The Ecovat is a seasonal thermal storage solution consisting of a large underground water tank divided into a number of virtual segments that can be individually charged and discharged. The goal of the Ecovat is to supply heat demand to a neighborhood throughout the entire year. In this work, we extend an integer linear programming model to describe the charging and discharging of such an Ecovat buffer by adding a long-term (yearly) planning step to the model. We compare the results from the model using this extension to previously obtained results and show significant improvements when looking at the combination of costs and the energy content of the buffer at the end of the optimization. Furthermore, we show that the model is very robust against prediction errors. For this, we compare two different cases: one case in which we assume perfect predictions are available and one case in which we assume no predictions are available. The largest observed difference in costs between these two cases is less than 2%.

An increase in the number of volatile renewables in the electricity grid enhances the imbalance of supply and demand. One promising candidate to solve this problem is to improve the energy storage. The Ecovat system is a new seasonal thermal energy storage system currently under development. In this paper, an integer linear programming model is developed to describe the behaviour and potential of this system. Furthermore, it is compared with a previously developed model, which is simplifying the behaviour of the Ecovat system much more, but is much less computationally expensive. It is shown that the new approach performs significantly better for several cases. For controlling a real Ecovat system in the future we may incorporate a number of improvements identified by our comparison analysis into the previously developed approach, which may help increase the quality of the obtained results without increasing the computational effort too much.