This paper presents a statistical approach for identifying the significant impact of cracks on the output power performance of photovoltaic (PV) modules. Since there are a few statistical analysis of data for investigating the impact of cracks in PV modules in real-time long-term data measurements. Therefore, this paper will demonstrate a statistical approach which uses two statistical techniques: T-test and F-test. Electroluminescence (EL) method is used to scan possible cracks in the examined PV modules. Moreover, virtual instrumentation (VI) LabVIEW software is used to predict the theoretical output power performance of the examined PV modules based on the analysis of I-V and P-V curves. The statistical analysis approach has been validated using 45 polycrystalline PV modules at the University of Huddersfield, UK.
|Title of host publication
|2017 IEEE Manchester PowerTech
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 20 Jul 2017
|12th IEEE Power and Energy Society PowerTech Conference: Towards and Beyond Sustainable Energy Systems - University of Manchester, Manchester, United Kingdom
Duration: 18 Jun 2017 → 22 Jun 2017
Conference number: 12
http://sites.ieee.org/pes-powertech/ (Link to Conference Website )
|12th IEEE Power and Energy Society PowerTech Conference
|18/06/17 → 22/06/17