Optimization of low-carbon multi-energy systems with seasonal geothermal energy storage: The Anergy Grid of ETH Zurich

Abstract

We investigate the optimal operation of multi-energy systems deploying geothermal energy storage to deal with the seasonal variability of heating and cooling demands. We do this by developing an optimization model that improves on the state-of-the-art by accounting for the nonlinearities of the physical system, and by capturing both the short- and long-term dynamics of energy conversion, storage and consumption. The algorithm aims at minimizing the CO2 emissions of the system while satisfying the heating and cooling demands of given end-users, and it determines the optimal operation of the system, i.e. the mass flow rate and temperature of the water circulating through the network, accounting for the time evolution of the temperature of the geothermal fields.This optimization model is developed with reference to a real-world application, namely the Anergy Grid installed at ETH Zurich, in Switzerland. Here, centralized heating and cooling provision based on fossil fuels is complemented by a dynamic underground network connecting geothermal fields, acting as energy source and storage, and demand end-users requiring heating and cooling energy. The proposed optimization algorithm allows reducing the CO2 emissions of the university campus by up to 87% with respect to the use of a conventional system based on centralized heating and cooling. This improves on the 72% emissions reduction achieved with the current operation strategies. Furthermore, the analysis of the system allows to derive design guidelines and to explain the rationale behind the operation of the system. The study highlights the importance of coupling daily and seasonal energy storage towards the achievement of low-carbon energy systems.

Keywords

• Multi-energy systems
• Seasonal storage
• Geothermal storage
• Energy networks
• MINLP
• Yearly scheduling