Fossil fuels, predominant in fulfilling current energy demands, are implicated in global warming, prompting a global shift towards renewable energy sources. Among these, photovoltaic (PV) solar power plants have garnered significant attention, experiencing a rapid surge in installed power capacity. However, a notable drawback of PV solar power plants is their considerable spatial footprint, emphasizing the pivotal role of efficient space utilization and shading mitigation in their design. Notably, pitch distance, array design, and PV type emerge as critical parameters influencing the performance of these power plants during installation. In the present study, eight distinct PV solar power plant designs were conceptualized, incorporating four different PV array configurations (2P-3P-2L-3L) and two PV types (monofacial-bifacial), each with specified orientations (portrait-landscape). Other parameters were held constant across designs. Leveraging PVsyst software, simulations were conducted for each design, yielding crucial performance metrics, including the annual energy output delivered to the grid (E-grid), performance ratio (PR), and associated CO2 emissions. Subsequently, a Taguchi analysis facilitated optimization based on these results. The outcome of this analysis identified the optimal PV array design as 3D and the optimal PV type as bifacial. Further insight was gained through an ANOVA analysis, revealing the substantial contributions of parameters to overall variability. Specifically, PV type exhibited a significant contribution of 65.27%, while PV array configuration contributed 34.72% to the observed variability in plant performance. These findings not only enhance the understanding of PV power plant design intricacies but also underscore the paramount significance of array design in achieving heightened efficiency and sustainability.