Análise térmica de uma câmara frigorífica comercial via método de sensoriamento remoto: estudo de caso

Abstract

The food trade widely employs refrigeration systems, which require high electricity consumption. This study proposes integrating remote monitoring technologies with data analysis to optimize the thermal management of a commercial cold storage room. The work aims to determine the system's heat load through open-source datalogger sensing, using DS18B20 temperature sensors, an SCT-013 current sensor, and an RTC module connected to ESP32 and Arduino Mega platforms. Data was collected over two months, with measurements every 1 minute, and analyzed in Excel. The total heat load was calculated considering gains from transmission, infiltration, products, occupancy, motors, and lighting. Results revealed that 45.98% of thermal losses stem from wall transmission, followed by motors (23.03%) and infiltration (13.05%). After optimizations (such as enhanced insulation, LED lighting replacement, and air curtain installation), the heat load was reduced by 55%, from 89,814.05 to 49,327.37 BTU/24h, with an estimated monthly savings of R$ 877.64. It is concluded that remote sensing is a viable tool for energy diagnosis, enabling significant improvements in operational efficiency and cost reduction.