• Energy Research

Using Griddler software, this study aims to select the optimal metallization design by analyzing the impact of the number and sizes of busbars and fingers on a solar cell’s performance. There is interest in the PV industry to reduce the finger size toward 25 μm in upcoming years. It is shown that an increase in the number and size of busbars and fingers causes an increase in the fill factor; however, with regards to the cell’s efficiency, the shading factor should be considered in addition to the size and number of metal contacts. The results of this study indicate that solar cells’ efficiency could be increased by 0.33–0.84% when using five busbars and a finger width of 35 μm. Moreover, this increase is achieved by reducing the emitter resistance to less than 60 ohm/sq and considering a recombination rate of about 165 fA/cm2.

The installation of large-scale solar (LSS) photovoltaic (PV) power plants continues to rise globally as well as in Malaysia. The data provided by LSS PV consist of five weather stations with seven parameters, a 22-unit inverter, and 1-unit PQM Meter Grid as a big dataset. These big data are rapidly changing every minute, they lack data quality when missing data, and need to be analyzed for a longer duration to leverage their benefits to prevent misleading information. This paper proposed the forecasting power LSS PV using decision tree regression from three types of input data. Case 1 used all 35 parameters from five weather stations. For Case 2, only seven parameters were used by calculating the mean of five weather stations. While Case 3 was chosen from an index correlation of more than 0.8. The analysis of the historical data was carried out from June 2019 until December 2020. Moreover, the mean absolute error (MAE) was also calculated. A reliability test using the Pearson correlation coefficient (r) and coefficient of determination (R2) was done upon comparing with actual historical data. As a result, Case 2 was proposed to be the best input dataset for the forecasting algorithm.