A Study on Output Monitoring of Green Roof Integrated PV System through Surface Temperature Algorithm

The centralized power supply system and rainwater treatment system, which are major infrastructure in modern cities, are showing their limitations in accommodating environment load due to climate changes that has aggravated recently. As a result, complex issues such as shortage of reserve power and urban flooding have emerged. As a single solution, decentralized systems such as a model integrating photovoltaic system and rooftop greening system are suggested. When these two systems are integrated and applied together, the synergy effect is expected as the rooftop greening has an effect of preventing urban flooding by controlling peak outflow and also reduces ambient temperature and thus the surface temperature of solar cells is lowered and power generation efficiency is improved. This study aims to compare and analyze the monitoring results of four algorithms that define correlations between micro-climate variables around rooftop greening and the surface temperature of solar cells and generate their significance. By doing so, this study seeks to present an effective algorithm that can estimate the surface temperature of solar cell that has direct impact on the efficiency of photovoltaic power generation by observing climate variables.