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This study explores the optimization of solar energy harvesting in Truro City in the UK using PVSyst simulations integrated with real-time meteorological data. Focusing on panel orientation, tilt angle, shading, and albedo, the research aimed to enhance both energy efficiency and economic viability of photovoltaic (PV) systems in green buildings. A 100 kWp rooftop solar installation served as the case study. Energy outputs derived from spreadsheet-based models and PVSyst simulations were compared to validate results. Optimal tilt angles were identified between 35° and 39°, and the azimuth angle of 0° yielded the highest energy gain without requiring solar tracking. Fixed configurations with a 5 m pitch showed only a 10% shading loss, requiring 1680 m2 of space and generating an average of 646.83 kWh/m2 monthly. Compared to recent works, our integration of real-time climate data improved simulation accuracy by 6–9%, refining operational planning and decision-making processes. This included better timing of high-load activities and enhanced prediction for grid feedback. The study demonstrates that data-driven optimization significantly improves performance reliability and system design, offering practical insights for solar infrastructure in similar temperate climates. These results provide a benchmark for urban energy planners seeking to balance performance and spatial constraints in PV deployment.
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Hosseini et al. (2025) studied this question.
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