INTEGRATED PERFORMANCE MODELING AND LIFE CYCLE CARBON ASSESSMENT OF A RESIDENTIAL GRID-CONNECTED PHOTOVOLTAIC SYSTEM

Abstract

Accurate power forecasting of grid-connected photovoltaic (PV) systems is critical for performance evaluation, financial planning, and grid stability. This study investigates the predictive accuracy of two industry-standard simulation platforms PVsyst and HelioScope by benchmarking their outputs against one year of measured operational data from a 24.64 kWp residential rooftop PV installation in Islamabad, Pakistan (33.53°N, 73.15°E). The system comprises 56 monocrystalline modules (440 Wp each) coupled with a 20-kW inverter operating at a DC/AC ratio of 1.23. Meteorological inputs, including global horizontal irradiance (GHI), diffuse irradiance, and ambient temperature, were analyzed to quantify their influence on energy yield. Key performance indicators reference yield, array yield, final yield, performance ratio (PR), capacity factor, and system losses were evaluated. PVsyst estimated annual energy production of approximately 44 MWh prior to system losses, with nearly 80% delivered after capture and conversion losses. HelioScope predicted annual grid injection of 36.20 MWh after accounting for optical, thermal, mismatch, soiling, and inverter losses. Seasonal trends from both models showed strong agreement with measured data, particularly during high-irradiance summer months. Life cycle assessment indicates that although manufacturing emissions amount to approximately 45 tCO₂-eq, the system offsets nearly 340 tCO₂ over a 25-year operational lifespan. The results confirm the robustness of both modeling platforms for reliable PV performance forecasting under semi-arid climatic conditions.