Smart Deep Learning Model to Recognize PCM Optimization Performance on Solar Cooling System

Abstract

Phase Change Materials (PCMs) offer a significant advantage by reducing the need for multiple cooling systems, potentially revolutionizing thermal comfort in buildings and optimizing thermal energy storage. The intriguing prospect of integrating PCMs into active heating and cooling systems has garnered considerable attention. Furthermore, the compatibility of PCMs with photovoltaic (PV) systems and various renewable energy sources enhances the system’s efficiency. This study explores the promising application of PCMs in solar-powered cooling systems, demonstrating their capacity to improve thermal comfort and energy efficiency. The choice of PCMs with specific phase change temperatures and heat of fusion is pivotal for optimal system performance. The integration of PV systems with thermoelectric coolers and other renewable energy sources further enhances the overall sustainability and energy utilization in buildings and cooling systems. These findings underscore the potential of PCM-based technology in addressing thermal energy storage challenges and advancing the sustainability of cooling systems and building environments.