mabrouki and
Energy, 2020, vol. 207, issue C
This paper presents a comparative analysis of the performance of three grid-connected photovoltaic power plants, of about 2kWp for each plant, using the principal component analysis (PCA) method. These systems include three silicon technologies. The analysis is based on the performance parameters described in the international standard IEC 61724. To perform this comparative analysis, the energy production, the operational and the meteorological data are first collected for a period of time. The performance evaluation of PV plants is then performed based on several performance indicators such as Final Yield, Performance Ratio, System Losses, Capture Losses, Array Efficiency and Capacity Factor. Using the PCA method, the correlation between the performance parameters and the meteorological variables is then studied and analyzed. The resulting analysis shows that the Polycrystalline silicon technology is the most performing one. The annual average values of the Performance Ratio were found to be 86.66% for the polycrystalline against 84.76% and 83%, for the monocrystalline and amorphous, respectively. For the daily data, the PCA method reveals that the Performance Ratio is independent of the solar irradiation but it has a slight correlation with temperature and System Losses and a strong correlation with Capture Losses. The result shows also that the temperature acts slightly on the amorphous compared to the crystalline ones.
Keywords: PCA; Performance ratio; Final yield; Solar photovoltaic plant; Silicon PV technologies (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:207:y:2020:i:c:s0360544220314225
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 Haili He ().