Simulation and Data Based Optimisation of an Operating Seasonal Aquifer Thermal Energy Storage

Abstract

Seasonal Aquifer thermal energy storage (ATES) systems have the potential to contribute significantly to reduce the primary energy consumption in energy provision systems. Energy is stored in periods when surplus heat is available and provided to the consumer when energy is demanded. The energetic efficiency of such heat storages in the groundwater determines the environmental and economic performance and is considerably affected by the storage operational mode. Therefore, the analysis and improvement of the actual storage operation is crucial. Combining measured data analysis and the application of numerical ATES models leads to a performance-enhancing storage operation strategy, thus to an overall improved energy utilisation. In this context, a case study of an existing aquifer storage system combined with the identification of general parameter dependencies is discussed. The example presented here is the energy supply system of the German Parliament Buildings in Berlin. Measured operational data from the last 6 years of the heat storage operation were analysed. The analysis shows that the energy recovery factor varies significantly between the annual storage cycles. Since the number of parameters influencing the storage efficiency is too large to be identified by data analysis only, a detailed simulation model based parameter study is carried out. Simulation results show that for the existing storage system the energy recovery factor can be improved with
(a) increasing storage temperature at the warm well,
(b) lowering the injection temperature at the cold well,
(c) increasing the circulated total ground water volume, and (d) increasing the amount of stored thermal energy.