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Sensible Heat Storage is the most common method of thermal energy storage, particularly in the form of hot water tanks. Essentially, sensible heat storage systems work by charging them with heat from a higher temperature source to raise the temperature of the thermal store, and by extracting heat to discharge them. On a larger scale, these sensible heat stores should be designed to store heat long term over seasons, which allow the thermal storage systems to be charged using solar thermal systems to then supply heat over colder periods and can be applied in an array of buildings, including individual dwellings and larger buildings. These seasonal storage systems consist of: Tank Thermal Energy Storage (TTES), Pit Thermal Energy Storage (PTES), Borehole Thermal Energy Storage (BTES) and Aquifer Thermal Energy Storage (ATES). The aim of this report is to provide useful information about the different construction techniques for the mentioned systems in addition to FP7 Einstein Project, where a big information research has already been done, analysing the main characteristics that interfere in the various proceedings. In addition, a general study for the three different CHESS-SETUP pilots is done regarding the availability and constraints of every case to introduce the different technologies. Finally, in order to ensure the correct operation of the installations, some guidance of the different types of maintenance is done as well as maintenance plans for the different elements of the system.

Underground Energy Storage (UES) Program activities during the period from April 1984 through March 1985 are briefly described. Primary activities in seasonal thermal energy storage (STES) involved field testing of high-temperature (>100/sup 0/C (212/sup 0/F)) aquifer thermal energy storage (ATES) at St. Paul, laboratory studies of geochemical issues associated with high-temperatures ATES, monitoring of chill ATES facilities in Tuscaloosa, and STES linked with solar energy collection. The scope of international activities in STES is briefly discussed.

This is the modeling data (input/output files of TOUGHREACT 4.10) used to simulate the reactive transport processes of the Aquifer Thermal Energy Storage (ATES) operations at Stockton University, NJ. Readme.txt lists all the files. TOUGHREACT 4.10 requires to reproduce the modeling output. The modeling data in this submission is related to the Aquifer Injection for Energy Storage purposes outlined in "Reactive Transport Modeling of Aquifer Thermal Energy Storage System at Stockton, NJ During Seasonal Operations".

Deep reinforcement learning (DRL) has demonstrated its effectiveness in the control of energy systems, although it has not yet been applied to sorption thermal energy storage (TES) systems. The operation of sorption TES systems is notably more complicated compared to other TES variants. The discharge of a sorption TES occurs at a particular desorption and evaporation temperature. Achieving a continuous and efficient discharge of a sorption TES is a challenging control task if heat required at the evaporator is obtained from the sun or the environment. Its operation is especially complicated during winter, because of the limited availability of solar irradiation and low ambient temperatures. Thus, this study analyzes for first time in the literature the competitiveness of deep reinforcement learning to control a solar-driven seasonal sorption TES system and compares it against traditional optimized rule-based control strategy. The system, located in Central Europe, supplied domestic hot water and space heating to a single-family house. Two DRL models were developed and trained to operate the system under two different sets of data: 120 winter consecutive days and 60 winter non-consecutive days. The results showed that the DRL control strategy reduced the system operational costs by 28% in a 60 winter days scenario. For a 120 winter days scenario, the operational cost savings decreased to 13% because the smart control performed worst once the sorption TES was fully discharged. These results were derived from a four-year validation data set, bolstering their robustness. The study demonstrates the successful application of DRL in controlling a solar-driven seasonal sorption TES system, yielding considerable economic savings compared to an RBC strategy. Subsequent work will consist of implementing the smart control strategy at prototype level to assess its performance. This work was partially funded by the Ministerio de Ciencia e Innovación - Agencia Estatal de Investigación, Spain (PID2021-123511OB-C31 - MCIN/AEI/10.13039/501100011033/FEDER, EU) and by the Ministerio de Ciencia, Innovación y Universidades, Spain—Agencia Estatal de Investigación (AEI) (RED2018-102431-T). The authors would also like to thank the Catalan Government for the quality accreditation given to their research group (2017 SGR 1537). GREiA is certified agent TECNIO in the category of technology developers from the Government of Catalonia. Alicia Crespo would also like to acknowledge the financial support of the FI-SDUR grant from the AGAUR of the Generalitat de Catalunya and Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya.

This paper details the use of piece-wise linear regression and non-linear optimisation to determine the heat transfer properties of two ice thermal stores of different volumes (85 m3 and 11 m3). The available energy of each ice storage was determined by the fraction of ice stored in the vessel. The heat loss coefficient was determined using an optimisation algorithm. Using this approach it was possible to determine the heat loss coefficients occurring at different layers of the storage. Validation of the approach yielded a relative mean error of 5.4% and 3.8% for the 85 m3 and 11 m3 storage respectively. This approach is dependent on the measurement of temperature at different segments and the quantity of ice in the storage. It is believed that this approach is scalable and could contribute to a performance database that could provide inputs to energy modelling studies. Journal of Energy Storage, 52 (Part A) ISSN:2352-152X

Laboratory test of a long term heat storage module utilizing the principle of stable supercooling of 199.5 kg of sodium acetate water mixture has been carried out. Avoiding phase separation of the incongruently melting salt hydrate by using the extra water principle increased the heat storage capacity. An external expansion vessel minimized the pressure built up in the module while heating and reduced the risk of instable supercooling. The module was stable supercooled at indoor ambient temperature for up to two months after which it was discharged. The energy discharged after activating the supercooled sodium acetate water mixture was 194 kJ/kg of sodium acetate water mixture in the first test cycles dropping to 179 kJ/kg in the later test cycles. Instability of the supercooling occurred when the charging periods were short and in the last test cycles where the tube connecting the module to the expansion vessel had been blocked by the salt hydrate.

The article estimates energy flexibility provided to the electricity grid by integration of long-term thermal energy storage in buildings. To this end, a liquid sorption storage combined with a compression heat pump is studied for a single-family home. This combination acts as a double-stage heat pump comprised of a thermal and an electrical stage. It lowers the temperature lift to be overcome by the electrical heat pump and thus increases its coefficient of performance. A simplified model is used to quantify seasonal energy flexibility by means of electric load shifting evaluated with a monthly resolution. Results are presented for unlimited and limited storage capacity leading to a total seasonal electric load shift of 631.8 kWh/a and 181.7 kWh/a, respectively. This shift, referred to as virtual battery effect, provided through long-term thermal energy storage is large compared to typical electric battery capacities installed in buildings. This highlights the significance of building-integrated long-term thermal energy storage for provision of energy flexibility to the electricity grid and hence for the integration of renewables in our energy system.

During the many years that thermochemical energy storage has been under investigation, the concept has been plagued with two persistent problems: high capital cost and poor efficiency. Literally hundreds of chemical reactions have also been carried out. For short-term storage, thermochemical systems suffer in comparison with highly efficient sensible storage media such as molten salts. Long-term storage, on the other hand, is not cost-competitive with systems employing fossil backup power. Thermochemical storage will play a significant role in solar thermal electric conversion only under highly select circumstances. The portion of electric demand served by solar plants must be sufficiently high that the balance of the grid cannot fully supplant seasonal storage. High fossil fuel costs must preclude the use of gas turbines for backup power. Significant breakthroughs in the development of one or more chemical reaction systems must occur. Ingeniously integrated systems must be employed to enhance the efficiency and cost-effectiveness of thermochemical storage. A promising integration scheme discussed herein consists of using sensible storage for diurnal cycling in parallel with thermochemical seasonal storage. Under the most favorable circumstances, thermochemical storage can be expected to play a small but perhaps vital role in supplying baseload energy from solar thermal electric more » conversion plants. « less