PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

The performance status of a grid-connected photovoltaic (GCPV) system is denoted by performance indices, namely performance ratio, capacity factor, and even through power acceptance ratio (AR), as documented in Malaysia Standard (MS) procedures for acceptance test of GCPV testing and commissioning (TNC). Even though AR analysis can be either on the DC or AC side, the MS TNC procedures implemented analysis on the AC side. Therefore, the question arises whether there is any significant difference when using AC AR analysis compared to DC AR analysis in evaluating the system performance. Thus, this paper evaluates the differences between applying DC AR analysis and AC AR analysis in accessing the performance of the ten kWp GCPV system in Malaysia. The AR analytical analysis employed the 2019 one-year historical data of solar irradiance, module temperature, DC power, and AC power. The results demonstrated that the monthly AC AR were consistently lower than DC AR with a percentage difference of approximately 3%. The percentage discrepancy was due to the variation of actual inverter efficiencies compared to the declared constant value by the manufacturer used in the AR prediction model. These findings have verified a significant difference between DC AR analysis and AC AR analysis. Most importantly, this study has highlighted the significance of AC AR analysis compared to DC AR analysis as a tool to evaluate GCPV system performance because AC AR has taken an additional factor into consideration, which is the inverter efficiency variation.

• Appiah, A. Y., Zhang, X., Ayawli, B. B. K., & Kyeremeh, F. (2019). Review and performance evaluation of photovoltaic array fault detection and diagnosis techniques. International Journal of Photoenergy, 2019, Article 6953530. https://doi.org/10.1155/2019/6953530

• Hansen, C., Stein, J., & Riley, D. (2012). Effect of time scale on analysis of PV system performance. Sandia National Laboratories. https://doi.org/10.13140/2.1.1150.3368

• Humada, A. M., Hojabri, M., Mohamed, M. B., Sulaiman, M. H., & Dakheel, T. H. (2014). A proposed method of photovoltaic solar array configuration under different partial shadow conditions. In Advanced Materials Research (Vol. 983, pp. 307-311). Trans Tech Publications LTD. https://doi.org/10.4028/www.scientific.net/AMR.983.307

• Hussin, M. Z., Omar, A. M., Zain, Z. M., & Shaari, S. (2013). Performance of grid-connected photovoltaic system in equatorial rainforest fully humid climate of Malaysia. International Journal of Applied Power Engineering (IJAPE), 2(3), 105-114. https://doi.org/10.11591/ijape.v2i3.2090

• IEC TS 61724. (2016). Photovoltaic system performance - Part 3: Energy evaluation method. International Electrotechnical Commission.

• Jaszczur, M., Teneta, J., Styszko, K., Hassan, Q., Burzyńska, P., Marcinek, E., & Łopian, N. (2019). The field experiments and model of the natural dust deposition effects on photovoltaic module efficiency. Environmental Science and Pollution Research, 26(9), 8402-8417. https://doi.org/10.1007/s11356-018-1970-x

• Khatib, T., Yasin, A., Mohammad, A. A., & Ibrahim, I. A. (2017). On the effectiveness of optimally sizing an inverter in a grid-connected photovoltaic power system. In 14th International Conference on Smart Cities: Improving Quality of Life Using ICT & IoT (HONET-ICT) (pp. 48-52). IEEE Publishing. https://doi.org/10.1109/HONET.2017.8102220

• Kim, G. G., Lee, W., Bhang, B. G., Choi, J. H., & Ahn, H. (2021). Fault Detection for Photovoltaic Systems Using Multivariate Analysis With Electrical and Environmental Variables. IEEE Journal of Photovoltaics, 11(1), 202-212. https://doi.org/10.1109/JPHOTOV.2020.3032974

• Marion, B., Adelstein, J., Boyle, K. E., Hayden, H., Hammond, B., Fletcher, T., Canada, B., Narang, D., Kimber, A., Mitchell, L., Rich, G., & Townsend, T. (2005). Performance parameters for grid-connected PV systems. In Conference Record of the Thirty-first IEEE Photovoltaic Specialists Conference (pp. 1601-1606). IEEE Publishing. https://doi.org/10.1109/PVSC.2005.1488451

• Muhammad, N., Zainuddin, H., Jaaper, E., & Idrus, Z. (2019). An early fault detection approach in grid-connected photovoltaic (GCPV) system. Indonesian Journal of Electrical Engineering and Computer Science, 17(2), 671-679. https://doi.org/10.11591/ijeecs.v17.i2.pp671-679

• Nurdiana, E., Subiyanto, I., Indarto, A., Wibisono, G., & Hudaya, C. (2020). Performance analysis and evaluation of a 10.6 kWp grid-connected photovoltaic system in Serpong. In IOP Conference Series: Materials Science and Engineering (Vol. 909, No. 1, p. 012019). IOP Publishing. https://doi.org/10.1088/1757-899X/909/1/012019

• OFA. (2010). MS IEC 61724:2010 Photovoltaic system performance monitoring-Guidelines for measurement, data exchange and analysis. Online Finding Aid.

• Platon, R., Martel, J., Woodruff, N., & Chau, T. Y. (2015). Online fault detection in PV systems. IEEE Transactions on Sustainable Energy, 6(4), 1200-1207. https://doi.org/10.1109/TSTE.2015.2421447

• SEDA. (2016). Malaysia grid-connected design course. Sustainable Energy Development Authority Malaysia.

• Shukor, F. A. M., Zainuddin, H., Muhammad, N., & Khir, F. L. M. (2021). Acceptance ratio analysis: An early fault indicator for grid- connected photovoltaic system. International Journal on Advanced Science Engineering Information Technology, 11(3), 1214-1223.

• SIRIM. (2020). MS 2692:2020 testing and commissioning of grid-connected photovoltaic system. Department of Standards Malaysia.

• Wittkopf, S., Valliappan, S., Liu, L., Seng, K., Chye, S., & Cheng, J. (2012). Analytical performance monitoring of a 142.5 kWp grid-connected rooftop BIPV system in Singapore. Renewable Energy, 47, 9-20. https://doi.org/10.1016/j.renene.2012.03.034

• Yusoff, N. F., Zakaria, N. Z., Zainuddin, H., & Shaari, S. (2017). Mounting configuration factor for building integrated photovoltaic and retrofitted grid-connected photovoltaic system. Science Letters, 11(1), 1-6.