A research team led by the University of Science and Technology of China has developed a framework to assess the fire performance of building-integrated photovoltaic (BIPV) façades. The framework identifies key fire risk factors and prioritizes measures to prevent ignition and limit fire spread.
“Although previous studies have investigated the fire behavior of PV materials and modules, systematic fire risk assessment and resilience optimization for BIPV façades remain limited,” corresponding author Yu Wang told pv magazine. “In this work, data-driven sensitivity analysis and expert-judgment-based weighting methods were used to identify the dominant fire risk factors among 16 indicators covering electrical conditions, environmental factors, module materials, and installation conditions.”
Wang said the team also conducted a fire resilience optimization analysis based on the fire performance assessment to translate the most significant risk factors into practical mitigation measures.
“These measures cover ignition prevention, fire-spread suppression, monitoring, maintenance, and emergency response, extending the analysis from risk identification to engineering application,” he said.
The researchers began by establishing 16 fire risk indicators: temperature differences between shaded and unshaded areas; aging of PV modules and associated equipment; DC voltage and current levels; circuit contact resistance; wind load; dust accumulation; ambient temperature; natural disasters such as lightning; module glass thickness; glass type; encapsulation material fire performance; module light transmittance; installation spacing; installation configuration; installation angle; and shielding width.
Drawing on previous and ongoing experiments and published studies, the researchers used normalized variance contribution (NVC) analysis to assess variations in the indicators’ normalized risk scores. Nine experts from Asia and Europe, including university researchers, fire service leaders, fire investigators, and senior engineers, also evaluated the indicators using the analytic hierarchy process (AHP). A fuzzy version of AHP accounted for uncertainty in expert judgments, while data perturbation tests assessed the stability of the NVC rankings.
The team linked the dominant risk factors to 15 safety measures: electroluminescence inspection; compliant equipment and wiring; rapid shutdown; encapsulant flammability ratings; module layout and spacing; module and surrounding fire loads; DC arc-fault detection; drone-based infrared inspection; machine learning-based detection; inspection and maintenance frequency; fault diagnosis and maintenance coverage; cleaning frequency; safe firefighting distances and electric shock prevention; extinguishing agent selection; and firefighting strategies and standards. The same experts ranked the measures using AHP.
“The most surprising finding was that the data-driven NVC analysis and expert-based AHP and triangular fuzzy number (TFN)-AHP assessments consistently identified five dominant risk factors despite differences in their overall rankings,” Wang said. “DC voltage and current magnitude ranked first in both the data-driven analysis and the expert-based assessments. Equipment aging, circuit contact resistance, module glass type, and encapsulation fire performance also consistently emerged as important factors. This highlights the need to consider electrical ignition hazards alongside the materials that influence fire development.”
Further uncertainty testing showed that the same six indicators – DC voltage and current magnitude, equipment aging, module glass type, circuit contact resistance, glass thickness, and encapsulation fire performance – remained the highest-ranked in the NVC analysis across all valid scenarios, with rank correlations exceeding 0.99.
The experts assigned a combined weight of 60.83% to ignition prevention and fire-spread suppression measures, with rapid shutdown ranking first among individual measures at 19.62%.
The researchers presented the framework in “Framework for fire risk assessment and resilience optimization of building-integrated photovoltaic façades,” published in Applied Thermal Engineering. The research team included scientists from the University of Science and Technology of China and Italy’s University of Trieste.
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