Solar PV tilt-azimuth optimization using OSM-MEPS and PVLIB: Statistical analysis, techno-economic assessment and ramp-rate modeling

Annual fixed tilt-azimuth in photovoltaic (PV) systems ignore seasonal solar geometry changes, limiting energy yield. This study quantifies monthly tilt-azimuth adjustment benefits using OSM-MEPS and PVLIB across four sites: Serres-C (Greece), Adelaide (Australia), Njagu (Kenya) and UKZN (South Africa). Brute-force optimization (tilt 0 ∘ –90 ∘ , azimuth 0 ∘ –360 ∘ ) identifies the optimal monthly and annual fixed orientations. Benchmarking the annual fixed tilt against eight empirical latitude-based correlations shows that the Luque et al. formulation ( θ opt =3.7+0.69⋅∣ λ ∣) provides the closest agreement with the dual-model simulations, with MAE of 1.87 ∘ across all sites. A repeated-measures ANOVA on 12 monthly observations rejects the null hypothesis for all site-model combinations ( F (2,22)=7.56–41.50, p <0.005). The 𝜂 2 𝑝 values ranging from 0.407 to 0.790 indicate that tilt-azimuth orientation explains 41%–79% of the variance in monthly energy yield after removing seasonal effects. Bonferroni-adjusted comparisons show monthly optimal orientations significantly outperform fixed configurations ( p Bonf <0.03, Cohen’s d >0.90). Energy outputs from the existing and annual fixed optimal orientations do not differ significantly ( p Bonf >0.123) in three of the four locations, indicating that the existing tilt–azimuth configuration is close to the annual optimum. Cross-model validation shows excellent agreement between OSM-MEPS and PVLIB (Pearson r >0.99). A techno-economic assessment using South Africa’s 2025/2026 feed-in tariff ( R 1.50∕ kWh ) shows carport PV systems rated 115–346 kW achieve internal rates of return of 12.2%–13.4% and positive net present values ( R 0.068−1.345 million). Integrating orientation optimization, effect-size analysis, cross-model verification, techno-economic evaluation and ramp-rate modeling within an open-source framework provides a comprehensive methodology for PV system assessment. This enables maximization of solar PV energy yield, better operational flexibility and investment decisions.