Optimization and advanced control of thermal energy storage systems

Thermal performance study of a solar-coupled phase changes thermal energy storage system for ORC power generation

Thermo-economic analysis and comparative study of different thermally integrated pumped thermal electricity storage systems

A comparison of storage systems in neighbourhood decentralized energy system applications from 2015 to 2050

Thermal performance comparison of three sensible heat thermal energy storage systems during charging cycles

This study involved an assessment of the potential economic benefit of small solar thermal electric power systems to small municipal and rural electric utilities. Five different solar thermal small power system configurations were considered in the study representing three different solar thermal technologies. The configurations included: (1) 1-MW, 2-MW, and 10-MW parabolic dish concentrators with a 15-kW heat engine mounted at the focal point of each dish. These systems utilized advanced battery energy storage. (2) A 10-MW system with variable slat concentrators and central steam Rankine energy conversion. This system utilized sensible thermal energy storage. (3) A 50-MW central receiver system consisting of a field of heliostats concentrating energy on a tower-mounted receiver and a central steam Rankine conversion system. This system also utilized sensible thermal storage. The approach used in determining the potential for solar thermal small power systems in the small utility market involved a comparison of the economics of power supply expansion plans for seven hypothetical small utilities through the year 2000 both with and without the solar thermal small power systems. Insolation typical of the Southwestern US was assumed. A comparison of the break-even capital costs with the range of plant costs estimated in this study yields the following conclusions: (1) The parabolic dish concentrator systems could be economically competitive with conventional generation if the lowest capital costs can be achieved. (2) The variable slat concentrator and central receiver systems would have to achieve lower costs than the lowest in the cost ranges generally assumed in the study to become economically competitive. (3) All of the solar thermal plant types are potentially more competitive in utilities which are heavily dependent upon oil.

Based on results from a one-year intensive monitoring project of a Northern New York commercial building with energy-conserving design features, a thermal storage project was undertaken to optimize the design of a thermal mass storage system for a moderately sized commercial building and transfer the technology to the commercial building sector. A generic commercial building design of 27,000 square feet (2508 m2) was selected for the optimization project. Several different types of thermal mass designs were considered as potentially practical for a commercial building. These included a “sandmass” design such as the mass incorporated in the previously monitored commercial building mentioned above, a foundation slab of sufficient thickness to serve as a significant building thermal mass, and the use of poured cement in interior wall and floor construction. Five different office building thermal designs were selected which represented various thermal storage features and two different building insulation levels (R10 and R20). Energy performance of the five thermal designs was modeled in building energy simulations using DOE 2.1C (Department of Energy 2.1C) energy simulation code. Results of the simulations showed a reduction in peak heating and cooling loads would be experienced by the HVAC equipment. The reduction in peak heating and cooling loads was anticipated because thermal mass within a building serves to average peak heating and cooling loads due to the capacity of the thermal mass to store and release heat from all building heat sources over a period of time. Peak heating loads varied from 1972 kBtuh (578 kW) for the R-10 light construction base case to a minimum of 980 kBtuh (287 kW) for the R-20 heavy construction sandmass storage case. Peak cooling loads dropped from 772 kBtuh (226 kW) for the R-20 light construction case to 588 kBtuh (172 kW) for the R-20 heavy construction sandmass storage case. Results of the simulations also showed annual energy savings for the high thermal mass designs. Energy savings varied from 20 percent [16.0 kBtu/ft2 (50 kWh/m2)] for the R-10 high thermal mass design in comparison to its base case to 18 percent [12.2 kBtu/ft2 (39 kWh/m2)] for the R-20 high thermal mass design in comparison to its base case. The annual energy savings are due to the ability of the thermal mass to absorb heat from all sources of heat generation (lights, occupancy, solar, and auxiliary) during occupied periods and release the heat during unoccupied periods. An optimized thermal design was developed based on results from the DOE 2.1C simulations. The initial cost for the optimized thermal storage design is lower than the initial costs for light construction office buildings, since the lower initial cost of the down-sized HVAC system for the optimized thermal storage design more than offsets the increased cost of wall and floor systems incorporated in the optimized design. Annual energy savings are realized from the high thermal mass system in both cooling and heating modes due to the interaction of building HVAC systems operation in the simulated 27000 ft2 (2508 m2) office building. Annual operating savings of $3781 to $4465 per year are estimated based on simulation results.

The importance and usefulness of second-law analysis for evaluating and comparing thermal energy storage (TES) systems in meaningful ways is discussed. Some of the main thermodynamic factors to be considered in evaluating TES performance are identified and described, including determining important analysis quantities, obtaining appropriate measures of efficiency, pinpointing losses, assessing the effects of stratification, and accounting for time duration of storage. As an illustrative example, exergy analysis, a particular type of second-law analysis, is applied to stratified TES systems in order to evaluate the effects and benefits of thermal stratification. It is concluded based on the results of the example that (i) the use of stratification in thermal storage designs should be considered as it increases the exergy storage capacity of a thermal storage, and (ii) exergy analysis should be applied in the analysis and comparison of stratified thermal storage systems.

In this study, supervised machine learning (ML) regression models are employed to predict water uptake during the sorption process in a sorption reactor for thermal energy storage applications. Two main methods are used to study sorption storage systems: experimental studies and numerical simulations. Experimental studies involve physical testing and measurements but are often costly and time-consuming. Numerical simulations are more flexible and cost-effective, though they can require significant computational resources for large or complex systems. To address these challenges, researchers are increasingly employing various machine learning techniques, which offer strong potential for data analysis and predictive modeling. In this study, CFD-based sorption simulations are integrated with machine learning models to predict the spatiotemporal evolution of water uptake. Several ML techniques including support vector regression (SVR), Random Forest, XGBoost, CatBoost (gradient boosting decision trees), and multilayer perceptron neural networks (MLPs) are evaluated and compared. A fixed-bed reactor equipped with fins and tubes is considered within a closed adsorption thermal storage system. Numerical simulations are conducted for three different fin lengths (10 mm, 25 mm, and 35 mm) to generate a comprehensive dataset for training the ML models and capturing the complex temporal evolution of water uptake, thereby enabling predictions for unseen fin geometries. The results indicate that neural network-based models achieve superior predictive performance compared to the other methods. For water uptake training, the mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination R2 are approximately 2.83, 4.37, and 0.91, respectively. The predicted water uptake shows close agreement with the numerical simulation results. For the prediction cases, the MAE, MSE, and R2 values are approximately 1.13, 1.2, and 0.8, respectively. Overall, the study demonstrates that machine learning models can accurately predict water uptake beyond the training dataset, indicating strong generalization capability and significant potential for improving thermal management system design. Additionally, the proposed approach reduces simulation time and computational cost while providing an efficient and reliable framework for modeling complex sorption processes in thermal energy storage systems.

The growing global energy demand necessitates advanced thermal energy storage solutions to enhance energy efficiency and sustainability. This study addresses the optimization of thermal energy storage systems by integrating artificial intelligence, dual-phase change materials, and nanoparticle additives. Utilizing a cylindrical thermal storage system with two different phase change materials - vaseline containing 1% Al<sub>2</sub>O<sub>3</sub> nanoparticles and pure wax - both open and closed configurations were analyzed. The performance was assessed using an artificial neural network model trained on 575 temperature profiles. Results indicate that the dual-phase change materials system with nanoparticles significantly enhances heat retention, maintaining 305°C for 4 h and achieving 73% efficiency, compared to 45% and 50% for single-phase change materials without and with additives, respectively. Artificial intelligence integration demonstrated high prediction accuracy, with a mean squared error of 0.0289 and coefficient of determination of 0.998. Integrating artificial intelligence with dual-phase change material technology, this innovative method can provide a powerful, effective, and intelligent thermal energy storage system that can cope with various environmental and operating situations.

Preparation and performance improvement of chlorides/MgO ceramics shape-stabilized phase change materials with expanded graphite for thermal energy storage system

We have developed the open-cycle type adsorbent thermal storage system, so called “Mega Stock”. Based on adsorbent of HAS-Clay, the thermal storage system can utilize the low-temperature waste heat. In the offline heat transportation type, the thermal storage tank charged in the co-generation system was transported by the tractorftrailer and used to heat up water and air in a swimming center. The adsorption heat storage system was evaluated through three kinds of seasons: summer, interphase, and winter. By the tests the regenerating efficiency of 90% or more was confirmed. On the other hand, we performed the demonstration test of the offline heat transportation from the charged thermal storage in the co-generation system to the air handling unit （AHU） of painting process by the tractor. The energy consumption of the cold and hot water used in AHU decreased by dehumidifying the air which flowed into AHU with the thermal storage tank. And, the CO2 reduction effect of 57% was confirmed from the test.

Experimental studies on thermophysical properties of protic ionic liquids for thermal energy storage systems

With a large capacity thermal storage system using phase change material (PCM), Concentrated Solar Power (CSP) is a promising technology for high efficiency of solar energy utilization. In a thermal storage system, a dual-media thermal storage tank is typically adopted in industry for the purpose of reducing the use of the heat transfer fluid (HTF). While the dual-media sensible heat storage system has been well studied, a dual-media latent heat storage system (LHSS) still needs more attention and study; particularly, the sizing of volumes of storage tanks considering actual operation conditions is of significance. In this paper, a strategy for LHSS volume sizing is proposed, which is based on computations using an enthalpy-based 1D model. One example of 60MW solar thermal power plant with 35% thermal efficiency is presented. In the study, potassium hydroxide (KOH) is adopted as PCM and Therminol VP-1 is used as HTF. The operational temperatures of the storage system are 390°C and 310°C, respectively for the high and low temperatures. The system is assumed to operate for 100 days with 6 hours charge and 6 hours discharge every day. From the study, the needed height of the thermal storage tank is calculated from using the strategy of tank sizing. The method for tank volume sizing is of significance to engineering application.

Numerical study and multilayer perceptron-based prediction of melting process in the latent heat thermal energy storage system with a finned elliptical inner cylinder

Energetic, economic and environmental benefits of utilizing the ice thermal storage systems for office building applications