Fault detection using acceptance ratio analysis on polycrystalline grid-connected photovoltaics system

• Published in: International Journal of Power Electronics and Drive Systems
• Main Author: Muhammad N.; Roland F.; Zainuddin H.
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150477757&doi=10.11591%2fijpeds.v14.i2.pp1098-1109&partnerID=40&md5=9a3a976f7300a56897dea495f9fca1c0

Around the world, electricity generation from PV photovoltaic systems is increasing, achieving 10-20% PV system efficiency. However, PV systems degrade due to the technology and the operating conditions and become worse in tropical climate countries. Hence, degradation is one of the key performance indicators for the reliability assessment of a PV system. This paper presents the acceptance ratio (AR) analysis grid-connected photovoltaic (GCPV) located on the campus of the Universiti Teknologi MARA, Shah Alam, Malaysia as the key performance indicators. A comparative analysis of the actual and predicted AC Power and AR of the polycrystalline GCPV system is carried out over monitoring of a one-year period. MATLAB software is chosen to simulate the output power using actual data. Malaysian Standard MS2692:2020 has noted that the AR value must ≥ 0.9 to classify as accepted in testing and commissioning tests and AR < 0.9 has been indicated as a non-accepted GCPV system. The results of acceptance ratio (AR), yield (Y), specific yield (SY), and performance ratio (PR) show that almost half of the AR’s data results show below 0.9 with the performance ratio of PV systems was less than 75%, indicating that the systems needed to be completely replaced. © 2023, Institute of Advanced Engineering and Science. All rights reserved.