Dynamic Energy Management Model: A Catalyst for Carbon Neutrality in Austrian Thermal Baths
Abstract
Austrian thermal baths, significant energy consumers, primarily rely on fossil fuels, posing ecological and economic challenges. This research focuses on optimizing energy consumption by integrating renewable energy sources, such as deep geothermal energy, and enhancing efficiency through innovative technologies like heat pumps and dynamic optimization models. The performed baseline survey of thermal baths identified major energy consumers and potential areas for efficiency improvements. The developed Python-based dynamic simulation program uses Mixed Integer Linear Programming (MILP) to optimize the energy system, considering various energy sources, demands, and storage systems. Key strategies included waste heat utilization, efficiency enhancements in heating, ventilation, and cooling systems, and the integration of photovoltaic systems. The demonstration case in southeast Austria highlighted significant energy savings through the recovery of waste heat from thermal splashing water, air conditioning systems, and drinking water cooling. The optimized system configuration, featuring cascaded heat pumps and stratified storage systems, achieved substantial reductions in both heat and electricity demand. The results underscore the importance of dynamic simulation and optimization in achieving energy efficiency and sustainability in thermal bath operations. The research work provides a reference model for replication in other facilities, contributing to Austria’s broader decarbonization goals.