Prediction of Maximum Solar Energy Harvest Considering Year-Round Sky Coverage Conditions and Integrating Shading Effect for Fixed PV Panels

Abstract

The installation of solar photovoltaic (PV) panels is growing globally as the international community transitions from fossil fuel energy to clean and sustainable resources such as solar energy, wind energy, hydropower, and bioenergy. Among various renewable energy technologies, the capacity of power generation using solar PV has expanded dramatically in recent years. In an attempt to maximize the irradiance on PV panels of various inclinations and orientations, this dissertation implements the Sunray-Energy Algorithm (SEA), a tool developed to estimate the maximum solar energy incident on photovoltaic (PV) solar panels, optimal tilt angles, and orientations under various sky coverage conditions and shading effects.One study investigated the impact of adjusting solar panel tilt angles on energy capture in Tucson, Arizona, over a decade, focusing on worst-case sky cover scenarios. A sunray vector analysis and energy calculation model with six-minute intervals reveal that a fixed tilt of approximately 32° due south results in an annual energy harvest of 2297 kWh/m². Seasonal adjustments—0° in summer, 17.5° in spring, 45° in fall, and 57.5° in winter—can further increase energy capture by 4.28% (two-season), 7.06% (four-season), and 8.42% (monthly) compared to a fixed tilt at local latitude SEA has been further enhanced to determine optimal tilt angles and the corresponding maximum solar energy harvest for solar panels across various orientations, utilizing 21 years of real cloud-cover data for Tucson and 10 years for Sydney, rather than worst-case sky cover scenarios. The model conducts calculations every five minutes when solar elevation angles exceed 5°, recommending tilt angles aligned with local latitude for yearly adjustments and specific angles for biannual and seasonal optimizations. Vertical PV installations are also analyzed, showing potential energy savings of approximately 1160.58 kWh/m²/year in Tucson and 1105.98 kWh/m²/year in Sydney. Applied to a 6 MW solar plant at The University of Arizona Tech Park, SEA projects annual energy yields between 2206.36 kWh/m² and 2407.40 kWh/m². Economic analysis reveals a payback period of 6.78 to 7.63 years and LCoE values of $33.08/MWh to $44.05/MWh. Sensitivity analysis identifies capacity factor and installation cost per watt as key influencers on LCoE, emphasizing the importance of strategic decisions regarding Operations and Maintenance (O&M) costs. Python code is developed to improve the SEA performance to account for inter-row shading effects and cost-effectiveness of PV solar fields. By optimizing inter-row spacing and implementing both fixed and dynamic tilt adjustments, the study identifies a 1-meter spacing as optimal for balancing energy capture and shading losses. Monthly tilt angle adjustments enhance annual energy harvest by approximately 8.5% compared to a fixed tilt of 32° in Tucson, AZ. Using the LM-BFGS optimization algorithm to minimize LCoE as an objective function, the findings identify key parameters that result in an optimized LCoE of approximately $11.20 per MWh. The study highlights the importance of minimizing installation and operational costs, as well as managing land expenses.