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Dear Reader,
for the 45th issue of our heatbeat Research Newsletter, we are focussing on thermal seasonal storage for district heating networks. We present two new articles on this topic. Solar energy is particularly available in summer, when demand in most heating networks is low. Thermal seasonal storage systems are designed to compensate for this time lag between the high-demand winter and the high-supply summer. Thermal pit storages are often used for this purpose. We have already written about seasonal storage and, in particular, thermal pit storages in one of our previous newsletters ("heatbeat Blog 29"). Thermal pit storages utilise a large volume of water, which is held in large artificial earth basins. In the simplest form, a dam is built with soil, the resulting pool is sealed with foil and the water surface is insulated against heat loss. Thermal pit storage systems can store up to 210,000 m³ of water at 95 °C (Vojens project in Denmark). Efficiencies of up to 90 % have already been proven by measurement. The first article presents a new model in the modelling language Modelica. We at heatbeat also use Modelica for our thermo-hydraulic models. The second article compares two different ways of charging thermal pit storages in summer. Solar thermal collectors are compared with the combination of PV and large heat pumps (air source).
The paper "Development, validation and demonstration of a new Modelica pit thermal energy storage model for system simulation and optimization" by Formhals et al. presents a new model for the simulation and optimisation of thermal energy storage systems. The focus is on the use of the modelling language Modelica to enable integration into system models and thus play a decisive role in the integration and development of new concepts.
The developed model is validated with the help of a model comparison and shows a generally good accuracy in the prediction of temperature profiles and energy losses. Potential for improvement is identified particularly in the modelling of heat transfer to the ground, where the more accurately resolved model (FEM) predicts better results. The authors emphasise that the model can be used for optimisation in energy system models, where it supports the planning process and design of new thermal pit storage systems.
To this end, the model is applied to a case study. The case study is a district heating system that can be fed from three different sources: Solar thermal energy, heat pump (source thermal pit storage) and a peak load boiler. In summer, the thermal pit storage tank is charged with solar thermal energy. The storage tank can be heated up to 90 °C. The use case was optimised on the basis of ecological and economic aspects. The case with and without subsidies was considered. The optimisation model was able to adjust the collector area of the solar thermal system, the storage volume and the size of the heat pump. It was found that the model is well suited for use in optimisations. The results indicate that the use of large seasonal storage systems can only be operated economically with a financial subsidy. Without a subsidy, the optimisation determines significantly smaller storage sizes.
A very common comparison in heat generation systems is the comparison between direct solar thermal energy and the combination of PV and heat pump. The authors Sporleder et al. also make this comparison, but explicitly for the charging of thermal pit storage systems. In their work "Solar thermal vs. PV with a heat pump: A comparison of different charging technologies for seasonal storage systems in district heating networks" they develop an open-source Python optimisatino framwork and apply the framwork on a district heating system in eastern Germany. The linear cost approximations for the main components as a function of the respective size of the system should be emphasised in particular. This relationship is often only described using generalised factors.
The optimisation framework was demonstrated in an extensive application example to compare the two concepts of solar thermal energy and PV + heat pump for charging the thermal pit storage system. The temperature in the storage, the electricity costs of the power supply and the land prices were varied. The results show that both variants have advantages and disadvantages. It can be shown that the electricity price has only little influence on both concepts. This is mainly due to the fact that a large proportion of the electricity for the heat pumps can be covered by the PV system itself. The remaining electricity use (e.g. grid hydraulics) is lower in proportion. The use of solar thermal energy is particularly suitable in less densely populated areas where land prices are lower. However, both concepts require large areas and therefore react sensitively to changes in the price of land. In principle, it can also be stated that the higher the temperature requirements in the network, the more worthwhile thermal pit storage systems are.
As always, we recommend reading the articles in full. From both articles it can be deduced that seasonal storage systems have many technical advantages, but that high costs and the large amount of space required pose a challenge.
The next issue of our newsletter will be published on August 7, 2024.