Organizational and Energy Efficiency Analysis of Italian Hospitals and Identification of Improving AI Solutions - Marino, Alfonso; Pariso, Paolo; Picariello, Michele (International Journal of Energy Economics and Policy, 2024)
This study investigates the integration of Artificial Intelligence (AI) to enhance energy efficiency in Italian hospitals, known for their high energy consumption due to continuous operations and stringent environmental controls. Using AI strategies from the Italian Ministry of Economic Development, the research focuses on optimizing hospital energy management. Analyzing data from 996 major hospitals (2016-2023) revealed an average annual energy consumption of 1,062 kTep. Key parameters were benchmarked against European standards, and MATLAB was utilized for hourly consumption analysis to identify inefficiencies. AI optimization, leveraging historical data, aids in predictive maintenance and reduces equipment downtime. The study underscores the complexities of managing energy in aging hospital infrastructures. Despite the critical need for energy efficiency, many opportunities have been missed due to prioritization of medical technologies and urgent structural repairs. AI offers a solution by enhancing energy management through data analysis, predictive maintenance, and real-time adjustments, leading to significant energy savings and operational improvements. Challenges include high initial investment for AI technology and training, technical integration issues, and variable energy consumption patterns. Nonetheless, the benefits of AI in improving energy efficiency and sustainability in hospitals are substantial, presenting a promising avenue for future research and investment. Strategic AI incorporation can significantly boost operational performance and sustainability, benefiting hospitals across Italy and beyond.