Optimization and Performance Analysis of Modelled Rooftop Solar Photovoltaic Systems for Urban Energy Sustainability
Keywords:
Load profile, Module efficiency, Optimization, Particle swarm optimization, Rooftop photovoltaic systemAbstract
The rising demand for sustainable energy in urban areas has intensified the need for efficient rooftop solar photovoltaic (PV) systems. Urban rooftops are often constrained by limited space, shading from surrounding buildings, and variable electricity demands, which can reduce the performance of PV installations if not properly accounted for. This study presents a simulation-based approach to optimize rooftop PV systems, integrating module and inverter specifications with realistic urban load profiles to enhance energy output, system efficiency, and self-consumption. The PV system model incorporates monocrystalline silicon modules rated at 330 W with 20.1% efficiency and a temperature coefficient of -0.4%/°C, paired with 5 kW inverters featuring 97.5% efficiency and a maximum DC input voltage of 600 V. Load demand data for a typical day, including both base and variable loads, were used to simulate system performance across 24 hours. The Particle Swarm Optimisation (PSO) algorithm was applied to determine the optimal module quantity, tilt, and orientation, thereby maximising total annual energy generation while aligning production with building load patterns. Results demonstrate that the optimized configuration improves total annual energy output by X% relative to the baseline, increases system efficiency from Y% to Y1%, and raises the self-consumption ratio to A1%, reducing reliance on the central grid. The study highlights the effectiveness of simulation-based modelling combined with optimisation techniques for designing rooftop PV systems that can meet urban energy sustainability goals.
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